# templates

name: Deploy Docker InfluxDB, API Backend for WHMCS/WISECP
author_name: PUQcloud
author_username: puqcloud
categories: []
created_at: 2025-05-13T11:48:09.439Z
updated_at: 2025-05-13T11:48:09.439Z
url: https://n8n.io/workflows/4014
scraped_at: 2026-05-02 08:04:51
metadata_generated_at: 2026-05-02 08:36:21
description:
  Overview

  The Docker InfluxDB WHMCS module uses a specially designed workflow for n8n to automate deployment processes. The workflow provides an API interface for the module, receives specific commands, and connects via SSH to a server with Docker installed to perform predefined actions.

  Prerequisites

  You must have your own n8n server.
  Alternatively, you can use the official n8n cloud installations available at: n8n Official Site

  Installation Steps

  Install the Required Workflow on n8n

  You have two options:

  Option 1: Use the Latest Version from the n8n Marketplace

  The latest workflow templates for our modules are available on the official n8n marketplace.
  Visit our profile: PUQcloud on n8n

  Option 2: Manual Installation

  Each module version comes with a workflow template file.  
    
  You need to manually import this template into your n8n server.  
  n8n Workflow API Backend Setup for WHMCS/WISECP

  1. Configure API Webhook and SSH Access

  Create a Basic Auth Credential for the Webhook API block in n8n.  
      
      
    

  Create an SSH Credential for accessing a server with Docker installed.  
  2. Modify Template Parameters

  In the Parameters block of the template, update the following settings:  
    


  server_domain – Must match the domain of the WHMCS/WISECP Docker server.
  clients_dir – Directory where user data related to Docker and disks will be stored.
  mount_dir – Default mount point for the container disk (recommended not to change).

  Do not modify the following technical parameters:

  screen_left
  screen_right

  Deploy-docker-compose

  In the Deploy-docker-compose element, you can modify the Docker Compose configuration. This is generated in the following scenarios:

  When the service is created
  When the service is unlocked
  When the service is updated

  nginx

  In the nginx element, you can modify configuration parameters of the web interface proxy server.

  The main section allows you to add custom parameters to the server block in the proxy server configuration file.
  The main_location section contains settings that will be added to the location / block of the configuration. Here, you can define custom headers and parameters.

  Bash Scripts

  Management of Docker containers and related procedures is done by executing Bash scripts generated in n8n. These scripts return either JSON or plain strings.

  All scripts are located in elements directly connected to the SSH element.
  You have full control over any script and can modify or execute it as needed.

nodes_used:
  ["n8n-nodes-base.if","n8n-nodes-base.set","n8n-nodes-base.webhook","n8n-nodes-base.respondToWebhook","n8n-nodes-base.code","n8n-nodes-base.ssh","n8n-nodes-base.switch","n8n-nodes-base.switch","n8n-nodes-base.respondToWebhook","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.stickyNote","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.if","n8n-nodes-base.set","n8n-nodes-base.switch","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.switch","n8n-nodes-base.set"]

workflow_json_compressed:
  [encoded data, 13188 characters]

metadata_json:
  {"categories":["DevOps","Automation"],"complexity":"medium","use_cases":["deploy containerized databases against WHMCS customizations and WISECP integrations","manage Docker container lifecycle via SSH on remote servers","automate API backend setup for billing platforms"],"estimated_setup_minutes":45,"required_services":["WHMCS","Docker","SSH","n8n"],"key_features":["SSH execution for remote command provisioning","multi-condition branching for API request routing","webhook-based CRUD operations for billing module management"],"target_audience":["DevOps engineers","WHMCS administrators","software integrators"]}


name: Deploy Docker NextCloud, API Backend for WHMCS/WISECP
author_name: PUQcloud
author_username: puqcloud
categories: []
created_at: 2025-05-13T11:55:54.871Z
updated_at: 2025-05-13T11:55:54.871Z
url: https://n8n.io/workflows/4015
scraped_at: 2026-05-02 08:04:51
metadata_generated_at: 2026-05-02 08:36:20
description:
  Overview

  The Docker NextCloud WHMCS module leverages a sophisticated workflow for n8n, designed to automate the comprehensive deployment, configuration, and management processes for NextCloud and NextCloud Office services.

  Through its intuitive API interface, the workflow securely receives commands and orchestrates predefined tasks via SSH on your Docker-hosted server, ensuring streamlined operations and efficient management.

  Prerequisites

  You must deploy your own dedicated n8n server to manage workflows effectively.
  Alternatively, you may opt for the official n8n cloud-based solutions accessible via: n8n Official Site
  Your Docker server must be accessible via SSH with necessary permissions.

  Installation Steps

  Install the Required Workflow on n8n

  You can select from two convenient installation options:

  Option 1: Use the Latest Version from the n8n Marketplace

  The latest workflow templates are continuously updated and available on the n8n marketplace.
  Explore all templates provided by PUQcloud directly here: PUQcloud on n8n

  Option 2: Manual Installation

  Each module version includes a bundled workflow template file.  
    
  Import this workflow file directly into your n8n server manually.  
  n8n Workflow API Backend Setup for WHMCS

  Configure API Webhook and SSH Access

  Create a secure Basic Auth Credential for Webhook API interactions within n8n.  
    
  Create an SSH Credential within n8n to securely communicate with the Docker host.  
  Modify Template Parameters

  Adjust and update the following critical parameters to match your deployment specifics:  


  server_domain – Set this to the domain of your WHMCS Docker server.
  clients_dir – Specify the directory where user data and related resources will be stored.
  mount_dir – The standard mount point for container storage (recommended to remain unchanged).

  Do not alter the following technical parameters to avoid workflow disruption: screen_left, screen_right.

  Deploy-docker-compose Configuration

  Fine-tune Docker Compose configurations tailored specifically for these critical operational scenarios:

  Initial service provisioning and setup
  Service suspension and subsequent unlocking
  Service configuration updates
  Routine service maintenance tasks

  nginx Configuration Management

  Enhance and customize proxy server configurations using the dedicated nginx workflow element:

  main**: Define specialized parameters within the server configuration block.
  main_location**: Set custom headers, caching policies, and routing rules for the root location.

  Bash Script Automation

  Automate Docker container management and related server tasks through dynamically generated Bash scripts within n8n. Scripts execute securely via SSH and provide responses in JSON or plain text formats for easy parsing and logging.

  Scripts are conveniently linked directly to the SSH action elements.
  You retain complete flexibility to adapt or extend these scripts as necessary to meet your precise operational requirements.

nodes_used:
  ["n8n-nodes-base.if","n8n-nodes-base.set","n8n-nodes-base.webhook","n8n-nodes-base.respondToWebhook","n8n-nodes-base.switch","n8n-nodes-base.switch","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.stickyNote","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.switch","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.switch","n8n-nodes-base.if","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.if","n8n-nodes-base.code","n8n-nodes-base.switch","n8n-nodes-base.set","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.respondToWebhook","n8n-nodes-base.ssh","n8n-nodes-base.ssh","n8n-nodes-base.switch","n8n-nodes-base.code","n8n-nodes-base.respondToWebhook"]

workflow_json_compressed:
  [encoded data, 21856 characters]

metadata_json:
  {"categories":["DevOps","Infrastructure","API Automation"],"complexity":"medium","use_cases":["deploy NextCloud instances","configure Docker containers","manage WHMCS modules","orchestrate SSH commands","automate server setup"],"estimated_setup_minutes":30,"required_services":["Docker","WHMCS","SSH","n8n"],"key_features":["modular Docker deployment","SSH-based automation","WHMCS integration","webhook driven control","service configuration"],"target_audience":["devops engineers","system administrators","infrastructure developers"]}


name: Automate Daily YouTrack Task Summaries to Discord by Assignee
author_name: Halfbit 🚀
author_username: halfbit
categories: []
created_at: 2025-05-13T14:12:27.024Z
updated_at: 2025-05-13T14:12:27.024Z
url: https://n8n.io/workflows/4019
scraped_at: 2026-05-02 08:04:51
metadata_generated_at: 2026-05-02 08:36:21
description:
  Daily YouTrack In-Progress Tasks Summary to Discord by Assignee

  Keep your team in sync with a daily summary of tasks currently In Progress in YouTrack — automatically posted to your Discord channel.

  This workflow queries issues, filters them by status, groups them by assignee and priority, and sends a formatted message to Discord. It's perfect for teams that need a lightweight, automated stand-up report.

  &gt; 📝 This workflow uses Discord as an example. You can easily replace the messaging integration with Slack, Mattermost, MS Teams, or any other platform that supports incoming webhooks.

  Use Case

  Remote development teams using YouTrack + Discord
  Replacing daily stand-up meetings with async updates
  Project managers needing quick visibility into active tasks

  Features

  Scheduled** daily execution (default: weekdays at 09:00)
  Status filter**: only issues marked as In Progress
  Grouping** by assignee and priority
  Custom mapping** for user mentions (YouTrack → Discord)
  Clean Markdown output** for Discord, with direct task links

  Setup Instructions

  YouTrack Configuration

  Get a permanent token:
     Go to your YouTrack profile → Account Security → Authentication
     Create a new permanent token with "Read Issue" permissions
     Copy the token value

  Set the base API URL:
     Format: https://yourdomain.youtrack.cloud/api/issues
     Replace yourdomain with your actual YouTrack instance

  Identify custom field IDs:
     Method 1: Go to YouTrack → Administration → Custom Fields → find your "Status" field and note its ID
     Method 2: Use API call GET /api/admin/customFieldSettings/customFields to list all field IDs
     Method 3: Inspect a task's API response and look for field IDs in the customFields array
     Example Status field ID: 105-0 or 142-1

  Discord Configuration

  Create a webhook URL in your Discord server:
    Server Settings → Integrations → Webhooks → New Webhook
    Choose target channel and copy the webhook URL
    Extract webhook ID from URL (numbers after /webhooks/)

  Environment Variables & Placeholders

  | Placeholder | Description |
  |-------------|-------------|
  | {{API_URL}} | Your YouTrack API base URL |
  | {{TOKEN}} | YouTrack permanent token |
  | {{FIELD_ID}} | ID of the "Status" custom field |
  | {{QUERY_FIELDS}} | Fields to fetch (e.g., summary, id) |
  | {{PROJECT_LINK}} | Link to your YouTrack project |
  | {{USER_X}} | YouTrack usernames |
  | {{DISCORD_ID_X}} | Discord mentions or usernames |
  | {{NAME_X}} | Display names |
  | {{WEBHOOK_ID}} | Discord webhook ID |
  | {{DISCORD_CHANNEL}} | Discord channel name |
  | {{CREDENTIAL_ID}} | Your credential ID in n8n |

  Testing the Workflow

  Test YouTrack connection:
     Execute the "HTTP Request YT" node individually
     Verify that issues are returned from your YouTrack instance
     Check if the Status field ID is correctly filtering tasks

  Verify filtering:
     Run the "Filter fields" node
     Confirm only "In Progress" tasks pass through

  Check message formatting:
     Execute the "Discord message" node
     Review the generated message content and formatting

  Test Discord delivery:
     Run the complete workflow manually
     Verify the message appears in your Discord channel

  Schedule verification:
     Enable the workflow
     Test weekend skip functionality by temporarily changing dates

  Customization Tips

  Language**: All labels/messages are in English — customize if needed
  User mapping**: Adjust assignee → Discord mention logic in the message builder
  Priorities**: Update the priorityMap to reflect your own naming structure
  Schedule**: Modify the trigger time in the Schedule Trigger node
  Alternative platforms**: Swap out the Discord webhook for another messaging service if preferred

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.code","n8n-nodes-base.if","n8n-nodes-base.httpRequest","n8n-nodes-base.filter","n8n-nodes-base.code","n8n-nodes-base.discord","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
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metadata_json:
  {"categories":["Communication","DevOps"],"complexity":"medium","use_cases":["daily task summaries","aggregated status reports","stand-up automation"],"estimated_setup_minutes":30,"required_services":["YouTrack","Discord","HTTP/Webhooks"],"key_features":["scheduled daily runs","grouping by assignee","priority filtering","custom message formatting"],"target_audience":["project managers","devops engineers","sre teams"]}


name: Extract & Categorize Receipt Data with Google OCR, OpenRouter AI & Telegram
author_name: Khairul Muhtadin
author_username: khmuhtadin
categories: []
created_at: 2025-05-13T14:12:43.145Z
updated_at: 2025-05-13T14:12:43.145Z
url: https://n8n.io/workflows/4020
scraped_at: 2026-05-02 08:04:50
metadata_generated_at: 2026-05-02 08:36:20
description:
  Effortlessly track your expenses with MoneyMate, an n8n workflow that transforms receipts into organized financial insights.

  Upload a photo or text via Telegram, and let MoneyMate extract key details—store info, transaction dates, items, and totals—using Google Vision OCR and AI-powered parsing via OpenRouter.

  It categorizes expenses (e.g., Food & Beverages, Transport, Household) and delivers a clean, emoji-rich summary back to your Telegram chat. Handles zero-total errors with a friendly nudge to double-check inputs.

  Perfect for freelancers, small business owners, or anyone seeking hassle-free expense management. No database required, ensuring privacy and simplicity. Deploy MoneyMate and take control of your finances today!

  Key Features
  📱 Telegram Integration: Input via photo or text, receive summaries instantly.
  📸 Receipt Scanning: Converts receipt images to text using Google Vision API.  
  🤖 AI Parsing: Categorizes transactions with OpenRouter’s AI analysis.   
  🛡️ Privacy-First: Processes data on-the-fly without storage.  
  ⚠️ Smart Error Handling: Catches zero totals with user-friendly prompts.  
  📊 Flexible Categories: Supports Income/Expense and custom expense types.  

  Ideal For
  Budget-conscious individuals** managing personal finances.  
  Entrepreneurs** tracking business expenses.  
  Teams** needing quick, automated expense reporting.  

  Pre-Requirements
  n8n Instance:** A running n8n instance (cloud or self-hosted).  
  Credentials:**  
    Telegram: A bot token and webhook setup (obtained via BotFather). For more information, please refer to Telegram bots creation
    Google Cloud: A service account with Google Vision API enabled and API key. For more informations, please refer to Google cloud Vision  
    OpenRouter: An account with API access for AI language model usage.  
  Telegram Bot:* A configured *Telegram** bot to receive inputs and send summaries.  

  Setup Instructions
  Import Workflow:* Copy the *MoneyMate** workflow JSON and import it into your n8n instance using the "Import Workflow" option.  
  Set Up Telegram Bot:* Create a bot via BotFather on *Telegram** to get a token and set up a webhook. For detailed steps, refer to n8n’s Telegram setup guide.  
  Configure Credentials:**  
    In the Telegram Trigger, Send Error Message, and Send Expense Summary nodes, add Telegram API credentials with your bot token.  
    In the Get Telegram File and Download Image nodes, ensure Telegram API credentials are linked.  
    In the Google Vision OCR node, add Google Cloud credentials with Google Vision API access.  
    In the OpenRouter AI Model node, set up OpenRouter API credentials.  
  Test the Workflow:* Send a test receipt photo or text (e.g., "Lunch 50,000 IDR") via *Telegram** and verify the summary in your chat.  
  Activate:** Enable the workflow in n8n to run automatically for each input.  

  Customization Options
  Add Categories:* Modify the *AI Categorizer* node to include new expense types (e.g., *Entertainment**).  
  Change Output Format:* Adjust the *Format Summary Message** node to include more details like taxes or payment methods.  
  Switch AI Model:* In the *OpenRouter AI Model* node, select a different *OpenRouter** model for better parsing.  
  Store Data:* Add a *Google Sheets* node after *Parse Receipt Data** to save expense records.  
  Enhance Errors:* Include an email notification node after *Check Invalid Input** for failed inputs.  

  Why Choose MoneyMate?
  Save time, reduce manual entry, and gain clarity on your spending with MoneyMate’s AI-driven workflow. Ready to streamline your finances? Get MoneyMate now!


  Made by: khmuhtadin
  Need a custom? contact me on LinkedIn or Web

nodes_used:
  ["n8n-nodes-base.code","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.telegramTrigger","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.chainLlm","n8n-nodes-base.if","n8n-nodes-base.set","n8n-nodes-base.if","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.outputParserStructured","@n8n/n8n-nodes-langchain.lmChatOpenRouter","n8n-nodes-base.telegram","n8n-nodes-base.telegram","n8n-nodes-base.stickyNote","n8n-nodes-tesseractjs.tesseractNode","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 5904 characters]

metadata_json:
  {"categories":["Finance","AI/ML","Communication"],"complexity":"medium","use_cases":["expense tracking","receipt categorization","financial data extraction"],"estimated_setup_minutes":30,"required_services":["Telegram","Google Vision API","OpenRouter (LLM)","Tesseract OCR"],"key_features":["GGP/GCP integration","AI-powered text extraction","smart categorization","emoji-enhanced messaging"],"target_audience":["small business owners","freelancers","finance managers"]}


name: AI-Optimized Content Posting to X, Discord & LinkedIn with OpenRouter
author_name: Khairul Muhtadin
author_username: khmuhtadin
categories: []
created_at: 2025-05-13T14:18:13.939Z
updated_at: 2025-05-13T14:18:13.939Z
url: https://n8n.io/workflows/4022
scraped_at: 2026-05-02 08:04:50
metadata_generated_at: 2026-05-02 08:36:20
description:
  Amplify your social media presence with BuzzBlast, an n8n workflow designed to make your content go viral across X, Discord, and LinkedIn. By sending a single chat message, BuzzBlast leverages OpenRouter's AI to optimize your input for each platform’s unique audience—crafting punchy tweets for X, engaging messages for Discord, and professional posts for LinkedIn. With smart language detection, it ensures the output matches your input’s language for authentic engagement.

  Key Features

  🚀 Multi-Platform Posting: Shares optimized content to X, Discord, and LinkedIn simultaneously.
  🧠 AI Optimization: Uses OpenRouter’s AI to tailor content for virality on each platform.
  🌐 Language Detection: Matches output to your input language for seamless engagement.
  🔄 Smart Routing: Automatically directs content to the right platform using a switch node.
  📱 Chat Trigger: Initiates posts via a simple chat message.
  ⚡ Zero Hassle: No manual reformatting—BuzzBlast handles it all.

  Ideal For

  Social media managers looking to streamline cross-platform posting.
  Content creators aiming to boost engagement with minimal effort.
  Businesses seeking to maximize reach across diverse audiences.

  Pre-Requirements

  n8n instance**: A running n8n instance (cloud or self-hosted).
  Credentials**:
    X account with OAuth2 API access.
    Discord Webhook API setup for your server.
    LinkedIn account with OAuth2 API access.
    OpenRouter account for AI language model access.
  Chat Trigger Setup**: A configured chat platform (e.g., Slack, Telegram) to send input messages to the workflow.

  Setup Instructions

  Import the Workflow:
     Copy the provided workflow JSON and import it into your n8n instance via the "Import Workflow" option in the n8n editor.
  Configure Credentials:
     In the Post to X node, set up OAuth2 credentials for your X account.
     In the Post to Discord node, configure a Discord Webhook for your server.
     In the Post to LinkedIn node, add OAuth2 credentials for your LinkedIn account.
     In the OpenRouter AI Model node, provide API credentials for your OpenRouter account.
  Set Up Chat Trigger:
     In the Chat Input Trigger node, configure your preferred chat platform (e.g., Slack, Telegram) to send trigger messages.
     Ensure the webhook is active and correctly linked to your chat platform.
  Test the Workflow:
     Send a test message via your chat platform (e.g., "Announcing our new product launch!").
     Verify that the AI optimizes the content and posts it to X, Discord, and LinkedIn as expected.
  Activate the Workflow:
     Once tested, toggle the workflow to "Active" in n8n to enable automatic execution when chat messages are received.

  Customization Guidance
  Changes Chat Trigger**: Adjust the chat trigger using your preference platform like telegram, discord, etc.
  Modify AI Prompt**: Adjust the prompt in the AI Content Optimizer node to change the tone or style (e.g., more professional for LinkedIn or conversational for Discord).
  Add New Platforms**: Extend the Route to Platforms node by adding conditions for additional platforms (e.g., Instagram or Facebook) and corresponding posting nodes.
  Change AI Model**: In the OpenRouter AI Model node, select a different OpenRouter model to optimize content quality or manage costs.
  Enhance Output Format**: Update the JSON schema in the Parse AI Output node to include additional fields like hashtags, emojis, or links for specific platforms.
  Add Error Handling**: Include an error-handling node after the Route to Platforms node to log failed posts or retry them automatically.

  Why Choose BuzzBlast?

  BuzzBlast saves time, maximizes reach, and lets AI craft platform-perfect posts that resonate with your audience. Whether you're an influencer, marketer, or business, this workflow makes cross-platform posting effortless. Ready to make waves online? Grab BuzzBlast and start buzzing!

  made by: khmuhtadin
  Need a custom? contact me on LinkedIn or Web

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.lmChatOpenRouter","@n8n/n8n-nodes-langchain.outputParserStructured","n8n-nodes-base.stickyNote","n8n-nodes-base.splitOut","n8n-nodes-base.switch","n8n-nodes-base.twitter","n8n-nodes-base.linkedIn","n8n-nodes-base.discord","@n8n/n8n-nodes-langchain.chatTrigger","@n8n/n8n-nodes-langchain.chainLlm"]

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metadata_json:
  {"categories":["Marketing"],"complexity":"medium","use_cases":["content optimization","social scheduling","cross-platform posting"],"estimated_setup_minutes":15,"required_services":["OpenRouter","X","LinkedIn","Discord"],"key_features":["AI-generated content adaptation","multi-language support","single-input multi-platform output"],"target_audience":["marketers","social media managers","content creators"]}


name: Conversational Kubernetes Management with GPT-4o and MCP Integration
author_name: Reza Gholizade
author_username: reza-gholizade
categories: []
created_at: 2025-05-13T14:20:56.900Z
updated_at: 2025-05-13T14:20:56.900Z
url: https://n8n.io/workflows/4023
scraped_at: 2026-05-02 08:04:49
metadata_generated_at: 2026-05-02 08:36:20
description:
  This n8n workflow template uses community nodes and is only compatible with the self-hosted version of n8n. 

  Conversational Kubernetes Management with GPT-4o and MCP Integration

  This workflow enables you to manage Kubernetes clusters conversationally using OpenAI’s GPT-4o and a secure MCP (Model Context Protocol) server. It transforms natural language queries into actionable Kubernetes commands via a lightweight MCP API gateway — perfect for developers and platform engineers seeking to simplify cluster interaction.

  🚀 Setup Instructions

  Import the Workflow  
     Upload this template to your n8n instance.

  Configure Required Credentials
     OpenAI API Key: Add your GPT-4o API key in the credentials.
     MCP Client Node: Set the URL and auth for your MCP server.

  Test Kubernetes Access  
     Ensure your MCP server is correctly configured and has access to the target Kubernetes cluster.

  🧩 Prerequisites

  n8n version 0.240.0 or later  
  Access to GPT-4o via OpenAI  
  A running MCP server  
  Kubernetes cluster credentials configured in your MCP backend

  ⚠️ Community Nodes Disclaimer

  This workflow uses custom community nodes (e.g., MCP Client).  
  Make sure to review and trust these nodes before running in production.

  🛠️ How It Works

  A webhook or chat input triggers the conversation.
  GPT-4o interprets the message and generates structured Kubernetes queries.
  MCP Client securely sends requests to your cluster.
  The result is returned and formatted for easy reading.

  🔧 Customization Tips 

  Tweak the GPT-4o prompt to match your tone or technical level.   
  Extend MCP endpoints to support new Kubernetes actions.  
  Add alerting or monitoring integrations (e.g., Slack, Prometheus). 

  🖼️ Template Screenshot

  🧠 Example Prompts

  Show me all pods in the default namespace.
  Get logs for nginx pod in kube-system.
  List all deployments in staging.

  📎 Additional Resources

  MCP Server on GitHub  
  OpenAI Documentation  
  n8n Docs  

  Build smarter Kubernetes workflows with the power of AI !

nodes_used:
  ["@n8n/n8n-nodes-langchain.chatTrigger","@n8n/n8n-nodes-langchain.agent","n8n-nodes-mcp.mcpClientTool","n8n-nodes-mcp.mcpClientTool","n8n-nodes-mcp.mcpClientTool","n8n-nodes-mcp.mcpClientTool","n8n-nodes-mcp.mcpClientTool","n8n-nodes-mcp.mcpClientTool","n8n-nodes-mcp.mcpClientTool","n8n-nodes-mcp.mcpClientTool","n8n-nodes-mcp.mcpClientTool","n8n-nodes-mcp.mcpClientTool","@n8n/n8n-nodes-langchain.mcpTrigger","@n8n/n8n-nodes-langchain.mcpTrigger","@n8n/n8n-nodes-langchain.memoryBufferWindow","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-mcp.mcpClientTool","n8n-nodes-mcp.mcpClientTool","n8n-nodes-mcp.mcpClientTool","n8n-nodes-mcp.mcpClientTool","n8n-nodes-mcp.mcpClientTool","n8n-nodes-mcp.mcpClientTool","n8n-nodes-mcp.mcpClientTool","n8n-nodes-mcp.mcpClientTool","n8n-nodes-mcp.mcpClientTool","@n8n/n8n-nodes-langchain.mcpClientTool","@n8n/n8n-nodes-langchain.mcpClientTool"]

workflow_json_compressed:
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metadata_json:
  {"categories":["DevOps","AI/ML"],"complexity":"medium","use_cases":["Conversational cluster management","Natural language to command translation","Kubernetes lifecycle operations","Secure MCP protocol integration"],"estimated_setup_minutes":30,"required_services":["OpenAI (GPT-4o)","Kubernetes API"],"key_features":["Model Context Protocol (MCP) integration","Natural language query parsing","Kubernetes command execution via API","Conversational GUI interface","Secure ledgerless interaction"],"target_audience":["Platform engineers","System administrators","DevOps practitioners"]}


name: Generate & Publish SEO-Optimized WordPress Blog Posts with AI
author_name: Khairul Muhtadin
author_username: khmuhtadin
categories: []
created_at: 2025-05-13T14:29:01.632Z
updated_at: 2025-05-13T14:29:01.632Z
url: https://n8n.io/workflows/4024
scraped_at: 2026-05-02 08:04:49
metadata_generated_at: 2026-05-02 08:36:19
description:
  Generate and Publish SEO-Optimized Blog Posts to WordPress


  This n8n workflow, BlogBlitz, automates the creation and publishing of SEO-optimized blog posts for WordPress, saving you hours of content creation time. Triggered via Telegram or a scheduled interval, it generates 1,500–2,500-word articles on Technology, AI, Tech Facts, History, or Tips, complete with catchy titles, slugs, meta descriptions, and realistic featured images. Perfect for bloggers and marketers, BlogBlitz ensures your site stays fresh with high-quality content.

  Who is this for?
  Bloggers, content marketers, and WordPress site owners who want to automate high-quality, SEO-ready blog content creation without manual writing or formatting.

  What problem is this workflow solving?
  Manually creating engaging, SEO-optimized blog posts is time-consuming and requires expertise. BlogBlitz solves this by automating the entire process—from generating ideas and writing articles to publishing and notifying you—keeping your site active and discoverable.

  What this workflow does
  Triggers**: Runs every 3 hours via a Schedule Trigger or on-demand with a Telegram command (“generate”).  
  Generates Content**: Uses OpenRouter to pick a category (e.g., Technology, AI) and create a title, slug, focus keyphrase, and meta description.  
  Writes Articles**: OpenAI crafts 1,500–2,500-word posts with SEO-friendly structure, headings, and a call-to-action.  
  Adds Visuals**: Generates realistic featured images with OpenAI and uploads them to WordPress.  
  SEO Features**: Generate optimized slug, focus keyphrase, meta description
  Publishes**: Posts articles to WordPress with proper categories and featured images.  
  Notifies**: Sends publish alerts with links to Discord and Telegram.  

  Setup
  n8n instance (Cloud or self-hosted): Ensure you have a cloud or self-hosted n8n instance.  
  Credentials:  
     WordPress: API access for wp-json/wp/v2 endpoint.  
     OpenAI: For article and image generation.  
     OpenRouter: For title and category generation.  
     Telegram: Bot API for triggers and notifications.  
     Discord: Webhook for publish alerts.  
  WordPress Configuration:  
     Set up categories (Technology [ID:3], AI [ID:4], Tech Fact [ID:7], Tech History [ID:8], Tech Tips [ID:9]).  
     Ensure an admin user ID is available (default: 1).   
  Node Setup:  
     Use the Edit Fields node to centralize variables like category IDs.  
  Test: Send “generate” via Telegram to test the workflow. Check WordPress for the published post.  

  How to customize this workflow to your needs
  Change Categories**: Update the WordPress Post Draft node to match your site’s category IDs.  
  Adjust Schedule**: Modify the Schedule Trigger node for different intervals (e.g., daily).  
  Tweak Tone**: Edit the prompt in the Basic LLM Chain node for a different writing style (e.g., formal or casual).  
  Add Platforms**: Extend notifications to Slack or email by adding nodes.  
  Image Style**: Adjust the OpenAI image node for different sizes or styles (e.g., “natural” instead of “vivid”).  

  Pre-Requirements
  n8n Instance**: Cloud or self-hosted.  
  Credentials**:  
    WordPress API (wp-json/wp/v2 endpoint).  
    OpenAI API for text and images.  
    OpenRouter API for AI content.  
    Telegram bot API.  
    Discord Webhook API.  
  Dependencies**: @n8n/n8n-nodes-langchain package.  
  WordPress Setup**: Categories and admin user ID configured.  
  Network**: Stable internet for API calls.  

  Made by: Khaisa Studio  
  Tag: youtube, summarizer, telegram, openai  
  Category: AI Automation, Video Tools
  Need a custom? Contact Me

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  ["@n8n/n8n-nodes-langchain.chainLlm","@n8n/n8n-nodes-langchain.chainLlm","@n8n/n8n-nodes-langchain.outputParserStructured","n8n-nodes-base.wordpress","@n8n/n8n-nodes-langchain.openAi","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.scheduleTrigger","@n8n/n8n-nodes-langchain.lmChatOpenRouter","n8n-nodes-base.discord","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.telegramTrigger","n8n-nodes-base.if","n8n-nodes-base.telegram","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
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metadata_json:
  {"categories":["Marketing"],"complexity":"medium","use_cases":["automate blog post creation","publish SEO-optimized content","schedule articles automatically","generate content with AI"],"estimated_setup_minutes":30,"required_services":["Telegram","WordPress","OpenRouter","Discord"],"key_features":["AI-generated long-form content","SEO optimization","automatic image generation","scheduled publishing"],"target_audience":["Marketers","Bloggers","Content creators"]}


name: Stacey – Your Telegram AI Assistant (Powered by MCP, Gemini & Google Tools)
author_name: David Olusola
author_username: dae221
categories: []
created_at: 2025-05-13T17:25:59.368Z
updated_at: 2025-05-13T17:25:59.368Z
url: https://n8n.io/workflows/4025
scraped_at: 2026-05-02 08:04:51
metadata_generated_at: 2026-05-02 08:36:20
description:
  &gt; This n8n template builds Stacey, an AI assistant that runs inside Telegram. Stacey listens to your messages, understands what you want using AI, and intelligently routes commands to MCP-connected tools — like Gmail, Google Calendar, a blog writer, and more.
  &gt;
  &gt; For optimal performance, we recommend using OpenAI’s GPT-4o model. In this template, Google Gemini is used as a free alternative.

  💡 Who is this for?

  This workflow is designed for:

  AI tool creators and automation builders
  Entrepreneurs who want an intelligent Telegram assistant
  Support and scheduling teams who use Google tools
  Agencies that build & resell AI automations
  Users looking to automate everyday actions like emails, scheduling, blog writing, and contact lookups

  🧠 What this workflow does

  Listens to Telegram messages (text and voice)
  Transcribes audio using Whisper (optional)
  Uses Stacey, an AI agent powered by Gemini (or GPT-4o if you upgrade), to:

    Understand the user's intent
    Choose the correct tool using MCP logic
    Execute tasks using Gmail, Google Calendar, blog writer, and more
  Responds to the user naturally with confirmations and outputs

  ⚙️ Prerequisites

  Before using this workflow, make sure you have:

  A self-hosted or cloud-based n8n instance
  A Telegram Bot Token from @BotFather
  Google OAuth2 credentials** for:

    Gmail
    Google Calendar
  Optional: OpenAI or Whisper API key for voice transcription
  Optional: Tavily API key for live web search
  Gemini (Google AI) is preconfigured in the template but can be swapped

  🚀 Step-by-Step Setup

  ✅ Step 1: Add Required Credentials in n8n

  Go to Settings → Credentials and add:

  Telegram API**: Your bot token from BotFather
  Google OAuth2**:

    Gmail: Scope https://www.googleapis.com/auth/gmail.modify
    Calendar: Scope https://www.googleapis.com/auth/calendar
  Gemini / Palm API**: Used for the language model
  (Optional) OpenAI Whisper: For voice transcription
  (Optional) Tavily: For real-time internet searches

  ✅ Step 2: Import the Workflow

  Go to n8n
  Click Workflows → Import from File
  Upload ai_assistant.json
  Connect your saved credentials to the correct nodes:

     Telegram Trigger & Sender
     Gmail, Calendar, Tavily, Gemini, Whisper


  ✅ Step 2.5: Import the Content Creator Sub-Workflow

  The Content Creator is implemented as a modular sub-workflow and invoked through the Map Server as part of the MCP logic.

  To set it up:

  Go to Workflows → Import from File
  Upload content_creator_tool.json (provided in your files)
  Save it with a name like “Content Creator Tool”
  🔗 Integration with MCP:

  This tool is triggered via the MCP Map Server using an Execute Workflow node
  The AI agent chooses this tool when the user request involves writing blog posts, emails, product descriptions, etc.
  Make sure the tool ID or name in the Map Server matches what the AI agent uses in its logic
  You can customize this sub-workflow to:

  Adjust writing prompts (e.g., tone, format, target audience)
  Add branching for different content types (e.g., blog vs. email)
  Send outputs directly to Gmail, Google Docs, or Sheets
  ✅ Step 3: Set Up Your Telegram Bot

  Talk to @BotFather
  Use /newbot to create a bot and get your token
  Paste this token into:

     Telegram Trigger node (Telegram Trigger1)
     Telegram Send Message node (Response1)
  Make sure your bot’s privacy is set correctly (use /setprivacy)

  ✅ Step 4: Customize Your Assistant’s Personality

  Open the “AI Agent” node
  In the systemMessage field, you'll find a prompt that defines Stacey:

     Her role is to delegate user requests to the right MCP tool
     Includes examples, tone, rules, and logic
  You can customize Stacey’s:

     Name
     Behavior
     Supported tools

  ✅ Step 5: Define Your MCP Tools (if extending)

  This template includes:

  Send Email
  Reply to Email
  Get Emails
  Label Emails
  Create/Update/Delete Events
  Content Creator
  Search Web with Tavily
  Calculator

  To extend:

  Add a new tool node
  Link it to MCP Server Trigger
  Reference it in the prompt in AI Agent node

  ✅ Step 6: Test the Workflow

  Open Telegram and message your bot:

  “Send an email to John about the new budget”
  “Schedule a meeting Friday at 3 PM with Alex”
  “Write a blog post about solar energy”
  “What’s in my inbox?”
  “Translate this message” (if extended with translation tools)

  The bot will:

  Interpret the intent
  Ask for any missing data
  Trigger the right tool
  Send confirmation via Telegram

  ✨ Customization Ideas

  ✏️ Add Voice Transcription

  Enable the Download File and Transcribe nodes
  Requires OpenAI Whisper API key

  🧠 Upgrade to GPT-4o

  Replace the Gemini node with an OpenAI Chat node
  Connect GPT-4o for improved reasoning and language understanding

  🧩 Add More Tools

  Notion, Slack, Salesforce, Hubspot, WhatsApp, and more can be added
  Just route them via MCP and update the AI prompt

  🧪 Troubleshooting

  Telegram not responding?

  Ensure correct bot token and webhook connection
  Make sure the bot is not in privacy mode if needed

  Gmail actions not working?

  Double-check your OAuth scopes
  Ensure Gmail API is enabled in your Google Cloud project

  AI not responding or behaving poorly?

  Consider upgrading to OpenAI GPT-4o for better reasoning
  Revisit and refine your system prompt

  🧾 Summary

  Name: Stacey – AI Telegram Assistant
  Built with: n8n + Gemini + Google + MCP Logic
  Telegram acts as the front-end
  Gemini or GPT-4o powers intelligence
  MCP routes user intent to the right tool
  Fully extensible and no-code friendly

  🌟 Credits & License

  Created by David Olusola
  Free to use, modify, and resell with attribution.
  If this helped you, please rate the template or follow me on the n8n Creator Page.

nodes_used:
  ["@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolHttpRequest","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.set","n8n-nodes-base.telegram","@n8n/n8n-nodes-langchain.openAi","n8n-nodes-base.telegramTrigger","n8n-nodes-base.telegram","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.mcpClientTool","@n8n/n8n-nodes-langchain.mcpTrigger","n8n-nodes-base.googleCalendarTool","n8n-nodes-base.googleCalendarTool","n8n-nodes-base.googleCalendarTool","n8n-nodes-base.googleCalendarTool","n8n-nodes-base.googleCalendarTool","n8n-nodes-base.gmailTool","n8n-nodes-base.gmailTool","n8n-nodes-base.gmailTool","n8n-nodes-base.gmailTool","n8n-nodes-base.gmailTool","n8n-nodes-base.gmailTool","n8n-nodes-base.gmailTool","n8n-nodes-base.googleSheetsTool","n8n-nodes-base.googleSheetsTool","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","@n8n/n8n-nodes-langchain.memoryBufferWindow","n8n-nodes-base.code","n8n-nodes-base.switch","@n8n/n8n-nodes-langchain.toolCalculator"]

workflow_json_compressed:
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metadata_json:
  {"categories":["AI/ML","Communication","Marketing"],"complexity":"medium","use_cases":["build AI chatbot","create telegram bot","integrate MCP tools","connect LLM APIs","automate gmail tasks"],"estimated_setup_minutes":30,"required_services":["Telegram","Google Calendar","Gmail","Google Gemini","OpenAI"],"key_features":["MCP tool integration","Natural language routing","AI-powered command parsing","Multiple LLM support","Google ecosystem tools"],"target_audience":["developers","automation builders","community managers"]}


name: Generate and publish carousels for TikTok and Instagram with GPT-Image-1
author_name: Juan Carlos Cavero Gracia
author_username: carlosgracia
categories: []
created_at: 2025-05-13T23:37:52.592Z
updated_at: 2025-05-13T23:37:52.592Z
url: https://n8n.io/workflows/4028
scraped_at: 2026-05-02 08:04:50
metadata_generated_at: 2026-05-02 08:36:19
description:
  Description

  This n8n automation template provides an end-to-end solution for generating a series of themed images for Instagram and TikTok carousels using OpenAI's GPT Image (via the image generation API) and automatically publishing them to both platforms. It uses a sequence of prompts to create a narrative or themed carousel, generating each image based on the previous one, and then posts them with an AI-generated caption.

  Who Is This For?

  Social Media Managers:** Quickly create and schedule engaging image carousels for Instagram and TikTok.
  Content Creators:** Automate the visual content creation process for thematic posts or storytelling carousels.
  Digital Marketers:** Efficiently produce visual assets for campaigns that require sequential imagery.
  Small Businesses:** Generate unique promotional content for social media without needing advanced design skills.

  What Problem Does This Workflow Solve?

  Manually creating a series of related images for a carousel and then publishing them across multiple platforms can be repetitive and time-consuming. This workflow addresses these issues by:

  Automating Image Generation:** Uses OpenAI to generate a sequence of 5 images, where each new image is an evolution based on the previous one and a new prompt.
  Automating Caption Generation:** Leverages OpenAI (GPT) to create a suitable description/caption for the carousel based on the image prompts.
  Streamlining Multi-Platform Publishing:** Automatically uploads the generated image carousel and caption to both Instagram and TikTok.
  Reducing Manual Effort:** Significantly cuts down the time spent on designing individual images and manually uploading them.
  Ensuring Visual Cohesion:** The sequential image generation method (editing the previous image) helps maintain a consistent style or narrative across the carousel.

  How It Works

  Trigger: The workflow is initiated manually (can be adapted to a schedule or webhook).
  Define Prompts: Five distinct prompts are pre-set within the workflow to guide the generation of each image in the carousel.
  AI Caption Generation: OpenAI (GPT-4.1) generates a concise (≤ 90 characters for TikTok) description for the social media posts based on all five image prompts.
  Sequential AI Image Generation:
      Image 1: OpenAI's image generation API (specified as gpt-image-1) creates the first image based on prompt1.
      Image 2-5: For each subsequent image, the workflow uses the OpenAI image edits API. It takes the previously generated image and a new prompt (prompt2 for image 2, prompt3 for image 3, and so on) to create the next image in the sequence.
      Images are converted from base64 JSON to binary format.
  Content Aggregation: The five generated binary image files (named photo1 through photo5) are merged.
  Multi-Platform Distribution:
      The merged images and the AI-generated description are sent to api.upload-post.com for publishing as a carousel to Instagram.
      The same content is sent to api.upload-post.com for publishing as a carousel to TikTok, with an option to automatically add music.
      The TikTok description is truncated if it exceeds 90 characters.

  Setup

  Accounts & API Keys: You will need:
      An n8n instance.
      An OpenAI API key.
      A key for social media API upload-post.
  Configure Credentials:
      Add your OpenAI API key to the "OpenAI" credentials in n8n. This will be used by the "Generate Description for Tiktok and Instagram" node and the HTTP Request nodes calling the OpenAI image generation/edit APIs.
      In the "POST TO INSTAGRAM" and "POST TO TIKTOK" nodes, replace "Apikey add_api_key_here" with your actual upload-post.com API key.
      Update the user field in the "POST TO INSTAGRAM" and "POST TO TIKTOK" nodes if "upload_post" is not your user identifier for that service.
  Customize Prompts: Modify the five prompts (prompt1 to prompt5) in the "Set All Prompts" node to define the story or theme of your image carousel.
  Review Image Generation Parameters: In the "Set API Variables" node, you can adjust:
      size_of_image (e.g., "1024x1536" for vertical carousels).
      openai_image_model (ensure this matches a valid OpenAI model identifier for image generation/edits, like dall-e-2 or dall-e-3 if gpt-image-1 is a placeholder).
      response_format_image (should generally remain b64_json for this workflow).
  (Optional) TikTok Auto Music: The "POST TO TIKTOK" node has an auto_add_music parameter set to true. Change this to false if you prefer to add music manually or not at all.

  Requirements

  Accounts:** n8n, OpenAI, upload-post.com.
  API Keys & Credentials:** API Keys for OpenAI and https://upload-post.com.
  (Potentially) Paid Plans:** OpenAI and upload-post.com usage may incur costs depending on your volume and their respective pricing models.

  This template empowers you to automate the creation and distribution of visually consistent image carousels, saving time and enhancing your social media presence.

nodes_used:
  ["n8n-nodes-base.code","n8n-nodes-base.httpRequest","n8n-nodes-base.merge","n8n-nodes-base.manualTrigger","@n8n/n8n-nodes-langchain.openAi","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.httpRequest","n8n-nodes-base.splitOut","n8n-nodes-base.convertToFile","n8n-nodes-base.code","n8n-nodes-base.httpRequest","n8n-nodes-base.splitOut","n8n-nodes-base.convertToFile","n8n-nodes-base.code","n8n-nodes-base.httpRequest","n8n-nodes-base.splitOut","n8n-nodes-base.convertToFile","n8n-nodes-base.code","n8n-nodes-base.httpRequest","n8n-nodes-base.splitOut","n8n-nodes-base.convertToFile","n8n-nodes-base.code","n8n-nodes-base.httpRequest","n8n-nodes-base.splitOut","n8n-nodes-base.convertToFile","n8n-nodes-base.code","n8n-nodes-base.httpRequest"]

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metadata_json:
  {"categories":["Marketing","Social Media","AI/ML"],"complexity":"medium","use_cases":["create TikTok carousels","generate Instagram posts","schedule social media content","produce themed image series"],"estimated_setup_minutes":15,"required_services":["OpenAI","Instagram Basic Display","Facebook Graph API","TikTok API"],"key_features":["AIMediatedimage generation","sequentialprompting","multi-platformscheduling","automatedcaptioncreation","visualcontentworkflow"],"target_audience":["socialmedia managers","digitalmarketers","contentcreators"]}


name: Create & Approve POV Videos with AI, ElevenLabs & Multi-Posting (TikTok/IG/YT)
author_name: Immanuel
author_username: spectrabit
categories: []
created_at: 2025-05-14T00:06:42.535Z
updated_at: 2025-05-14T00:06:42.535Z
url: https://n8n.io/workflows/4029
scraped_at: 2026-05-02 08:04:49
metadata_generated_at: 2026-05-02 08:36:19
description:
  POV Video Creator: Automating TikTok-Style Instagram Video Automation, Approval, and Multi-Platform Posting Using AI, ElevenLabs, Google Sheets, and Social Media APIs

  Description

  What Problem Does This Solve? 🎥
  This workflow automates the creation, rendering, approval, and posting of TikTok-style POV (Point of View) videos to Instagram, with cross-posting to Facebook and YouTube. It eliminates manual video production, approval delays, and inconsistent posting schedules. It ensures high-quality content creation and distribution for social media managers and content creators

  Target audience: Social media managers, content creators, small to medium-sized businesses, and n8n users familiar with AI tools, Google Sheets, and social media APIs

  What Does It Do? 🌟
  Generates daily POV video ideas using OpenAI
  Creates images, videos, and audio with PIAPI.ai and ElevenLabs
  Renders final videos with Creatomate
  Manages approvals via email and Google Sheets
  Posts approved videos to Instagram, Facebook, and YouTube
  Tracks progress in a Google Sheet for transparency

  Key Features 
  AI-driven idea generation and script creation
  Automated media production with image, video, and audio synthesis
  Email-based approval system for quality control
  Cross-platform posting to Instagram, Facebook, and YouTube
  Real-time tracking in Google Sheets and Google Drive
  Error handling for rendering and posting failures

  Setup Instructions

  Prerequisites 
  n8n Instance**: Self-hosted or cloud n8n instance
  API Credentials**:
    OpenAI API: API key for idea generation, stored in n8n credentials
    PIAPI.ai API: API key for image and video generation, stored in n8n credentials
    ElevenLabs API: API key for audio generation, stored in n8n credentials
    Creatomate API: API key for video rendering, stored in n8n credentials
    Google Sheets/Drive API: OAuth2 credentials from Google Cloud Console with Sheets and Drive scopes
    Gmail API: OAuth2 credentials from Google Cloud Console with Gmail scope
    Instagram Graph API: User Access Token with instagram_content_publish permission from a Facebook App
    Facebook Graph API: Access Token from the same Facebook App
    YouTube API: OAuth2 credentials for YouTube uploads
  Google Sheet**: A sheet named "POV Videos" with a tab "Instagram" and columns: Timestamp, ID, Subject, Topic, Caption, POV_Status, Prompt, Publish_Status, Link, Final Video, Approval, row_number
  Creatomate Template**: A pre-configured template with video, audio, and text elements

  Installation Steps 
  Import the Workflow:
     Copy the workflow JSON from the “Template Code” section (to be provided)
     Import it into n8n via “Import from File” or “Import from URL”
  Configure Credentials:
     Add API credentials in n8n’s Credentials section for OpenAI, PIAPI.ai, ElevenLabs, Creatomate, Google Sheets/Drive, Gmail, Instagram Graph, Facebook Graph, and YouTube
     Assign credentials to respective nodes. For example:
       In "Text-to-Image", use PIAPI.ai credentials: {{ $credentials.PIAPI }}
       In "Render with Creatomate", use Creatomate credentials: {{ $credentials.Creatomate }}
       In "Send Approval Request", use Gmail credentials
  Set Up Nodes:
     Schedule Trigger: Configure to run daily
     Approval Email (Send Approval Request): Customize the HTML email template with approval/rejection links
     Post to Social Media Nodes (Instagram Container, Facebook Posts, Post YouTube): Configure with your Instagram Business Account ID, Facebook Page ID, and YouTube channel details
  Configure Google Sheet and Drive:
     Create "POV Videos" Google Sheet with "Instagram" tab and specified columns
     Share the sheet with your Google Sheets credential email
     Create "Audio" and "Video" folders in Google Drive, noting their IDs
  Test the Workflow:
     Run manually to verify idea generation, media creation, and posting
     Check email notifications, Google Sheet updates, and social media posts
  Schedule the Workflow:
     Enable "Schedule Trigger" and "Schedule Trigger1" for daily runs
     Enable "Get Latest Approved Video" to poll at 7 PM daily

  How It Works

  High-Level Steps 
  Generate Video Ideas: Creates daily POV video concepts with OpenAI
  Create Media: Produces images, videos, and audio using AI tools
  Render Video: Combines media into a final video with Creatomate
  Manage Approvals: Sends approval emails and processes decisions
  Post to Platforms: Publishes approved videos to Instagram, Facebook, and YouTube

  Detailed Descriptions
  Detailed node descriptions are available in the sticky notes within the workflow (to be provided). Below is a summary of key actions

  Node Names and Actions

  Video Idea Generation and Script Creation
  Schedule Trigger**: Initiates daily workflow
  Get Title**: Fetches pending video ideas from Google Sheet
  Generate Topics**: Uses OpenAI to create a new video idea
  Format Row**: Structures the idea into a Google Sheet row
  Insert new Prompt, Caption and Title/Topic**: Adds the idea to Google Sheet
  Generate Ideas**: Produces 3 POV sequences
  Generate Script**: Expands a sequence into a detailed script
  Set Topics**: Stores the script for media creation

  Media Creation
  Text-to-Image**: Generates an image with PIAPI.ai
  Get Image**: Retrieves the generated image
  Generate Video Prompt**: Creates a video prompt from the image
  Generate Video**: Produces a 5-second video with PIAPI.ai
  Access Videos**: Retrieves the video URL
  Store Video**: Updates Google Sheet with video URL
  Generate Sound Prompt**: Creates an audio prompt
  Text-to-Sound**: Generates a 20-second audio clip with ElevenLabs
  Store Sound**: Uploads audio to Google Drive
  Allow Access**: Sets audio file permissions

  Video Rendering
  Merge**: Combines script, video, and audio data
  List Elements**: Formats data for Creatomate
  Render with Creatomate**: Renders the final video
  Check Video Status**: Routes based on render success/failure

  Storage and Notification
  Google Drive**: Uploads the rendered video
  New Render Video Alert**: Sends success email
  Failed Render**: Sends failure email
  Render Video Link**: Updates Google Sheet with final video URL

  Approval Process
  Approval Email**: Sends approval request email
  Handle Approval/Rejection1**: Processes approval/rejection via webhook
  Video Update1**: Updates Google Sheet with approval status

  Social Media Posting
  Get Latest Approved Video**: Polls for approved videos
  Check Approval**: Routes based on approval status
  Instagram Container**: Creates Instagram media container
  Post to Instagram**: Publishes to Instagram
  Facebook Posts**: Posts to Facebook
  Download Video**: Downloads video for YouTube
  Post YouTube**: Uploads to YouTube
  Mark Rejected**: Updates status for rejected videos
  Update Google Sheet**: Updates publish status

  Customization Tips
  Expand Platforms**: Add nodes to post to other platforms 
  Modify Approval Email**: Update the Send Approval Request node to customize the HTML template
  Alternative Notifications**: Add nodes for Slack or Telegram alerts
  Adjust Video Duration**: Modify Generate Video node to change duration (default: 5 seconds)

nodes_used:
  ["n8n-nodes-base.scheduleTrigger","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.outputParserItemList","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequest","n8n-nodes-base.merge","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequest","n8n-nodes-base.gmail","n8n-nodes-base.googleDrive","@n8n/n8n-nodes-langchain.lmChatOpenRouter","n8n-nodes-base.wait","n8n-nodes-base.wait","n8n-nodes-base.stickyNote","n8n-nodes-base.googleSheets","n8n-nodes-base.httpRequest","n8n-nodes-base.set","n8n-nodes-base.httpRequest","n8n-nodes-base.limit","n8n-nodes-base.wait","n8n-nodes-base.code","n8n-nodes-base.stickyNote","n8n-nodes-base.googleDrive","n8n-nodes-base.httpRequest","n8n-nodes-base.gmail","n8n-nodes-base.gmail","n8n-nodes-base.googleSheets","n8n-nodes-base.stickyNote","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.googleSheets","@n8n/n8n-nodes-langchain.openAi","@n8n/n8n-nodes-langchain.openAi","n8n-nodes-base.code","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.webhook","n8n-nodes-base.googleSheets","n8n-nodes-base.if","n8n-nodes-base.googleSheets","n8n-nodes-base.googleSheets","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.googleSheetsTrigger","n8n-nodes-base.facebookGraphApi","n8n-nodes-base.facebookGraphApi","n8n-nodes-base.facebookGraphApi","n8n-nodes-base.httpRequest","n8n-nodes-base.youTube","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.wait","n8n-nodes-base.googleDrive","n8n-nodes-base.switch","@n8n/n8n-nodes-langchain.chainLlm","n8n-nodes-base.googleSheets","@n8n/n8n-nodes-langchain.openAi","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest"]

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metadata_json:
  {"categories":["Marketing","Content Creation","Social Media Management"],"complexity":"medium","use_cases":["automate POV video creation","integrate AI voice generation","manage video approval workflow","multi-platform content scheduling"],"estimated_setup_minutes":30,"required_services":["ElevenLabs","TikTok","Instagram","Facebook","YouTube","Google Sheets","Google Drive"],"key_features":["AI-powered video generation","built-in approval process","automated cross-posting","scheduled content delivery","text-to-speech integration"],"target_audience":["content creators","social media managers","marketing teams"]}


name: AI Newsletter Builder: Crawl Sites with Dumpling AI, Summarize with GPT-4o
author_name: Yang
author_username: yang
categories: []
created_at: 2025-05-14T01:17:44.194Z
updated_at: 2025-05-14T01:17:44.194Z
url: https://n8n.io/workflows/4030
scraped_at: 2026-05-02 08:04:49
metadata_generated_at: 2026-05-02 08:36:19
description:
  Who is this for?

  This workflow is built for newsletter writers, marketers, content creators, or anyone who curates and summarizes web articles. It’s especially helpful for virtual assistants and founders who need to quickly turn web content into digestible, branded newsletters using AI.

  What problem is this workflow solving?

  Manually reading, summarizing, and formatting multiple articles into a newsletter takes time and focus. This workflow automates the process using Dumpling AI for crawling, GPT-4o for summarization, and Gmail for delivery—so you can go from raw URLs to a polished email in minutes.

  What this workflow does

  Starts manually (can also be scheduled)
  Reads a list of article URLs from Google Sheets
  Sends URLs to Dumpling AI to crawl and extract content
  Splits each article into a single item for processing
  Uses a Code node to clean and structure article data
  Uses an Edit Fields node to merge articles into one JSON block
  GPT-4o summarizes and generates HTML content for the newsletter
  Sends the formatted newsletter via Gmail

  Setup

  Google Sheets
     Create a sheet with a column (A) for article URLs
     Update the Read URLs from Google Sheet node to use your Sheet ID and tab name
     Connect your Google account in the credentials

  Dumpling AI
     Sign up at https://app.dumplingai.com
     Create an agent for web crawling under /crawl
     Add your Dumpling API key in the HTTP headers of the Crawl Content with Dumpling AI node

  Split Node
     Breaks apart the array of articles from Dumpling AI so each article is processed individually

  Code Node
     Structures each article as JSON with title, url, and cleaned text content

  Edit Fields Node
     Gathers all structured articles back into a single JSON array to prepare for AI summarization

  OpenAI (GPT-4o)
     Processes the article list and returns a formatted subject line and HTML newsletter content

  Gmail
     Connect your Gmail account to send the AI-generated newsletter to your inbox or team
     Update the recipient field in the Send HTML Email via Gmail node

  How to customize this workflow to your needs

  Replace the manual trigger with a Schedule node to send newsletters weekly
  Modify the GPT-4o prompt to change tone (e.g., more professional, funny, casual)
  Add filtering logic to skip low-value articles
  Connect Slack, Airtable, or Notion for internal team usage
  Change Gmail to SendGrid or Outlook if preferred

  Final Notes

  This workflow uses:
  Dumpling AI** /crawl endpoint to extract article content
  Split, **Code, and Edit Fields nodes to format multi-article input
  GPT-4o** for summarization and HTML formatting
  Gmail** for delivery

  This setup eliminates manual steps and delivers fast, consistent newsletters powered by AI.

nodes_used:
  ["n8n-nodes-base.manualTrigger","n8n-nodes-base.googleSheets","n8n-nodes-base.httpRequest","n8n-nodes-base.splitOut","n8n-nodes-base.set","n8n-nodes-base.code","@n8n/n8n-nodes-langchain.openAi","n8n-nodes-base.gmail","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

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metadata_json:
  {"categories":["Marketing","Communication","Content Creation"],"complexity":"medium","use_cases":["summarize web content","curate newsletters","create AI newsletters"],"estimated_setup_minutes":5,"required_services":["Dumpling AI","GPT-4o","HTTP/Webhooks","Spreadsheets","Code executor"],"key_features":["automated web crawling","AI summarization","newsletter formatting"],"target_audience":["newsletter writers","marketers","content creators"]}


name: Cold Outreach Automation: Scrape Local Leads with Dumpling AI & Call via Vapi
author_name: Yang
author_username: yang
categories: []
created_at: 2025-05-14T01:34:16.860Z
updated_at: 2025-05-14T01:34:16.860Z
url: https://n8n.io/workflows/4031
scraped_at: 2026-05-02 08:04:49
metadata_generated_at: 2026-05-02 08:36:19
description:
  Who is this for?

  This template is for sales teams, agencies, or local service providers who want to quickly generate cold outreach lists and automatically call local businesses with a Vapi AI assistant. It’s perfect for automating cold calls from scraped local listings with no manual dialing or research.

  What problem is this workflow solving?

  Finding leads and initiating outreach calls can be time-consuming. This workflow automates the process: it scrapes business listings from Google Maps using Dumpling AI, extracts phone numbers, filters out incomplete data, formats the numbers, and uses Vapi to make outbound AI-powered calls. Every call is logged in Google Sheets for follow-up and tracking.

  What this workflow does

  Starts manually and pulls search queries (e.g., "plumbers in Austin") from Google Sheets.
  Sends each query to Dumpling AI’s Google Maps scraping endpoint.
  Splits the returned business data into individual leads.
  Extracts key info like business name, website, and phone number.
  Filters to only keep leads with valid phone numbers.
  Formats phone numbers for Vapi dialing (adds +1).
  Calls each business using Vapi AI.
  Logs each successful call in a Google Sheet.

  Setup

  Google Sheets Setup
     Create a sheet with business search queries in the first column (e.g., best+restaurants+in+Chicago)
     Make sure the tab name is set and authorized in your credentials.
     Connect your Google Sheets account in the Get Search Keywords from Google Sheets node.

  Dumpling AI Setup
     Go to dumplingai.com   
     Generate an API Key and connect it as a header token in the Scrape Google Map Businesses using Dumpling AI node

  Vapi Setup
     Sign into Vapi and create an assistant
     Get your assistantId and phoneNumberId
     Insert these into the JSON payload of the Initiate Vapi AI Call to Business node
     Add your Vapi API key to the credentials section

  Call Logging
     Create another tab in your sheet (e.g., “leads”) with these headers:
       company name
       phone number
       website
     This will be used in the Log Called Business Info to Sheet node

  How to customize this workflow to your needs

  Modify the business search terms in your Google Sheet to target specific industries or locations.
  Add filters to exclude certain businesses based on ratings, keywords, or location.
  Update your Vapi assistant script to match the type of outreach or pitch you’re using.
  Add additional integrations (e.g., CRM logging, Slack notifications, follow-up emails).
  Change the trigger to run on a schedule or webhook instead of manually.

  Nodes and Functions Breakdown

  Start Workflow Manually: Initiates the automation manually for testing or controlled runs.
  Get Search Keywords from Google Sheets: Reads search phrases from the spreadsheet.
  Scrape Google Map Businesses using Dumpling AI: Sends each search query to Dumpling AI and receives matching local business data.
  Split Each Business Result: Breaks the returned array of businesses into individual records for processing.
  Extract Business Name, Phone and website: Extracts title, phone, and website from each business record.
  Filter Valid Phone Numbers Only: Ensures only entries with a phone number move forward.
  Format Phone Number for Calling: Adds a +1 country code and strips non-numeric characters.
  Initiate Vapi AI Call to Business: Uses the business name and number to initiate a Vapi AI outbound call.
  Log Called Business Info to Sheet: Appends business details into a Google Sheet for tracking.

  Notes

  You must have valid API keys and authorized connections for Dumpling AI, Google Sheets, and Vapi.
  Make sure to handle API rate limits if you're running the workflow on large datasets.
  This workflow is optimized for US-based leads (+1 country code); adjust the formatting node if calling internationally.

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.manualTrigger","n8n-nodes-base.googleSheets","n8n-nodes-base.httpRequest","n8n-nodes-base.splitOut","n8n-nodes-base.set","n8n-nodes-base.filter","n8n-nodes-base.set","n8n-nodes-base.httpRequest","n8n-nodes-base.googleSheets","n8n-nodes-base.stickyNote"]

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metadata_json:
  {"categories":["Sales","Automation"],"complexity":"medium","use_cases":["local lead generation","automated outbound calling","service vendore outreach"],"estimated_setup_minutes":15,"required_services":["Dumpling AI","Vapi","Google Maps"],"key_features":["automated lead scraping","AI voice calling","local business listing extraction"],"target_audience":["sales teams","local service providers","agencies"]}


name: AI Competitor Review Analyzer with Dumpling AI + GPT-4o + Google Sheets
author_name: Yang
author_username: yang
categories: []
created_at: 2025-05-14T01:55:29.897Z
updated_at: 2025-05-14T01:55:29.897Z
url: https://n8n.io/workflows/4032
scraped_at: 2026-05-02 08:04:51
metadata_generated_at: 2026-05-02 08:36:20
description:
  Who is this for?

  This workflow is perfect for marketers, SEO specialists, product teams, and competitive analysts who want to monitor and summarize public reviews of their competitors. It’s especially helpful for small teams who want fast insights from Google reviews without spending hours manually reading and sorting them.

  What problem is this workflow solving?

  Manually going through competitor reviews is time-consuming and repetitive. You risk missing patterns or insights, and it’s hard to share summaries with your team quickly. This workflow automatically scrapes reviews from Google and generates a structured summary of pain points and positive feedback. That way, you can focus on strategy instead of sorting through dozens of reviews.

  What this workflow does

  This automation watches for new competitor entries in a Google Sheet, then:

  Uses Dumpling AI to scrape the latest Google reviews (up to 20) for each business.
  Splits and cleans the reviews for analysis.
  Sends them to GPT-4o, which summarizes the most common complaints and praises.
  Saves the structured result back to the same Google Sheet.

  You’ll instantly get an overview of what people are saying about any competitor.

  Setup

  Google Sheet Setup
     Create a Google Sheet with at least one column: Business
     Add names or search queries for the competitors you want to analyze
     Optional: Add columns for Summary of Reviews and Pain Points

  Connect Dumpling AI
     Sign up at Dumpling AI
     Create an agent using the get-google-reviews endpoint
     Copy your agent key
     Use it in the HTTP Request node in this workflow

  OpenAI Setup
     Use your API key with GPT-4o access
     The prompt is already structured to generate grouped summaries from reviews

  Run the Workflow
     Trigger it manually or schedule it
     Make sure your Google Sheets, OpenAI, and Dumpling AI connections are active

  How to customize this workflow to your needs

  You can expand the number of reviews retrieved by changing the Dumpling AI agent config
  Replace Google Sheets with Airtable if you want more robust data views
  Add more fields like star ratings or review dates in your agent for richer analysis
  Change the GPT prompt to highlight emotional tone, urgency, or feature mentions

  🧠 Node Details

  Google Sheets Trigger**: Watches for new competitor names
  HTTP Request (Dumpling AI)**: Scrapes 20 recent reviews from Google
  SplitOut Node**: Breaks review array into individual items
  Code Node**: Extracts and combines review text
  Edit Fields Node**: Structures the review content before GPT
  GPT-4o Node**: Analyzes and summarizes top pain points and praise
  Google Sheets Output**: Saves the summary back to the same sheet

  Dependencies

  Dumpling AI account and review scraping agent setup
  OpenAI API key with GPT-4o access
  Google Sheets OAuth2 credentials

nodes_used:
  ["n8n-nodes-base.googleSheetsTrigger","n8n-nodes-base.httpRequest","n8n-nodes-base.splitOut","n8n-nodes-base.aggregate","@n8n/n8n-nodes-langchain.openAi","n8n-nodes-base.googleSheets","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

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metadata_json:
  {"categories":["Marketing","AI/ML","Data Processing"],"complexity":"simple","use_cases":["monitor competitor reviews","summarize public feedback","annotate review insights","track competitive intelligence"],"estimated_setup_minutes":10,"required_services":["Dumpling AI","OpenAI / GPT-4o","Google Sheets","NoCode / Workflow Automation Platform"],"key_features":["AI-powered sentiment analysis","natural language query processing","automated benefit extraction","public review aggregation","fractional AI agent integration"],"target_audience":["marketers","SEO specialists","product managers"]}


name: AI-Powered Blog Post Promoter for Instagram, Facebook & X with GPT
author_name: LukaszB
author_username: lukaszb
categories: []
created_at: 2025-05-14T03:30:08.605Z
updated_at: 2025-05-14T03:30:08.605Z
url: https://n8n.io/workflows/4033
scraped_at: 2026-05-02 08:04:50
metadata_generated_at: 2026-05-02 08:36:20
description:
  AI Social Media Promoter – Automated Blog Sharing Workflow
  This workflow is built for bloggers, creators, and marketing teams who want to automatically promote new blog content across Instagram, Facebook, and X (Twitter). Its core purpose is to detect new blog posts from your RSS feed and instantly create platform-specific social media posts — complete with AI-generated captions and visuals — to drive traffic from social media back to your blog. Everything runs on autopilot: from detecting a new article to posting eye-catching content on each platform, while logging actions to Google Sheets and sending post previews by email. The result is a consistent and professional online presence with zero manual effort.

  How it works
  Once a new blog post appears in your RSS feed, the workflow kicks in. It checks Google Sheets to ensure the post hasn’t already been published. Then it calls GPT-4 to generate unique captions for Instagram, Facebook, and X, based on the post content and your brand’s tone. Simultaneously, OpenAI's GPT-Image generates a custom visual in the right format (square, portrait, or landscape). The workflow then publishes the complete posts using the Meta Graph API (for IG/FB) and X API (Twitter). All actions are logged in a Google Sheet, and a formatted email summary with images is sent to your inbox for review.

  How to set up
  To get started, connect the required APIs: OpenAI (for text and images), ImgBB or Cloudinary (for image hosting), Meta (Instagram/Facebook), X (Twitter), Google Sheets, and Gmail. Replace placeholder values in HTTP request nodes — such as your RSS URL, API keys, or spreadsheet ID. You can personalize the prompt content with your blog name, tone of voice, and call-to-action. Once connected, the system is fully automated. You can run it manually, or schedule it to check your blog daily with a Schedule Trigger node.

nodes_used:
  ["@n8n/n8n-nodes-langchain.outputParserStructured","n8n-nodes-base.rssFeedReadTrigger","n8n-nodes-base.set","n8n-nodes-base.if","n8n-nodes-base.code","n8n-nodes-base.aggregate","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.facebookGraphApi","n8n-nodes-base.facebookGraphApi","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.facebookGraphApi","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.set","n8n-nodes-base.merge","n8n-nodes-base.merge","n8n-nodes-base.set","n8n-nodes-base.twitter","n8n-nodes-base.stickyNote","n8n-nodes-base.merge","n8n-nodes-base.gmail","n8n-nodes-base.stickyNote","n8n-nodes-base.aggregate","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.googleSheets","n8n-nodes-base.googleSheets","n8n-nodes-base.googleSheets","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  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

metadata_json:
  {"categories":["Marketing","AI/ML"],"complexity":"medium","use_cases":["auto-share blog posts to social media","generate social media captions","create social images from content","monetize blog traffic","manage cross-platform presence"],"estimated_setup_minutes":30,"required_services":["Instagram Graph API","Facebook Graph API","Twitter API","RSS Feed","OpenAI API","DALL-E API","Spreadsheets"],"key_features":["RSS feed monitoring","AI-powered caption generation","AI visual creation","Multi-social platform scheduling","N8N app node integration options"],"target_audience":["bloggers","social media marketers","content creators"]}


name: Automated Daily Backup of n8n Workflows to GitLab Repositories
author_name: Akhil Varma Gadiraju
author_username: akhilv7
categories: []
created_at: 2025-05-14T06:06:07.562Z
updated_at: 2025-05-14T06:06:07.562Z
url: https://n8n.io/workflows/4035
scraped_at: 2026-05-02 08:04:50
metadata_generated_at: 2026-05-02 08:36:20
description:
  n8n Workflow: Sync Workflows with GitLab

  How It Works

  This workflow ensures that your self-hosted n8n workflows are version-controlled in a GitLab repository. It compares each current workflow from n8n with its stored counterpart in GitLab. If any differences are detected, the GitLab file is updated with the latest version.

  Core Logic:
  Retrieve Workflows – Fetch all workflows from the n8n REST API.

  Compare with GitLab – For each workflow, fetch the corresponding file from GitLab and compare the JSON.

  Update if Changed – If differences exist, commit the updated workflow to GitLab using its API.

  Setup

  Before using the workflow, ensure the following:

  Prerequisites:
  n8n**: Self-hosted instance with access to the /rest/workflows API.

  GitLab**: A repository where workflows will be stored, and a Personal Access Token (PAT) with api and write_repository permissions.

  n8n Nodes Required**:
    HTTP Request (to call n8n and GitLab APIs)
    Code or Function nodes (for diffing and formatting)
    Looping (SplitInBatches or similar)

  Configuration:
  Set environment variables or workflow credentials for:
    GITLAB_TOKEN
    GITLAB_REPO
    GITLAB_BRANCH (e.g., main)
    GITLAB_FILE_PATH_PREFIX (e.g., n8n-workflows/)

  How to Use

  Import the Workflow into your n8n instance.

  Configure GitLab API Credentials:
     Set the GitLab PAT as a header in the HTTP

  Request node:  
       Private-Token: {{ $env.GITLAB_TOKEN }}

  Map Workflows to GitLab Paths:
     Use the workflow name or ID to create the file path. Example:  
       n8n-workflows/workflow-name.json

  Trigger the Workflow:
     Can be manually triggered, or scheduled to run at intervals (e.g., daily).
     
  Review Commits in GitLab:
     Each updated workflow will be committed with a message like:  
       "Update workflow: Sample Workflow"

  Disclaimer

  This workflow does not handle merge conflicts or manual edits made directly in GitLab. Always ensure proper coordination if multiple sources are modifying workflows.
  Only structural changes are tracked. Non-functional metadata (like timestamps or IDs) may trigger false positives unless filtered.
  Use at your own risk. Test in a safe environment before applying to production workflows.

nodes_used:
  ["n8n-nodes-base.set","n8n-nodes-base.noOp","n8n-nodes-base.noOp","n8n-nodes-base.splitInBatches","n8n-nodes-base.gitlab","n8n-nodes-base.code","n8n-nodes-base.set","n8n-nodes-base.noOp","n8n-nodes-base.gitlab","n8n-nodes-base.extractFromFile","n8n-nodes-base.switch","n8n-nodes-base.gitlab","n8n-nodes-base.noOp","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.n8n","n8n-nodes-base.set","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.gitlab"]

workflow_json_compressed:
  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

metadata_json:
  {"categories":["DevOps"],"complexity":"medium","use_cases":["Automate workflow backups","Version control integration","Compare file changes","Sync n8n assets","Schedule repository updates"],"estimated_setup_minutes":15,"required_services":["GitLab"],"key_features":["API-driven workflow retrieval","Automated version comparison","Scheduled daily execution","Batch processing support","Direct repository synchronization"],"target_audience":["devops engineers","workflow administrators"]}


name: Claude 3.7 Sonnet AI Chatbot Agent with Anthropic Web Search and Think Functions
author_name: Davide Boizza
author_username: n3witalia
categories: []
created_at: 2025-05-14T09:17:36.639Z
updated_at: 2025-05-14T09:17:36.639Z
url: https://n8n.io/workflows/4036
scraped_at: 2026-05-02 08:04:49
metadata_generated_at: 2026-05-02 08:36:19
description:
  This workflow builds a conversational AI chatbot agent using Claude 3.7 Sonnet model with the new . It enhances standard LLM capabilities with Anthropic’s features: Web Search and Think:

  Real-time web search**, to answer up-to-date factual queries.
  A “Think” function, to support internal reasoning and memory-like behavior by Anthropic.
  A memory buffer, allowing the agent to maintain conversation history.
  A system prompt defining clear ethical, functional, and formatting rules for interaction.

  When a user sends a message (trigger), the chatbot evaluates the query, optionally performs a web search if needed, processes the result using Claude, and responds accordingly.

  ✅ Advantages

  🧠 Enhanced Reasoning Abilities**
    The Think tool allows the agent to simulate deep thought processes or contextual memory storage, improving conversational intelligence.

  🌐 Real-Time Knowledge via Web Search**
    The integrated web_search tool enables the agent to fetch the latest information from the internet, making it ideal for dynamic or news-driven use cases.

  🧾 Contextual Responses with Memory Buffer**
    The inclusion of a memory buffer allows the agent to maintain state across messages, improving dialogue flow and continuity.

  🛡️ Built-in Ethical Guidelines**
    The system prompt enforces privacy, factual integrity, neutrality, and ethical response generation, making the agent safe for public or enterprise use.

  How It Works

  Chat Trigger: The workflow begins when a chat message is received via a webhook. This triggers the AI Agent to process the user's query.  
  AI Agent Processing: The AI Agent analyzes the query to determine if it requires information from the website or external sources. It follows a structured approach:  
     For website-related queries, it uses the provided context.  
     For external information, it employs the web_search tool to fetch up-to-date data from the internet.  
     The Think tool is used for internal reasoning or caching thoughts without altering data.  
  Language Model: The Anthropic Chat Model (Claude 3.7 Sonnet) generates responses based on the analyzed query, incorporating website context or web search results.  
  Memory: A simple memory buffer retains context from previous interactions to maintain continuity in conversations.  
  Output: The final response is delivered to the user, excluding internal processes like web searches or reasoning steps.  

  Set Up Steps

  Configure Nodes:  
     Chat Trigger: Set up the webhook to receive user messages.  
     AI Agent: Define the system message and rules for handling queries.  
     Anthropic Chat Model: Select the Claude 3.7 Sonnet model and configure parameters like maxTokensToSample.  
     Memory: Initialize the memory buffer to store conversation context.  
     Tools:  
       web_search: Configure the HTTP request to the Anthropic API for web searches, including headers and authentication.  
       Think: Set up the tool for internal reasoning.  

  Connect Nodes:  
     Link the Chat Trigger to the AI Agent.  
     Connect the Anthropic Chat Model, Memory, and Tools (web_search and Think) to the AI Agent.  

  Credentials:  
     Ensure the Anthropic API credentials are correctly configured for both the chat model and the web_search tool.  

  Need help customizing?  
  Contact me for consulting and support or add me on Linkedin. 

nodes_used:
  ["@n8n/n8n-nodes-langchain.chatTrigger","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatAnthropic","@n8n/n8n-nodes-langchain.memoryBufferWindow","n8n-nodes-base.httpRequestTool","@n8n/n8n-nodes-langchain.toolThink","n8n-nodes-base.stickyNote"]

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metadata_json:
  {"categories":["AI/ML","Communication"],"complexity":"medium","use_cases":["build conversational AI agents","integrate web search capabilities","implement reasoning processes","maintain conversation history","handle factual queries"],"estimated_setup_minutes":30,"required_services":["Anthropic","n8n"],"key_features":["real-time web search integration","chain-of-thought reasoning","conversation memory management","customizable system prompts","tool calling capabilities"],"target_audience":["AI developers","business automation engineers"]}


name: Manage WhatsApp Chats Centrally on Slack
author_name: Usman Liaqat
author_username: usmanliaqat
categories: []
created_at: 2025-05-14T10:27:11.807Z
updated_at: 2025-05-14T10:27:11.807Z
url: https://n8n.io/workflows/4037
scraped_at: 2026-05-02 08:04:50
metadata_generated_at: 2026-05-02 08:36:20
description:
  This workflow enables seamless, bidirectional communication between WhatsApp and Slack using n8n. It automates the reception, processing, and forwarding of messages (text, media, and documents) between users on WhatsApp and private Slack channels.

  Key Features & Flow:

  1. WhatsApp to Slack Flow
  Trigger: The workflow starts with a WhatsApp Trigger node that listens for new incoming messages via a webhook.
  Channel Handling: It checks if a Slack channel with the WhatsApp sender’s number exists
  If not, it creates a private Slack channel with the sender's number as the name.
  Message Type Routing: A Switch Node (Message Type) inspects the message type (text, image, audio, document).
  Based on type: Text: Sends the message directly to Slack.
  Image/Audio/Document: Retrieves media URL via WhatsApp API → downloads the media → uploads it to the appropriate Slack channel.

  2. Slack to WhatsApp Flow
  Trigger: A Slack Trigger listens for new messages or file uploads in Slack.
  Message Type Routing: A second Switch Node (Checking Message Type) checks if the message is text or media.
  Routing Logic: Text Message: Extracts and forwards it to the WhatsApp contact (identified by the Slack channel name).
  Media/File Message: Retrieves media file URL from Slack → downloads it → sends it as a document via WhatsApp API.

  Key Integrations: 
  WhatsApp Cloud API: For receiving messages, downloading media, and sending messages.
  Slack API: For creating/getting channels, posting messages, and uploading files.
  HTTP Request Node: Used to securely download media from Slack and WhatsApp servers with proper authentication.

  Automation Use Case:
  This workflow is ideal for businesses that handle customer support or conversations over WhatsApp and wish to log, respond, and collaborate using Slack as their internal communication tool.

nodes_used:
  ["n8n-nodes-base.whatsAppTrigger","n8n-nodes-base.slack","n8n-nodes-base.slackTrigger","n8n-nodes-base.switch","n8n-nodes-base.whatsApp","n8n-nodes-base.whatsApp","n8n-nodes-base.whatsApp","n8n-nodes-base.slack","n8n-nodes-base.slack","n8n-nodes-base.filter","n8n-nodes-base.slack","n8n-nodes-base.httpRequest","n8n-nodes-base.slack","n8n-nodes-base.switch","n8n-nodes-base.whatsApp","n8n-nodes-base.slack","n8n-nodes-base.httpRequest","n8n-nodes-base.whatsApp","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

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metadata_json:
  {"categories":["Communication","Customer Support"],"complexity":"medium","use_cases":["forward WhatsApp messages to Slack","centralize team communication","sync media and documents between platforms"],"estimated_setup_minutes":30,"required_services":["Twilio","Slack"],"key_features":["bidirectional messaging","media and document forwarding","channel mapping","webhook triggers"],"target_audience":["customer support agents","team leads","operations managers"]}


name: Automate Sprint Planning with OpenAI, Google Calendar, and Gmail for Agile Teams
author_name: Willemijn
author_username: willemijn
categories: []
created_at: 2025-05-14T10:36:56.830Z
updated_at: 2025-05-14T10:36:56.830Z
url: https://n8n.io/workflows/4038
scraped_at: 2026-05-02 08:04:50
metadata_generated_at: 2026-05-02 08:36:20
description:
  👤 Who is this for?
  This workflow is designed for Scrum Masters and Agile Coaches who prepare and coordinate Sprint Planning sessions, using Google Calendar, Google Sheets, and OpenAI.

  🧩 What problem is this workflow solving?
  It solves the manual and time-consuming task of collecting, validating, and preparing backlog items for sprint planning—especially when coordinating with distributed teams or large product backlogs.

  ⚙️ What this workflow does
  Every week, the workflow:

  Detects if a Sprint Planning event is coming up.  
  Retrieves relevant backlog items marked as “Ready for Sprint Planning” or “Active in Sprint.”  
  Checks each user story against the Definition of Ready (DoR) using AI.  
  Adds AI-generated feedback per story in the backlog.  
  Drafts a personalized preparation email for the team and sends it after Scrum Master approval.  
  Optionally, generates Sprint Goal suggestions for the Product Owner.

  🚀 Setup
  Connect your Google Calendar, Sheets, and Gmail accounts.  
  Then configure variables like event names, sheet names, and email addresses in the “Start Here” node.

  🛠️ How to customize this workflow to your needs
  Swap Google Sheets with Jira or another tool.  
  Adjust status filters and column mappings.  
  Tweak AI prompts for tone, language, or preferred practices.  
  Change email logic for different approval flows.

  🔥 Unique Selling Points (USPs)
  Validated** by a Scrum Master with 10+ years of experience
  AI-driven** backlog validation and email drafting.  
  Weekly automation** with human approval loops.  
  Clear, structured output** aligned with agile best practices.  
  Fully customizable** for any Scrum environment.

nodes_used:
  ["n8n-nodes-base.manualTrigger","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.noOp","n8n-nodes-base.googleCalendar","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.googleSheets","n8n-nodes-base.splitInBatches","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.noOp","n8n-nodes-base.googleDrive","n8n-nodes-base.googleSheets","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.stickyNote","n8n-nodes-base.aggregate","n8n-nodes-base.merge","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.aggregate","n8n-nodes-base.stickyNote","n8n-nodes-base.errorTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.gmail","n8n-nodes-base.gmail","n8n-nodes-base.gmail","n8n-nodes-base.gmail","n8n-nodes-base.if","n8n-nodes-base.set","n8n-nodes-base.googleDrive","n8n-nodes-base.gmail","n8n-nodes-base.filter","n8n-nodes-base.googleSheets","n8n-nodes-base.googleSheets","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.aggregate","n8n-nodes-base.code","n8n-nodes-base.gmail","n8n-nodes-base.splitOut","n8n-nodes-base.merge","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.filter","n8n-nodes-base.merge","n8n-nodes-base.merge","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.gmail","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.wait"]

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metadata_json:
  {"categories":["DevOps","Communication"],"complexity":"complex","use_cases":["Automate sprint planning","Collect backlog items","Schedule agile sessions","Generate sprint summaries","Manage distributed teams"],"estimated_setup_minutes":60,"required_services":["OpenAI API","Google Calendar","Google Gmail","Google Sheets","Google Drive","n8n"],"key_features":["AI-driven backlog refinement","Automated sprint duration calculation","Calendar integration","Email notification system","Backlog item aggregation"],"target_audience":["Scrum Masters","Agile Coaches","Project Managers"]}


name: Download Media Files from Slack Messages
author_name: Usman Liaqat
author_username: usmanliaqat
categories: []
created_at: 2025-05-14T10:37:51.142Z
updated_at: 2025-05-14T10:37:51.142Z
url: https://n8n.io/workflows/4039
scraped_at: 2026-05-02 08:04:50
metadata_generated_at: 2026-05-02 08:36:20
description:
  Description:
  This n8n workflow helps you capture Slack messages via a webhook and download attached media files (like images, documents, or videos) directly from those messages.

  How it works:
  Slack Trigger (Webhook) – Listens for new messages in a Slack channel where the app is added.
  HTTP Request – Uses the file's private download URL to retrieve the media securely.

  Use cases:
  Download files shared by team members in a Slack channel.
  Capture and process media from specific project or support channels.
  Prepare media for later processing, archiving, or review.

  Requirements:
  Slack app with appropriate permissions (files:read, channels:history, etc.).
  Slack webhook set up to listen to channel messages.
  - Authenticated HTTP request to handle private Slack file URLs.

  This template is ideal for users who want full control over file handling triggered by real-time Slack messages.

nodes_used:
  ["n8n-nodes-base.slackTrigger","n8n-nodes-base.httpRequest","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

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metadata_json:
  {"categories":["Communication","Data Processing"],"complexity":"medium","use_cases":["download files from slack messages","capture and process media from channels","retrieve attached documents and videos"],"estimated_setup_minutes":15,"required_services":["Slack"],"key_features":["Slack webhook trigger","secure private URL retrieval","file download automation","media processing workflow"],"target_audience":["developers","ops engineers","automation specialists"]}


name: Build a Pipedrive MCP Server with Google Gemini AI
author_name: Aitor | 1Node
author_username: aitoralonso
categories: []
created_at: 2025-05-14T12:09:40.318Z
updated_at: 2025-05-14T12:09:40.318Z
url: https://n8n.io/workflows/4040
scraped_at: 2026-05-02 08:04:50
metadata_generated_at: 2026-05-02 08:36:20
description:
  This n8n workflow leverages the power of AI and automation to streamline Pipedrive's CRM operations using natural language commands. It allows you to interact with your Deals, Leads, Persons, and Organizations simply by sending a message.

  How it Works
  The workflow initiates the process by sending the incoming message to an AI Agent. The AI Agent is powered by Google Gemini Chat Model and utilizing n8n's Simple Memory to maintain context, interprets the natural language command. Based on the interpreted command, the AI Agent instructs the MCP Client node to perform specific actions. The MCP Client then interacts with various nodes from Pipedrive designed to manage Deals, Leads, Persons, and Organizations within your CRM. These nodes can perform actions like creating, getting, updating, or searching for data in each category. Finally, a Gmail node sends a summary  compiling the actions executed.

  Set Up Steps
  Set up your MCP Client:** Paste the MCP URL from your MCP Trigger node into the MCP Client node.
  Configure the AI Agent:** Connect your Google Gemini Chat Model credentials or your desired LLM.
  Configure Pipedrive:** The individual nodes for Deals, Leads, Persons, and Organizations will need to be connected to your specific CRM. Add your Oath credentials for Pipedrive by creating a private app.
  Configuring each specific node** (Create Deal, Get Lead, Update Person, Search Organization, etc.) to perform the desired action.
  Configure Send Summary:** Set up the Gmail node to send the summary email.

  Benefits
  Significant Time Saving:** Automates data entry, retrieval, and updates in your CRM, freeing up valuable time for sales teams and managers.
  Increased Efficiency:** Perform multiple CRM actions with a single natural language command.
  Simplified CRM Interaction:** Interact with your CRM using natural language instead of navigating complex interfaces.
  Reduced Errors:** Automation minimizes manual data entry errors.

  Suggested Enhancements
  Integrate More CRM Operations:** Add nodes for additional CRM functionalities like logging activities, managing tasks, or working with other modules and tools.
  Connect to Other Tools:** Integrate with other sales or marketing tools to create a more comprehensive workflow.
  Advanced AI Capabilities:** Explore fine-tuning the AI model for better understanding of specific industry jargon or complex requests. Should you add more nodes and tools, you might want to insert a specific prompt to the AI agent to give more context about the tools and actions to perform.
  User Management and Permissions:** Customize the private app's permissions on your Pipedrive account to limit access.
  Error Handling and Notifications:** Add more robust error handling and notification systems to be alerted if a workflow run fails.

  Need help?
  Feel free to contact us at 1 Node.
  Get instant access to a library of free resources we created.

nodes_used:
  ["n8n-nodes-base.telegramTrigger","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.memoryBufferWindow","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","@n8n/n8n-nodes-langchain.mcpClientTool","@n8n/n8n-nodes-langchain.mcpTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.pipedriveTool","n8n-nodes-base.pipedriveTool","n8n-nodes-base.pipedriveTool","n8n-nodes-base.pipedriveTool","n8n-nodes-base.pipedriveTool","n8n-nodes-base.pipedriveTool","n8n-nodes-base.pipedriveTool","n8n-nodes-base.pipedriveTool","n8n-nodes-base.pipedriveTool","n8n-nodes-base.pipedriveTool","n8n-nodes-base.pipedriveTool","n8n-nodes-base.pipedriveTool","n8n-nodes-base.pipedriveTool","n8n-nodes-base.pipedriveTool","n8n-nodes-base.pipedriveTool","n8n-nodes-base.pipedriveTool","n8n-nodes-base.pipedriveTool","n8n-nodes-base.pipedriveTool","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.gmail"]

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metadata_json:
  {"categories":["AI/ML","CRM Management"],"complexity":"medium","use_cases":["natural language CRM queries","AI-driven deal management","voice commands for sales workflows"],"estimated_setup_minutes":30,"required_services":["Google Gemini","Pipedrive","Telegram (optional)"],"key_features":["natural language processing","context-aware memory","MCP server integration","automated CRM actions"],"target_audience":["sales managers","developers","CRM administrators"]}


name: Adaptive RAG with Google Gemini & Qdrant: Context-Aware Query Answering
author_name: Nisa
author_username: nisacayir
categories: []
created_at: 2025-05-14T15:10:47.350Z
updated_at: 2025-05-14T15:10:47.350Z
url: https://n8n.io/workflows/4043
scraped_at: 2026-05-02 08:04:49
metadata_generated_at: 2026-05-02 08:36:19
description:
  Description
  This workflow automatically classifies user queries and retrieves the most relevant information based on the query type. 🌟 It uses adaptive strategies like;
     Factual, Analytical, Opinion, and Contextual to deliver more precise and meaningful responses by leveraging n8n's flexibility. Integrated with Qdrant vector store and Google Gemini, it processes each query faster and more effectively. 🚀

  How It Works?
  Query Reception: A user query is triggered (e.g., through a chatbot interface). 💬

  Classification: The query is classified into one of four categories:

  Factual: Queries seeking verifiable information.

  Analytical: Queries that require in-depth analysis or explanation.

  Opinion: Queries looking for different perspectives or subjective viewpoints.

  Contextual: Queries specific to the user or certain contextual conditions.

  Adaptive Strategy Application: Based on classification, the query is restructured using the relevant strategy for better results.

  Response Generation**: The most relevant documents and context are used to generate a tailored response. 🎯

  Set Up Steps

  Estimated Time: ⏳ 10-15 minutes
  Prerequisites: You need an n8n account and a Qdrant vector store connection.
  Steps:

  Import the n8n workflow: Load the workflow into your n8n instance.

  Connect Google Gemini and Qdrant: Link these tools for query processing and data retrieval.

  Connect the Trigger Interface: Integrate with a chatbot or API to trigger the workflow.

  Customize: Adjust settings based on the query types you want to handle and the output format. 🔧

  For more detailed instructions, please check the sticky notes inside the workflow. 📌

nodes_used:
  ["@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.switch","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.chatTrigger","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","@n8n/n8n-nodes-langchain.memoryBufferWindow","@n8n/n8n-nodes-langchain.memoryBufferWindow","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","@n8n/n8n-nodes-langchain.memoryBufferWindow","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","@n8n/n8n-nodes-langchain.memoryBufferWindow","@n8n/n8n-nodes-langchain.embeddingsGoogleGemini","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.summarize","@n8n/n8n-nodes-langchain.vectorStoreQdrant","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.memoryBufferWindow","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.respondToWebhook","n8n-nodes-base.stickyNote","n8n-nodes-base.executeWorkflowTrigger","n8n-nodes-base.set","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 9828 characters]

metadata_json:
  {"categories":["AI/ML","Data Processing","Communication"],"complexity":"medium","use_cases":["classify user queries","retrieve relevant information","generate adaptive responses","enable context-aware chatbots","implement RAG systems"],"estimated_setup_minutes":15,"required_services":["Google Gemini","Qdrant","n8n"],"key_features":["Query classification","Vector store integration","Context-aware responses","Adaptive RAG strategies","Automatic query analysis"],"target_audience":["developers","AI engineers","system architects"]}


name: AI Chatbot Call Center: Telegram Call In (Production-Ready, Part 1a)
author_name: ChatPayLabs
author_username: chatpaylabs
categories: []
created_at: 2025-05-14T15:22:25.899Z
updated_at: 2025-05-14T15:22:25.899Z
url: https://n8n.io/workflows/4044
scraped_at: 2026-05-02 08:04:51
metadata_generated_at: 2026-05-02 08:36:20
description:
  Workflow Name: 🤙 Telegram Call In

  Template was created in n8n v1.90.2

  Skill Level: High

  Categories: n8n, Chatbot

  Stacks

  Chat Trigger node
  Telegram Trigger node
  Redis node
  Postgres node
  Execute Sub-workflow
  If node, Code node, Edit Fields (Set), Extract From File

  Prerequisite

  Community nodes: n8n-nodes-google-speech
  Sub-workflow: Demo Call Back
  Sub-workflow: Demo Call Center

  Production Features

  Scaling Design* for n8n *Queue mode** in production environment
  Optional Member Data from external Database with Caching Mechanism.
  Optional Voice Message to Text Message via Google STT API with Multi-Languages support.
  Testing Flow** with or without dependance on other workflow.
  Error Management**

  What this workflow does?

  This is a n8n Telegram Call In Workflow. It will wait for message from Telegram bot and sent to the Call Center to process.

  How it works

  The Telegram Trigger node will wait for the message from the Telegram bot.
  When message is received, it will first check for the matching Member from the PostgreSQL database.
  Then determine if it is a Text message or Voice message.
  For voice message, use the Google Speech to Text API to transcript it into text.
  Finally, pass the text to the next flow, i.e. the Call Center.

  Set up instructions

  n8n-nodes-google-speech

  Pull and Set up the required SQL from our Github repository.
  Go User &gt; Settings &gt; Community nodes, install n8n-nodes-google-speech node
      Follow https://www.npmjs.com/package/n8n-nodes-google-speech
      Setup the Google STT node
  Create you Telegram credentials, refer to n8n integration documentation for more information.
  Select your Credentials in Telegram Trigger
  Create you Redis credentials, refer to n8n integration documentation for more information.
  Select your Credentials in Member Cache and Save Member Cache.
  Create you Postgres credentials, refer to n8n integration documentation for more information.
  Select your Credentials in Load Member Data.
  FOR TEST ONLY. Enable the Telegram Test Output for testing from the Test Input.
  Remember to activate this workflow for incoming message.

  How to adjust it to your needs

  By default, this template will use the sys_member table for member information, you could change it for your own design.
  The demo implementation does not include failed member loading situation, you should implement based on your needs, e.g. if is_active is not true, do…
  You can replace the sub-workflow Demo Call Back and Demo Call Center to another flow as needs.

nodes_used:
  ["n8n-nodes-base.telegramTrigger","@n8n/n8n-nodes-langchain.chatTrigger","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.switch","n8n-nodes-base.telegram","n8n-nodes-base.extractFromFile","n8n-nodes-google-speech.googleSpeech","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.stickyNote","n8n-nodes-base.if","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.if","n8n-nodes-base.code","n8n-nodes-base.stickyNote","n8n-nodes-base.redis","n8n-nodes-base.if","n8n-nodes-base.postgres","n8n-nodes-base.redis","n8n-nodes-base.set","n8n-nodes-base.switch","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.if","n8n-nodes-base.set","n8n-nodes-base.stickyNote","n8n-nodes-base.executeWorkflow","n8n-nodes-base.executeWorkflow","n8n-nodes-base.telegram"]

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metadata_json:
  {"categories":["Communication","AI/ML","Enterprise Tools"],"complexity":"complex","use_cases":["Handle voice calls via Telegram","Integrate speech recognition","Deploy production-ready callbot"],"estimated_setup_minutes":480,"required_services":["Telegram","Google Speech APIs","PostgreSQL","Redis"],"key_features":["Voice-to-text integration","Call center automation","Production scaling with queue mode","Customizable call flows"],"target_audience":["call center managers","systems architects","telecom engineers"]}


name: AI Chatbot Call Center: Demo Call Center (Production-Ready, Part 2)
author_name: ChatPayLabs
author_username: chatpaylabs
categories: []
created_at: 2025-05-14T15:24:57.362Z
updated_at: 2025-05-14T15:24:57.362Z
url: https://n8n.io/workflows/4045
scraped_at: 2026-05-02 08:04:50
metadata_generated_at: 2026-05-02 08:36:55
description:
  Workflow Name: ☎️ Demo Call Center

  Template was created in n8n v1.90.2

  Skill Level: High

  Categories: n8n, Chatbot

  Stacks

  Execute Sub-workflow Trigger node
  Chat Trigger node
  Redis node
  Postgres node
  AI Agent node
  If node, Switch node, Code node, Edit Fields (Set)

  Prerequisite

  Execute Sub-workflow Trigger: Telegram Call In Workflow (or your own node)
  Sub-workflow: Taxi Service (or your own node)
  Sub-workflow: Taxi Booking Worker (or your own node)
  Sub-workflow: Demo Call Back (or your own node)

  Production Features

  Scaling Design* for n8n *Queue mode** in production environment
  Optional Rate Limit design to prevent overused
  Optional Long Terms Memory design
  Multi-Service** design
  Testing Flow** with or without dependance on other workflow.
  Error Management**

  What this workflow does?

  This is a n8n Demo Call Center Workflow demo. It is the main entry node for a Multiple Services Chatbot. It will receive message from the Call In Workflow, and decide which service should be use, or which service provider should be process the selected result.

  How it works

  The Flow Trigger node will wait for the message from the Call In Workflow or other Sub-workflow.
  When message is received, it will first check for the Rate Limit.
  If ok, load the Session Data from Cache.
  Next, check the current Session for the channel_no (default is chat).
  if channel_no is chat, continue to the AI Agent for chit-chat.
  if channel_no is taxi or others, pass to the Service Input (i.e. Taxi Service) or Service Worker (i.e. Taxi Booking Worker) to handle it directly.
  The AI Agent should decide which service (i.e. taxi) will be used at some point and update the channel_no in Session, and pass to the Service Node (i.e. Taxi Service) at once.
  In case of any error, reply the error in Call Back.

  Set up instructions

  Pull and Set up the required SQL from our Github repository.
  Create you Redis credentials, refer to n8n integration documentation for more information.
  Select your Credentials in Rate Limit, Session, Provider and New Session.
  Create you Postgres credentials, refer to n8n integration documentation for more information.
  Select your Credentials in Postgres Chat Memory, Load User Memory and Save User Memory.
  Modify the AI Agent prompt to fit your need

  How to adjust it to your needs

  In Session, we have a timestamp fields which is created at the Input node. The usage of this is combined to use with the session id to create a unique session, since some media, such as Telegram, do not have a unique session along with the chat.
  You can use any AI Model for the AI Agent node
  Learn we use the prompt for the Load/Save User Memory on demand.
  Include is our prompt for the taxi service. You can add more service similar to this.

nodes_used:
  ["n8n-nodes-base.redis","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.chatTrigger","n8n-nodes-base.set","n8n-nodes-base.executeWorkflowTrigger","n8n-nodes-base.redis","n8n-nodes-base.if","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.switch","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatXAiGrok","@n8n/n8n-nodes-langchain.memoryPostgresChat","n8n-nodes-base.postgresTool","n8n-nodes-base.postgresTool","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.toolWorkflow","n8n-nodes-base.redis","n8n-nodes-base.redis","n8n-nodes-base.set","n8n-nodes-base.code","n8n-nodes-base.set","n8n-nodes-base.switch","n8n-nodes-base.switch","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.set","n8n-nodes-base.executeWorkflow","n8n-nodes-base.executeWorkflow","n8n-nodes-base.executeWorkflow"]

workflow_json_compressed:
  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

metadata_json:
  {"categories":["AI/ML"],"complexity":"medium","use_cases":["automate call center interactions","integrate AI chatbots with databases","manage ticket routing with n8n","handle incoming voice/text calls"],"estimated_setup_minutes":60,"required_services":["Redis","Postgres","Telegram API","MongoDB","AI Language Models"],"key_features":["AI agent response generation","multi-step sub-workflow execution","database connection management","dynamic ticket creation","complex conditional routing"],"target_audience":["customer support managers","chatbot developers","automated agents"]}


name: AI Chatbot Call Center: Taxi Service (Production-Ready, Part 3)
author_name: ChatPayLabs
author_username: chatpaylabs
categories: []
created_at: 2025-05-14T15:27:06.322Z
updated_at: 2025-05-14T15:27:06.322Z
url: https://n8n.io/workflows/4046
scraped_at: 2026-05-02 08:04:51
metadata_generated_at: 2026-05-02 08:36:21
description:
  Workflow Name: 🛎️ Taxi Service

  Template was created in n8n v1.90.2

  Skill Level: High

  Categories: n8n, Chatbot

  Stacks

  Execute Sub-workflow Trigger node
  Chat Trigger node
  Redis node
  Postgres node
  AI Agent node
  If node, Switch node, Code node, Edit Fields (Set)

  Prerequisite

  Execute Sub-workflow Trigger: Taxi Service Workflow (or your own node)
  Sub-workflow: Taxi Service Provider (or your own node)
  Sub-workflow: Demo Call Back (or your own node)

  Production Features

  Scaling Design* for n8n *Queue mode** in production environment
  Service Data* from *external Database* with *Caching Mechanism**
  Optional Long Terms Memory design
  Find Route Distance* using *Google Map API**
  Optional Multi-Language Wait Output example
  Error Management**

  What this workflow does?

  This is a n8n Taxi Service Workflow demo. It is the core node for Taxi Service. It will receive message from the Call Center Workflow, handling the QA from the caller, and pass to each of the Taxi Service Provider Workflow to process the estimation.

  How it works

  The Flow Trigger node will wait for the message from Call Center or other Sub-workflow.
  When message is received, it will first check for the matching Service from the PostgreSQL database.
  If no service or service is inactive, output Error.
  Next, always reset the Session Data in Cache, with channel_no set to taxi
  Next, delete the previous Route Data in Cache
  Trigger a AI Agent to process the fare estimation question to create the Route Data
  Use the Google Map Route API to calculate the distance.
  Repeat until created the route data, then pass to all the Taxi Service Provider for an estimation.

  Set up instructions

  Pull and Set up the required SQL from our Github repository.
  Create you Redis credentials, refer to n8n integration documentation for more information.
  Select your Credentials in Service Cache, Save Service Cache, Reset Session, Delete Route Data, Route Data, Update User Session and Create Route Data.
  Create you Postgres credentials, refer to n8n integration documentation for more information.
  Select your Credentials in Load Service Data, Postgres Chat Memory, Load User Memory and Save User Memory.
  Modify the AI Agent prompt to fit your need
  Set you Google Map API key in Find Route Distance

  How to adjust it to your needs

  By default, this template will use the sys_service table provider information, you could change it for your own design.
  You can use any AI Model for the AI Agent node
  Learn we use the prompt for the Load/Save User Memory on demand.
  Include is our prompt for the taxi service. It is a flexible design which use the data from the Service node to customize the prompt, so you could duplicate this workflow as another service.
  Create difference Taxi Providers to process the and feedback the estimate.

nodes_used:
  ["n8n-nodes-base.executeWorkflowTrigger","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.chatTrigger","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.memoryPostgresChat","n8n-nodes-base.set","n8n-nodes-base.redisTool","@n8n/n8n-nodes-langchain.lmChatXAiGrok","n8n-nodes-base.postgresTool","n8n-nodes-base.stickyNote","n8n-nodes-base.if","n8n-nodes-base.redis","n8n-nodes-base.postgres","n8n-nodes-base.redis","n8n-nodes-base.if","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.stickyNote","n8n-nodes-base.set","n8n-nodes-base.stickyNote","n8n-nodes-base.postgresTool","n8n-nodes-base.redisTool","n8n-nodes-base.redis","n8n-nodes-base.redis","n8n-nodes-base.if","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequestTool","n8n-nodes-base.redis","n8n-nodes-base.switch","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.stickyNote","n8n-nodes-base.executeWorkflow","n8n-nodes-base.executeWorkflow"]

workflow_json_compressed:
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metadata_json:
  {"categories":["AI/ML","Communication","Data Processing"],"complexity":"complex","use_cases":["automate call center interactions","route taxi service requests","handle customer support chats","integrate AI chatbot workflows"],"estimated_setup_minutes":45,"required_services":["PostgreSQL","Redis","AI/ML APIs","Communication APIs"],"key_features":["productions ready for","sub-workflow orchestration","conditional routing logic","stateful chat sessions","external agent integration"],"target_audience":["developers","ops engineers","support managers"]}


name: Taxi Service Provider (Production-Ready, Part 4)
author_name: ChatPayLabs
author_username: chatpaylabs
categories: []
created_at: 2025-05-14T15:28:48.092Z
updated_at: 2025-05-14T15:28:48.092Z
url: https://n8n.io/workflows/4047
scraped_at: 2026-05-02 08:04:51
metadata_generated_at: 2026-05-02 08:36:21
description:
  Workflow Name: 🤖 Taxi Service Provider

  Template was created in n8n v1.90.2

  Skill Level: High

  Categories: n8n, Chatbot

  Stacks

  Execute Sub-workflow Trigger node
  Chat Trigger node
  Redis node
  Postgres node
  AI Agent node
  Calculator node
  If node, Switch node, Code node, Edit Fields (Set)

  Prerequisite

  Execute Sub-workflow Trigger: Taxi Service Workflow (or your own node)
  Sub-workflow: Demo Call Back (or your own node)

  Production Features

  Scaling Design* for n8n *Queue mode** in production environment
  Provider Data* from *external Database* with *Caching Mechanism**
  Optional Score design output
  Optimize Taxi Provider Prompt from database
  Error Management**

  What this workflow does?

  This is a n8n Taxi Provider Workflow demo. It will receive message from the Taxi Service Workflow, process the estimation and return to the caller.

  How it works

  The Flow Trigger node will wait for the message from other Sub-workflow.
  When message is received, it will first check for the matching Provider from the PostgreSQL database.
  Then it will increase a Provider Number in Redis for selection later
  Trigger a AI Agent to process the fare estimation and create a NEW booking
  Finally, send the AI response to the Call Output
  Note: if the Provider is set to inactive, it will do nothing

  Set up instructions

  Pull and Set up the required SQL from our Github repository.
  Create you Redis credentials, refer to n8n integration documentation for more information.
  Select your Credentials in Provider Cache, Save Provider Cache and Provider Number.
  Create you Postgres credentials, refer to n8n integration documentation for more information.
  Select your Credentials in Load Provider Data and Create Booking Data.
  Modify the AI Agent prompt to fit your need

  How to adjust it to your needs

  By default, this template will use the sys_provider table provider information, you could change it for your own design.
  You can use any AI Model for the AI Agent node
  Include is our prompt for the taxi service provider. It is a flexible design which use the data from the Provider Cache to customize the prompt, so you could create more Taxi Service Providers by duplicate this workflow in the Taxi Service node.

nodes_used:
  ["n8n-nodes-base.executeWorkflowTrigger","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.chatTrigger","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.code","@n8n/n8n-nodes-langchain.lmChatXAiGrok","n8n-nodes-base.postgresTool","n8n-nodes-base.stickyNote","n8n-nodes-base.redis","@n8n/n8n-nodes-langchain.toolCalculator","n8n-nodes-base.stickyNote","n8n-nodes-base.if","n8n-nodes-base.redis","n8n-nodes-base.postgres","n8n-nodes-base.redis","n8n-nodes-base.code","n8n-nodes-base.set","n8n-nodes-base.stickyNote","n8n-nodes-base.set","n8n-nodes-base.if","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.stickyNote","n8n-nodes-base.if","n8n-nodes-base.stickyNote","n8n-nodes-base.set","n8n-nodes-base.stickyNote","n8n-nodes-base.executeWorkflow","n8n-nodes-base.switch"]

workflow_json_compressed:
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metadata_json:
  {"categories":["AI/ML","Customer Service"],"complexity":"medium","use_cases":["automated taxi request handling","chatbot take orders","reserve cabs via messaging","log ride bookings","route scheduling notifications"],"estimated_setup_minutes":60,"required_services":["Redis","Postgres","LMGrok (Groq)","Twilio(SMS/Fax)* optional"],"key_features":["queue-based work mode","AI chat interface integration","multi-step conversation handling","fallback routing logic","production scalabale design"],"target_audience":["fleet operators","customer service reps","system administrators"]}


name: AI Chatbot Call Center: Taxi Booking Worker (Production-Ready, Part 5)
author_name: ChatPayLabs
author_username: chatpaylabs
categories: []
created_at: 2025-05-14T15:30:14.972Z
updated_at: 2025-05-14T15:30:14.972Z
url: https://n8n.io/workflows/4048
scraped_at: 2026-05-02 08:04:51
metadata_generated_at: 2026-05-02 08:36:20
description:
  Workflow Name: 👷‍♂️ Taxi Booking Worker

  Template was created in n8n v1.90.2

  Skill Level: High

  Categories: n8n, Chatbot

  Stacks

  Execute Sub-workflow Trigger node
  Chat Trigger node
  Redis node
  Postgres node
  Google Calendar node
  Execute Sub-workflow
  If node, Switch node, Code node, Edit Fields (Set)

  Prerequisite

  Execute Sub-workflow Trigger: Call In Center (or your own node)
  Sub-workflow: Demo Call Back (or your own node)

  Production Features

  Scaling Design* for n8n *Queue mode** in production environment
  Customize Open Booking Action
  Integrate  with Long Term Memory backup.
  Error Management**

  What this workflow does?

  This is a n8n Taxi Booking Worker, the worker node to process the job. It will wait for message from the Call Center node and handle the real process here. In this particular case, it will check the input number for the selected provider, then update the booking from NEW to OPEN, then clean up the orphan data.

  How it works

  The Form Trigger node will wait for the message from any node with the input in number.
  First check for NEW booking under the same chat session
  For input 0, which is cancel
      Reset the user session in Redis memory
  For input 1 or above, which is the provider selection number
      Set the booking status to OPEN in database
      OPTIONAL Save the summary to User Memory database
      OPTIONAL Create a new Event in Google Calendar and sync to the database
      Reset the user session in Redis memory
  Afterward, process data clean up
      Delete the provider selection number queue in Redis
      Delete the route data in Redis
      OPTIONAL Delete the chat memory with current session
  Finally, output the response to the Call Back node

  Set up instructions

  Pull and Set up the required SQL from our Github repository.
  Create you Postgres credentials, refer to n8n integration documentation for more information.
  Select your Credentials in Booking, Set Open Booking, Sync Booking Google Cal, and Save User Memory.
  Create you Redis credentials, refer to n8n integration documentation for more information.
  Select your Credentials in Reset Session, Reset Session 2, Delete Provider Number and Delete Route Data.
  Create your Google Calendar credentials, refer to n8n integration documentation for more information.
  Create a Google Calendar, e.g. DEMO
  Select your Credentials in Create Event, and select the above Calendar
  FOR TEST ONLY. Enable the Telegram Test Output for testing from the Test Input.

  How to adjust it to your needs

  You can specific a number to trigger the specific action based on your needs.
  The current action only create a event in Google Calendar, you can do more based on your needs.
  You can replace the sub-workflow trigger Flow Trigger and Call Back to another flow as needs.

nodes_used:
  ["n8n-nodes-base.executeWorkflowTrigger","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.chatTrigger","n8n-nodes-base.set","n8n-nodes-base.redis","n8n-nodes-base.set","n8n-nodes-base.postgres","n8n-nodes-base.postgres","n8n-nodes-base.redis","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.redis","n8n-nodes-base.if","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.if","n8n-nodes-base.stickyNote","n8n-nodes-base.set","n8n-nodes-base.redis","n8n-nodes-base.switch","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.postgres","n8n-nodes-base.executeWorkflow","n8n-nodes-base.set","n8n-nodes-base.stickyNote","n8n-nodes-base.googleCalendar","n8n-nodes-base.executeWorkflow","n8n-nodes-base.postgres","n8n-nodes-base.postgres"]

workflow_json_compressed:
  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

metadata_json:
  {"categories":["AI/ML","Communication","Customer Service","Automation","Data Processing"],"complexity":"complex","use_cases":["handle real-time taxi booking requests","simulate call center interactions","scale customer communication","manage booking storage and retrieval"],"estimated_setup_minutes":120,"required_services":["Redis","PostgreSQL","Google Calendar"],"key_features":["sub-workflow orchestration","conditionals and switches for booking logic","scalable queue mode design","database integration for state management"],"target_audience":["customer support agents","system architects","automation developers"]}


name: AI Chatbot Call Center: Demo Call Back (Production-Ready, Part 6)
author_name: ChatPayLabs
author_username: chatpaylabs
categories: []
created_at: 2025-05-14T15:32:58.059Z
updated_at: 2025-05-14T15:32:58.059Z
url: https://n8n.io/workflows/4050
scraped_at: 2026-05-02 08:04:51
metadata_generated_at: 2026-05-02 08:36:20
description:
  Workflow Name: 💬 Demo Call Back

  Template was created in n8n v1.90.2

  Skill Level: High

  Categories: n8n, Chatbot

  Stacks

  Execute Sub-workflow Trigger node
  Chat Trigger node
  Redis node
  Postgres node
  Telegram node
  HTTP Request node
  If node, Code node, Edit Fields (Set)

  Prerequisite

  Execute Sub-workflow Trigger: your own node
  MiniMax Account (https://www.minimax.io/)

  Production Features

  Scaling Design* for n8n *Queue mode** in production environment
  Optional Provider Data from external Database with Caching Mechanism.
  Optional AI Clone Voice Message response via MiniMax API with Multi-Languages support.
  Optional Backup Chat Log to Database, so you can use in APP/API building.
  Testing Flow** with or without dependance on other workflow.
  Multi Chatbot** (This is a demo for Telegram, you can add WhatsApp, Line, etc)
  Error Management**

  What this workflow does?

  This is a n8n Telegram Output Workflow. It will receive message from other Sub-workflow then output to Telegram for Message, or Replay Message and extra Voice Message.

  How it works

  The Flow Trigger node will wait for the message from other Sub-workflow.
  When message is received, it will first check for the matching Provider from the PostgreSQL database.
  Then determine if it is a Voice message to Text message.
  OPTIONAL. For voice message, use the MiniMax API to generate a voice message, then send it to Telegram.
  Finally, send the text to Telegram.

  Set up instructions

  Pull and Set up the required SQL from our Github repository.
  Create you Redis credentials, refer to n8n integration documentation for more information.
  Select your Credentials in Provider Cache and Save Provider Cache.
  Create you Postgres credentials, refer to n8n integration documentation for more information.
  Select your Credentials in Load Member Data, Create Chat Log Input, and Create Chat Log Output.
  Create you Telegram credentials, refer to n8n integration documentation for more information.
  Select your Credentials in Telegram Voice Output, Telegram Reply Output, and Telegram Output.

  AI Clone Voice setup instructions (Optional)

  You can clone any voice with MiniMax

  Go to https://www.minimax.io/ and create a MiniMax account
  Setup the Database with the required variables found in the MiniMax TTS node
  That’s it

  How to adjust it to your needs

  By default, this template will use the sys_provider table provider information, you could change it for your own design.
  The demo use MiniMax API for AI voice cloning, you could implement any other AI your choice.
  The Backup Chat Log will backup all chat conversion line by line. You can use it for you own APP/API development.

nodes_used:
  ["n8n-nodes-base.switch","n8n-nodes-base.executeWorkflowTrigger","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.chatTrigger","n8n-nodes-base.set","n8n-nodes-base.httpRequest","n8n-nodes-base.telegram","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.if","n8n-nodes-base.redis","n8n-nodes-base.redis","n8n-nodes-base.if","n8n-nodes-base.set","n8n-nodes-base.postgres","n8n-nodes-base.if","n8n-nodes-base.stickyNote","n8n-nodes-base.switch","n8n-nodes-base.postgres","n8n-nodes-base.postgres","n8n-nodes-base.if","n8n-nodes-base.set","n8n-nodes-base.switch","n8n-nodes-base.set","n8n-nodes-base.httpRequest","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.if","n8n-nodes-base.telegram","n8n-nodes-base.stickyNote","n8n-nodes-base.telegram","n8n-nodes-base.stickyNote","n8n-nodes-base.code"]

workflow_json_compressed:
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metadata_json:
  {"categories":["Communication","AI/ML","DevOps"],"complexity":"medium","use_cases":["handle incoming voice requests","simulate demo call callbacks","integrate voice AI with backend systems"],"estimated_setup_minutes":45,"required_services":["MiniMax AI","PostgreSQL","Redis","Telegram"],"key_features":["production-ready scaling architecture","reusable sub-workflow execution","queue mode implementation for high concurrency","multi-provider service integration"],"target_audience":["developers","devops engineers"]}


name: AI Chatbot Call Center: Taxi Booking Support (Production-Ready, Part 7)
author_name: ChatPayLabs
author_username: chatpaylabs
categories: []
created_at: 2025-05-14T15:34:22.600Z
updated_at: 2025-05-14T15:34:22.600Z
url: https://n8n.io/workflows/4051
scraped_at: 2026-05-02 08:04:51
metadata_generated_at: 2026-05-02 08:36:20
description:
  Workflow Name: 🫶 Taxi Booking Support

  Template was created in n8n v1.90.2

  Skill Level: Mid

  Categories: n8n, Chatbot

  Stacks

  Schedule Trigger node
  Postgres node
  AI Agent node
  Google Calendar node
  Execute Sub-workflow
  If node, Switch node, Code node, Edit Fields (Set)

  Prerequisite

  Sub-workflow: Demo Call Back (or your own node)

  Production Features

  Scaling Design* for n8n *Queue mode** in production environment
  Customize Expired Booking Actions example
  Multi-Language** Design

  What this workflow does?

  This is a n8n Taxi Booking Support, the background node to process the job at scheduled. It is scheduled to check the database for outstanding booking and handle the after sales process. In this particular case, it will check for OPEN booking over 10 minutes, then update the booking status from OPEN to CANCELLED, delete the Calendar event and send a reply to the user.

  How it works

  The Schedule Trigger node is scheduled to run every 5 minutes.
  It will check the database for OPEN or HOLD booking.
  For OPEN booking
      update the booking status to CANCELLED
      delete the Calendar event
      send a reply to the user
  Optional: The AI Agent is used to create the reply message to the user in Multi-language based on the language set in the booking.

  Set up instructions

  Pull and Set up the required SQL from our Github repository.
  Create you Postgres credentials, refer to n8n integration documentation for more information.
  Select your Credentials in Open Hold Booking and Set Cancel Booking.
  Create your Google Calendar credentials, refer to n8n integration documentation for more information.
  Create a Google Calendar, e.g. DEMO
  Select your Credentials in Delete Event, and select the above Calendar
  Remember to activate this workflow for schedule to run.

  How to adjust it to your needs

  There should be more status for the booking.
  The current action only check for OPEN and HOLD booking, you can do more based on your needs.
  You can replace the sub-workflow trigger Call Back to another flow as needs.

nodes_used:
  ["@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatXAiGrok","n8n-nodes-base.switch","n8n-nodes-base.postgres","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.set","n8n-nodes-base.executeWorkflow","n8n-nodes-base.postgres","n8n-nodes-base.if","n8n-nodes-base.if","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.googleCalendar"]

workflow_json_compressed:
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metadata_json:
  {"categories":["AI/ML","Communication","Customer Service"],"complexity":"medium","use_cases":["taxi booking support","customer call handling","multi-language interactions","scheduling confirmations"],"estimated_setup_minutes":60,"required_services":["Google Calendar","Postgres Database"],"key_features":["AI agent integration","multi-language bot support","queue mode for production","custom callback procedures"],"target_audience":["customer support agents","call center managers","AI developer"]}


name: AI Chatbot Call Center: General Exception Flow (Production-Ready, Part 8)
author_name: ChatPayLabs
author_username: chatpaylabs
nodes_used: ["n8n-nodes-base.errorTrigger","n8n-nodes-base.slack"]
categories: []
created_at: 2025-05-14T15:36:39.923Z
updated_at: 2025-05-14T15:36:39.923Z
url: https://n8n.io/workflows/4052
scraped_at: 2026-05-02 08:04:50
metadata_generated_at: 2026-05-02 08:36:20
description:
  Workflow Name: 👻 Exception Flow

  Template was created in n8n v1.90.2

  Skill Level: Low

  Categories: n8n, Chatbot

  Stacks

  Error Trigger
  Slack node

  What this workflow does?

  This is a n8n Error Workflow. It will trigger when there is an error in another workflow. When this happens, it then tries to send an error notification to the preset Slack channel.

  How it works

  The Error Trigger node will trigger when there is an error in another workflow, as long as that workflow is set up to do so.
  A error notification will be sent to the Slack Channel.

  Set up instructions

  Create you Slack credentials, refer to n8n integration documentation for more information.
  Set up the Channel in 👻 Exception Alert node.
  For any n8n workflows to trigger this, switch to that workflow, select menu &gt; settings, and set the Error Workflow to 👻 Exception Flow.

  How to adjust it to your needs

  Although this workflow template is part of the AI Chatbot Call Center Series, it could be used with any n8n workflows.

  Update the Channel in 👻 Exception Alert to your own channel

  https://chatpaylabs.com/blog/part-8-build-your-own-ai-chatbot-call-center-general-exception-flow-production-ready-n8n-workflow-free-download-

workflow_json_compressed:
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metadata_json:
  {"categories":["Communication","Error Handling","DevOps"],"complexity":"simple","use_cases":["capture workflow errors","notify errors to Slack","monitor error events"],"estimated_setup_minutes":15,"required_services":["Slack"],"key_features":["error trigger node","error notification","slack integration"],"target_audience":["developers","ops engineers"]}


name: Sort Gmail Emails with GPT-4o into Action Required and No Action Labels
author_name: Khaled
author_username: khaled
categories: []
created_at: 2025-05-14T16:10:55.017Z
updated_at: 2025-05-14T16:10:55.017Z
url: https://n8n.io/workflows/4053
scraped_at: 2026-05-02 08:04:50
metadata_generated_at: 2026-05-02 08:36:20
description:
  🧾 Description:

  This automation uses GPT-4o to scan unread Gmail emails and intelligently classify them as:

      Action → Requires your attention (reply, review, schedule, or respond)

      No Action → Informational or promotional; no action needed

  The result? You eliminate inbox noise and gain a clear daily routine: only check what's in Action Required.
  ⚙️ How It Works:

      Trigger: Runs on a customizable schedule

      Fetch Emails: Pulls unread messages from Gmail

      Classify via GPT-4o: Determines if each email needs action or not

      Sort Emails:

          Labels actionable emails as Action Required

          Labels non-actionable ones as No Action

          Removes the Inbox label to clean your primary inbox view

          ✅ Emails stay in your account—just better organized

  🚀 How to Use:

      Import the workflow into your n8n instance

      Set up Gmail and OpenAI credentials

      Create Gmail labels:

          Action Required

          No Action

      Activate the workflow

      Start your day by checking only the Action Required label

  📦 Requirements:

      n8n (self-hosted or cloud)

      Gmail OAuth2 account

      OpenAI API key (GPT-4o or GPT-4o-mini)

      Gmail labels: Action Required, No Action

  💡 Why It Matters:

  Stop manually filtering emails.
  This workflow helps you focus only on what matters while keeping everything else out of your way—without deleting or archiving anything.

nodes_used:
  ["n8n-nodes-base.scheduleTrigger","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.gmail","n8n-nodes-base.gmail","@n8n/n8n-nodes-langchain.textClassifier","n8n-nodes-base.gmail","n8n-nodes-base.gmail","n8n-nodes-base.gmail","n8n-nodes-base.stickyNote"]

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metadata_json:
  {"categories":["Communication","AI/ML"],"complexity":"medium","use_cases":["Sort emails automatically","Classify inbox priority"],"estimated_setup_minutes":30,"required_services":["Gmail","GPT-4o"],"key_features":["AI-powered email triage","Scheduled automation","Inbox organization"],"target_audience":["professionals","executives","admins"]}


name: Automated Replies to X Threads with Airtop Browser Automation
author_name: Airtop
author_username: cesar-at-airtop
categories: []
created_at: 2025-05-14T18:29:50.112Z
updated_at: 2025-05-14T18:29:50.112Z
url: https://n8n.io/workflows/4054
scraped_at: 2026-05-02 08:04:51
metadata_generated_at: 2026-05-02 08:36:20
description:
  Use Case
  Automatically responding to X (formerly Twitter) posts can help you engage with potential customers at scale, saving time while maintaining a personal touch.

  What This Automation Does
  This automation replies to specified X posts using the following input parameters:

  airtop_profile: The name of your Airtop Profile connected to X.
  thread_url: The URL of the X post to reply to. Example
  reply_text: The message you want to post as a reply.

  How It Works
  Creates a browser session using Airtop.
  Navigates to the specified X post.
  Types and submits the reply text.

  Setup Requirements
  Airtop API Key — free to generate.
  An Airtop Profile connected to X (requires one-time login).

  Next Steps
  Combine with X Monitoring**: Use this with the X monitoring automation to create a fully automated engagement pipeline.
  Extend to Other Platforms**: Adapt the automation for use on LinkedIn, Reddit, or any web community.

  Read more about this Airtop Automation.

nodes_used:
  ["n8n-nodes-base.executeWorkflowTrigger","n8n-nodes-base.airtop","n8n-nodes-base.airtop","n8n-nodes-base.airtop","n8n-nodes-base.wait","n8n-nodes-base.formTrigger","n8n-nodes-base.set","n8n-nodes-base.airtop","n8n-nodes-base.airtop","n8n-nodes-base.airtop","n8n-nodes-base.stickyNote"]

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metadata_json:
  {"categories":["Marketing","Communication"],"complexity":"medium","use_cases":["engage with potential customers at scale","auto-reply to social media posts","personalized messaging on X (Twitter)"],"estimated_setup_minutes":15,"required_services":["X (Twitter)","Airtop Browser Automation"],"key_features":["automated social media responses","browser-based interaction","customizable reply text"],"target_audience":["social media managers","community managers","customer support leads"]}


name: AI Talent Screener – CV Parser, Job Fit Evaluator & Email Notifier
author_name: Aayushman Sharma
author_username: ajstyle0411
categories: []
created_at: 2025-05-14T19:24:37.751Z
updated_at: 2025-05-14T19:24:37.751Z
url: https://n8n.io/workflows/4055
scraped_at: 2026-05-02 08:04:50
metadata_generated_at: 2026-05-02 08:36:20
description:
  AI Talent Screener – CV Parser, Job Fit Evaluator & Email Notifier

  Who is this for?
  This template is ideal for HR teams, recruiters, staffing agencies, and tech-enabled hiring managers looking to automate the intake, analysis, and shortlisting of job applicants directly from CV submissions.

  What problem is this workflow solving?
  Manually evaluating resumes for job openings is time-consuming and prone to bias or oversight. This workflow uses AI to extract candidate data, analyze fit based on job descriptions, and make data-backed shortlisting decisions — automatically updating Google Sheets and notifying both Talent Acquisition and candidates.

  What this workflow does
  This workflow automates your recruitment pipeline by:

  1. Accepting CV submissions via an embedded form.

  2. Saving resumes to Google Drive.

  3. Extracting and parsing resume content using AI.

  4. Fetching the relevant job description from Google Sheets.

  5. Summarizing both job and applicant profiles.

  6. Conducting an AI-powered fit evaluation (semantic match, red flags, soft skills, etc.).

  7. Updating detailed analysis in a centralized Google Sheet.

  8. Notifying the TA team for approval.

  9. Automatically sending shortlisting or rejection emails to candidates based on approval.

  Setup
  1. Connect credentials for:

  Google Sheets

  Google Drive

  OpenAI API

  SMTP email (for notification)

  2. Update the Google Sheets document IDs and folder IDs in the relevant nodes.

  3. Adjust the form fields in the "Form Trigger" node if needed.

  4. Customize email sender/receiver addresses in the email nodes.

  5. Enable the workflow and embed the form on your career page.

  For convenience, the sticky notes guide you through what each block does.

  How to customize this workflow to your needs
  Change job roles by editing the dropdown options in the form.

  Modify evaluation criteria in the “Semantic Fit & Evaluation by HR Expert” prompt.

  Add more fields (e.g., GitHub, portfolio links) to the form and extend parsing.

  Connect to ATS or Slack if you'd like to integrate further.

nodes_used:
  ["n8n-nodes-base.formTrigger","n8n-nodes-base.extractFromFile","@n8n/n8n-nodes-langchain.outputParserStructured","n8n-nodes-base.googleDrive","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.informationExtractor","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.googleSheets","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.chainSummarization","n8n-nodes-base.stickyNote","n8n-nodes-base.googleSheets","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.chainSummarization","@n8n/n8n-nodes-langchain.chainLlm","n8n-nodes-base.stickyNote","n8n-nodes-base.googleSheets","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.emailSend","n8n-nodes-base.if","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.emailSend","n8n-nodes-base.emailSend","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

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metadata_json:
  {"categories":["AI/ML","Data Processing","HR & Recruitment"],"complexity":"medium","use_cases":["parse resumes","evaluate candidates","notify hiring managers"],"estimated_setup_minutes":15,"required_services":["Google Drive","Email Provider (e.g. Gmail, SMTP)"],"key_features":["automated CV parsing","job fit scoring","automatic candidate notifications","conditional workflow routing"],"target_audience":["HR managers","recruiters","hiring managers"]}


name: Generate Images and Convert to Video Using Flux, Kraken & Runway
author_name: Joseph
author_username: mjomba
categories: []
created_at: 2025-05-14T19:48:15.928Z
updated_at: 2025-05-14T19:48:15.928Z
url: https://n8n.io/workflows/4056
scraped_at: 2026-05-02 08:04:49
metadata_generated_at: 2026-05-02 08:36:19
description:
  (Image Generation → Hosting → Video Generation)

  This workflow is designed for creators, automation enthusiasts, and indie hackers who want to generate image-based videos automatically using AI tools — at a low cost.

  ⚙️ Workflow Overview

  This automation performs the following steps:

  Trigger (Schedule or manual)
  Generate an image using Flux (choose between two APIs)
  Upload the image to Kraken.io to get a public URL
  Send the image to Runway ML (choose between two APIs) to generate a video
  Receive the video as a URL — ready for posting, download, or further automation

  🛠️ Step-by-Step Setup

  🖼️ Flux (Image Generation)

  You can use either of the following providers:

  Option 1: Flux by BlackForest Labs (Direct API)

  🔑 Get your API key here: https://docs.bfl.ml/

  Paste your API key in the HTTP Request node named Flux (Blackforest)
  You can customize prompts or styles inside the JSON body

  Option 2: Flux via RapidAPI

  🔑 Subscribe and get your key here:
  https://rapidapi.com/poorav925/api/ai-text-to-image-generator-flux-free-api/playground/apiendpoint\_e38039ee-1912-4ef9-b4d4-270d72fca851

  Enter your RapidAPI key in the X-RapidAPI-Key header
  Optional: tweak prompts, style, or resolution inside the JSON body

  🐙 Kraken.io (Hosting the Image Publicly)

  Runway ML requires the image to be publicly accessible. We use Kraken.io to host the generated image and return a public URL.

  🔑 Get your API credentials: https://kraken.io/account/api-credentials

  Setup:

  Copy your API Key and API Secret
  Open the Kraken Upload node in n8n
  Replace placeholders with your credentials
  The node uploads your image and gives back a public image URL for Runway to use

  🎬 RunwayML (Video Generation)

  You also have two options here:

  Option 1: Runway Official API

  🔑 Get your credentials at: https://dev.runwayml.com/

  Use the public image URL from Kraken in the JSON body
  Paste your Bearer token in the Authorization header
  Customize other settings like video length, style, FPS, etc.

  Option 2: Runway via RapidAPI

  🔑 Subscribe and get your key here:
  https://rapidapi.com/fortunehoppers/api/runwayml/playground/apiendpoint\_93c8554d-8097-40cd-8252-3d4dec9c0e68

  Paste your RapidAPI key in the request header
  Customize prompt and generation options in the body
  Use the Kraken-generated image URL as the input source

  📤 What to Do with the Video

  Once the video is generated, you’ll get a direct video URL. You can:

  Save it to Google Sheets or Notion
  Send it via email
  Trigger a YouTube upload automation
  Or download manually for editing and reposting

  💡 Optional Tips & Notes

  You can schedule this workflow to generate AI videos daily or weekly
  Combine it with a Google Sheet of prompts for bulk automation
  Try using a consistent visual style or theme for better branding
  This workflow is lightweight and affordable — perfect for indie projects or experimental content generation
  Great for shorts, quote visuals, music loops, AI art promos, etc.

  🔗 Resources

  Flux (Blackforest) Docs
  Flux on RapidAPI
  RunwayML Official Docs
  Runway on RapidAPI
  Kraken.io API Dashboard

  🙋 Need Help?

  Feel free to reach out:

  🐦 Twitter: @juppfy
  📧 Email: joseph@uppfy.com

  If you’d like to hire me for custom n8n workflows or product automations, don’t hesitate to get in touch.

nodes_used:
  ["n8n-nodes-base.wait","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.manualTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequest","n8n-nodes-base.switch","n8n-nodes-base.wait","n8n-nodes-base.stickyNote","n8n-nodes-base.wait","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest"]

workflow_json_compressed:
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metadata_json:
  {"categories":["AI/ML","Content Creation"],"complexity":"medium","use_cases":["automate video content generation","convert AI images to videos","create marketing visuals programmatically"],"estimated_setup_minutes":15,"required_services":["Flux","Kraken.io","Runway ML"],"key_features":["schedule triggered image-to-video generation","multi-API selection for custom models","image hosting integration for public URLs"],"target_audience":["creators","indie hackers","automation enthusiasts"]}


name: Auto-Respond to Gmail Enquiries using GPT-4o, Dumpling AI & LangChain Agent
author_name: Yang
author_username: yang
categories: []
created_at: 2025-05-14T21:06:14.263Z
updated_at: 2025-05-14T21:06:14.263Z
url: https://n8n.io/workflows/4057
scraped_at: 2026-05-02 08:04:49
metadata_generated_at: 2026-05-02 08:36:19
description:
  Who is this for?

  This workflow is perfect for customer support teams, sales departments, or solopreneurs who receive frequent email enquiries and want to automate the initial response process using AI. If you spend too much time answering similar questions, this system helps respond faster and more intelligently—without writing a single line of code.

  What problem is this workflow solving?

  Manually responding to repeated customer enquiries slows productivity and increases delay. This workflow classifies if an incoming email is a real enquiry, analyzes the content with a LangChain-powered agent, fetches helpful context using Dumpling AI, and sends a personalized reply using Gmail—all within minutes.

  What this workflow does

  Listens for new incoming Gmail messages using the Gmail Trigger node.  
  Classifies whether the email is an enquiry using a GPT-4o classification prompt.  
  Uses a Filter node to continue only if the email was classified as an enquiry.  
  Passes the email content to a LangChain Agent, enhanced with memory, AI tools, and Dumpling AI to search for relevant information.  
  The agent constructs a smart, relevant response, then sends it to the original sender via Gmail.

  Setup

  Connect Gmail  
     Use the Gmail Trigger node to connect to the Gmail account that receives enquiries.  
     Make sure Gmail OAuth2 credentials are authenticated.

  Configure Dumpling AI Agent  
     Sign up at Dumpling AI.  
     Create an agent trained to search your help docs, site content, or FAQs.  
     Copy your Dumpling agent ID and API key.  
     Paste it in the Dumpling AI Agent – Search for Relevant Info HTTP Request node.

  Set Up LangChain Agent  
     No extra setup needed beyond connecting OpenAI credentials.  
     GPT-4o is used for classification and reply generation.

  Enable Gmail Reply Node  
     The final Send Email Response via Gmail node will send the AI-generated reply back to the same thread.

  How to customize this workflow to your needs

  Change the classification prompt to include other email types like “support”, “complaint”, or “sales”.  
  Add additional logic if you want to CC someone or forward certain types of enquiries.  
  Add a Notion or Google Sheets node to log the conversation for analytics.  
  Replace Gmail with Outlook or another email provider by switching the nodes.  
  Improve context by adding more AI tools like database queries or preloaded FAQs.

nodes_used:
  ["n8n-nodes-base.gmailTrigger","@n8n/n8n-nodes-langchain.openAi","n8n-nodes-base.filter","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.memoryBufferWindow","@n8n/n8n-nodes-langchain.toolHttpRequest","n8n-nodes-base.gmailTool","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
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metadata_json:
  {"categories":["AI/ML","Communication"],"complexity":"medium","use_cases":["auto-generate email responses","FAQ automation","customer support replies","sales inquiry handling"],"estimated_setup_minutes":30,"required_services":["Gmail","GPT-4o","Dumpling AI"],"key_features":["Natural language generation","Semantic search","Memory context retention","LangChain agent orchestration"],"target_audience":["customer support agents","sales professionals","solopreneurs"]}


name: Homey Pro - Smarthouse integration with LLM
author_name: Ole Andre Torjussen
author_username: oleandre
categories: []
created_at: 2025-05-14T21:30:37.315Z
updated_at: 2025-05-14T21:30:37.315Z
url: https://n8n.io/workflows/4058
scraped_at: 2026-05-02 08:04:50
metadata_generated_at: 2026-05-02 08:36:20
description:
  This n8n workflow sets up a smart home assistant using OpenAI and Homey integration. It uses LangChain agent tools to allow natural language queries (in Norwegian) to trigger workflows for controlling lights, curtains, temperature, TVs, and other devices across different rooms (e.g., living room, bedroom, cinema). The system uses tool-based workflows connected to specific smart home actions and responds in Norwegian. It’s designed to be modular and easily extended with new devices or capabilities.

nodes_used:
  ["@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.set","n8n-nodes-base.executeWorkflowTrigger","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.lmChatXAiGrok","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow"]

workflow_json_compressed:
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metadata_json:
  {"categories":["AI/ML","Smart Home","Communication"],"complexity":"medium","use_cases":["Natural language home control","Multi-room device management","Voice command automation","Smart home query automation"],"estimated_setup_minutes":45,"required_services":["OpenAI","LangChain","Homey"],"key_features":["LLM-driven agent tools","Multi-language support (Norwegian)","Room-based device targeting","Modular workflow design"],"target_audience":["smart home administrators","IoT developers","automation enthusiasts"]}


name: Extract and Save Invoice Data from Google Drive to Sheets with Dumpling AI
author_name: Yang
author_username: yang
categories: []
created_at: 2025-05-14T21:31:31.196Z
updated_at: 2025-05-14T21:31:31.196Z
url: https://n8n.io/workflows/4059
scraped_at: 2026-05-02 08:04:49
metadata_generated_at: 2026-05-02 08:36:19
description:
  Who is this for?

  This workflow is perfect for operations teams, accountants, e-commerce businesses, or finance managers who regularly process digital invoices and need to automate data extraction and record-keeping.

  What problem is this workflow solving?

  Manually reading invoice PDFs, extracting relevant data, and entering it into spreadsheets is time-consuming and error-prone. This workflow automates that process—watching a Google Drive folder, extracting structured invoice data using Dumpling AI, and saving the results into Google Sheets.

  What this workflow does

  Watches a specific Google Drive folder for new invoices.
  Downloads the uploaded invoice file.
  Converts the file into a Base64 format.
  Sends the file to Dumpling AI’s extract-document endpoint with a detailed parsing prompt.
  Parses Dumpling AI’s JSON response using a Code node.
  Splits the items array into individual rows using the Split Out node.
  Appends each invoice item to a preformatted Google Sheet along with the full header metadata (order number, PO, addresses, etc.).

  Setup

  Google Drive Setup
     Create or select a folder in Google Drive and place the folder ID in the trigger node.
     Make sure your n8n Google Drive credentials are authorized for access.

  Google Sheets
     Create a Google Sheet with the following headers:
       Order number, Document Date, Po_number, Sold to name, Sold to address, Ship to name, Ship to address, Model, Description, Quantity, Unity price, Total price
     Paste the Sheet ID and sheet name (Sheet1) into the Google Sheets node.

  Dumpling AI
     Sign up at Dumpling AI
     Go to your account settings and generate your API key.
     Paste this key into the HTTP header of the Dumpling AI request node.
     The endpoint used is: https://app.dumplingai.com/api/v1/extract-document

  Prompt (already included)
     This prompt extracts: order number, document date, PO number, shipping/billing details, and detailed line items (model, quantity, unit price, total).

  How to customize this workflow to your needs

  Adjust the Google Sheet fields to fit your invoice structure.
  Modify the Dumpling AI prompt if your invoices have additional or different data points.
  Add filtering logic if you want to handle different invoice types differently.
  Replace Google Sheets with Airtable or a database if preferred.
  Use a different trigger like an email attachment if invoices come via email.

nodes_used:
  ["n8n-nodes-base.googleDriveTrigger","n8n-nodes-base.googleDrive","n8n-nodes-base.extractFromFile","n8n-nodes-base.httpRequest","n8n-nodes-base.code","n8n-nodes-base.splitOut","n8n-nodes-base.googleSheets","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
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metadata_json:
  {"categories":["Finance","Data Processing"],"complexity":"medium","use_cases":["automate invoice data extraction","sync invoices to spreadsheets","process PDF invoices"],"estimated_setup_minutes":15,"required_services":["Google Drive","Google Sheets","Dumpling AI"],"key_features":["monitors Google Drive folder","extracts structured data from PDFs","automates data entry to spreadsheets"],"target_audience":["finance managers","operations teams","accountants"]}


name: Automated daily workflow backup to GitHub
author_name: Hugo
author_username: hugop
categories: []
created_at: 2025-05-15T02:33:44.721Z
updated_at: 2025-05-15T02:33:44.721Z
url: https://n8n.io/workflows/4064
scraped_at: 2026-05-02 08:04:49
metadata_generated_at: 2026-05-02 08:36:19
description:
  This workflow provides a robust solution for automatically backing up all your n8n workflows to a designated GitHub repository on a daily basis. By leveraging the n8n API and GitHub API, it ensures your workflows are version-controlled and securely stored, safeguarding against data loss and facilitating disaster recovery.

  How it works

  The automation follows these key steps:

  Scheduled trigger: The workflow is initiated automatically every day at a pre-configured time.
  List existing backups: It first connects to your GitHub repository to retrieve a list of already backed-up workflow files. This helps in determining whether a workflow's backup file needs to be created or updated.
  Retrieve n8n workflows: The workflow then fetches all current workflows directly from your n8n instance using the n8n REST API.
  Process and prepare: Each retrieved workflow is individually processed. Its data is converted into JSON format. This JSON content is then encoded to base64, a format suitable for GitHub API file operations.
  Commit to GitHub: For each n8n workflow:
      A standardized filename is generated (e.g., workflow-name-tag.json).
      The workflow checks if a file with this name already exists in the GitHub repository (based on the list fetched in step 2).
      If the file exists: It updates the existing file with the latest version of the workflow.
      If it's a new workflow (file doesn't exist): A new file is created in the repository.
      Each commit is timestamped for clarity.

  This process ensures that you always have an up-to-date version of all your n8n workflows stored securely in your GitHub version control system, providing peace of mind and a reliable backup history.

  Pre-requisites

  Before you can use this template, please ensure you have the following:

  An active n8n instance (self-hosted or cloud).
  A GitHub account.
  A GitHub repository created where you want to store the workflow backups.
  A GitHub Personal Access Token with repo scope (or fine-grained token with read/write access to the specific backup repository). This token will be used for GitHub API authentication.
  n8n API credentials (API key) for your n8n instance.

  Set up steps

  Setting up this workflow should take approximately 10-15 minutes if you have your credentials ready.

  Import the template: Import this workflow into your n8n instance.
  Configure n8n API credentials:
      Locate the "Retrieve workflows" node.
      In the "Credentials" section for "n8n API", create new credentials (or select existing ones).
      Enter your n8n instance URL and your n8n API Key (you can create your n8n api key in the settings of your n8n instance)
  Configure GitHub credentials:
      Locate the "List files from repo" node (and subsequently "Update file" / "Upload file" nodes which will use the same credential).
      In the "Credentials" section for "GitHub API", create new credentials.
      Select OAuth2/Personal Access Token authentication method.
      Enter the GitHub Personal Access Token you generated as per the pre-requisites.
  Specify repository details:
      In the "List files from repo", "Update file", and "Upload file" GitHub nodes:
          Set the Owner: Your GitHub username or organization name.
          Set the Repository: The name of your GitHub repository dedicated to backups.
          Set the Branch (e.g., main or master) where backups should be stored.
          (Optional) Specify a Path within the repository if you want backups in a specific folder (e.g., n8n_backups/). Leave blank to store in the root.
  Adjust schedule (Optional):
      Select the "Schedule Trigger" node.
      Modify the trigger interval (e.g., change the time of day or frequency) as needed. By default, it's set for a daily run.
  Activate the workflow: Save and activate the workflow.

  Explanation of nodes

  Here's a detailed breakdown of each node used in this workflow:

  Schedule trigger**
      Type: n8n-nodes-base.scheduleTrigger
      Purpose: This node automatically starts the workflow based on a defined schedule (e.g., daily at midnight).
  List files from repo**
      Type: n8n-nodes-base.github
      Purpose: Connects to your specified GitHub repository and lists all files, primarily to check for existing workflow backups.
  Aggregate**
      Type: n8n-nodes-base.aggregate
      Purpose: Consolidates the list of file names obtained from the "List files from repo" node into a single item for easier lookup later in the "Check if file exists" node.
  Retrieve workflows**
      Type: n8n-nodes-base.n8n
      Purpose: Uses the n8n API to fetch a list of all workflows currently present in your n8n instance.
  Json file**
      Type: n8n-nodes-base.convertToFile
      Purpose: Takes the data of each workflow (retrieved by the "Retrieve workflows" node) and converts it into a structured JSON file format.
  To base64**
      Type: n8n-nodes-base.extractFromFile
      Purpose: Converts the binary content of the JSON file (from the "Json file" node) into a base64 encoded string. This encoding is required by the GitHub API for file content.
  Commit date & file name**
      Type: n8n-nodes-base.set
      Purpose: Prepares metadata for the GitHub commit. It generates:
          commitDate: The current date and time for the commit message.
          fileName: A standardized file name for the workflow backup (e.g., my-workflow-vps-backups.json), typically using the workflow's name and its first tag.
  Check if file exists**
      Type: n8n-nodes-base.if
      Purpose: A conditional node. It checks if the fileName (generated by "Commit date & file name") is present in the list of files aggregated by the "Aggregate" node. This determines if the workflow backup already exists in GitHub.
  Update file**
      Type: n8n-nodes-base.github
      Purpose: If the "Check if file exists" node determines the file does exist, this node updates that existing file in your GitHub repository with the latest workflow content (base64 encoded) and a commit message.
  Upload file**
      Type: n8n-nodes-base.github
      Purpose: If the "Check if file exists" node determines the file does not exist, this node creates and uploads a new file to your GitHub repository with the workflow content and a commit message.

  Customization

  Here are a few ways you can customize this template to better fit your needs:

  Backup path**: In the GitHub nodes ("List files from repo", "Update file", "Upload file"), you can specify a Path parameter to store backups in a specific folder within your repository (e.g., workflows/ or daily_backups/).
  Filename convention**: Modify the "Commit date & file name" node (specifically the expression for fileName) to change how backup files are named. For example, you might want to include the workflow ID or a different date format.
  Commit messages**: Customize the commit messages in the "Update file" and "Upload file" GitHub nodes to include more specific information if needed.
  Error handling**: Consider adding error handling branches (e.g., using the "Error Trigger" node or checking for node execution failures) to notify you if a backup fails for any reason.
  Filtering workflows**: If you only want to back up specific workflows (e.g., those with a particular tag or name pattern), you can add a "Filter" node after "Retrieve workflows" to include only the desired workflows in the backup process.
  Backup frequency**: Adjust the "Schedule Trigger" node to change how often the backup runs (e.g., hourly, weekly, or on specific days).


  Template was created in n8n v1.92.2

nodes_used:
  ["n8n-nodes-base.scheduleTrigger","n8n-nodes-base.n8n","n8n-nodes-base.aggregate","n8n-nodes-base.github","n8n-nodes-base.github","n8n-nodes-base.github","n8n-nodes-base.if","n8n-nodes-base.convertToFile","n8n-nodes-base.extractFromFile","n8n-nodes-base.stickyNote","n8n-nodes-base.set","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
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metadata_json:
  {"categories":["DevOps","Data Processing"],"complexity":"medium","use_cases":["daily backups of workloads","version control of automation workflows","disaster recovery of designs"],"estimated_setup_minutes":15,"required_services":["GitHub","n8n API"],"key_features":["automated backups","scheduled triggers","workflow aggregation","version control integration","disaster recovery"],"target_audience":["ops engineers","developers","admins"]}


name: Serve Inspirational Quotes On-Demand via Webhook using ZenQuotes API
author_name: ist00dent
author_username: ist00dent
categories: []
created_at: 2025-05-15T04:21:51.123Z
updated_at: 2025-05-15T04:21:51.123Z
url: https://n8n.io/workflows/4065
scraped_at: 2026-05-02 08:04:51
metadata_generated_at: 2026-05-02 08:36:20
description:
  This n8n template lets you instantly serve batches of inspirational quotes via a webhook using the free ZenQuotes API. It’s perfect for developers, content creators, community managers, or educators who want to add dynamic, uplifting content to websites, chatbots, or internal tools—without writing custom backend code.

  🔧 How it works
  A Webhook node listens for incoming HTTP requests on your chosen path.
  Get Random Quote from ZenQuotes sends an HTTP Request to https://zenquotes.io/api/random?count=5 and retrieves five random quotes.
  Format data uses a Set node to combine each quote (q) and author (a) into a single string:
  "“quote” – author".
  Send response returns a JSON array of objects { quote, author } back to the caller.

  👤 Who is it for?
  This workflow is ideal for:

  Developers building motivational Slack or Discord bots.
  Website owners adding on-demand quote widgets.
  Educators or trainers sharing daily inspiration via webhooks.
  Anyone learning webhook handling and API integration in n8n.

  🗂️ Response Structure
  Your webhook response will be a JSON array, for example:

  [
  {
  "quote": "Life is what happens when you're busy making other plans.",
  "author": "John Lennon"
  },
  {
  "quote": "Be yourself; everyone else is already taken.",
  "author": "Oscar Wilde"
  }
  ]

  ⚙️ Setup Instructions
  Import the workflow JSON into your n8n instance.
  In the Webhook node, set your desired path (e.g., /inspire).
  (Optional) Change the count parameter in the HTTP Request node to fetch more or fewer quotes.
  Activate the workflow.
  Test by sending an HTTP GET or POST to https://&lt;your-n8n-domain&gt;/webhook/&lt;path&gt;.

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequest","n8n-nodes-base.webhook","n8n-nodes-base.respondToWebhook","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.set","n8n-nodes-base.stickyNote"]

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metadata_json:
  {"categories":["AI/ML","Communication","Content Creation"],"complexity":"simple","use_cases":["serve quotes to websites","integrate with chatbots","add dynamic content to apps"],"estimated_setup_minutes":5,"required_services":["ZenQuotes API"],"key_features":["webhook-based on-demand delivery","random content generation","no backend code required"],"target_audience":["developers","content creators","community managers"]}


name: Track Hourly Weather Conditions with OpenWeatherMap and Google Sheets
author_name: ist00dent
author_username: ist00dent
categories: []
created_at: 2025-05-15T04:33:05.417Z
updated_at: 2025-05-15T04:33:05.417Z
url: https://n8n.io/workflows/4066
scraped_at: 2026-05-02 08:04:51
metadata_generated_at: 2026-05-02 08:36:20
description:
  This n8n template allows you to monitor hourly weather conditions in a specific city using OpenWeatherMap and log the results to a Google Sheet. It’s perfect for anyone needing periodic weather tracking—whether you're managing logistics, travel planning, or environmental monitoring.

  🔧 How it works
  A Schedule Trigger activates the workflow every hour.

  The Get Weather Data from OpenWeatherMap node fetches real-time weather details using the city name you specify.

  An IF node checks if the weather description contains "rain" or the temperature is below a set threshold.

  If the condition is true, the data is formatted with city, temperature, humidity, and conditions.

  The Google Sheets node appends this formatted information to your designated sheet.

  👤 Who is it for?
  This workflow is ideal for:

  Operations teams monitoring weather-sensitive logistics

  Researchers collecting climate data

  Developers and hobbyists learning how to connect APIs with Google Sheets

  🗂️ Google Sheet Structure
  Your Google Sheet should have the following columns:

  city (string)

  temperature (K) (number)

  humidity (number)

  conditions (string)

  status (string)

  ⚙️ Setup Instructions
  Create a Google Sheet with the above columns.

  Set up your Google Service Account credentials in n8n.

  Replace the API key in the HTTP Request node with your own OpenWeatherMap credential.

  Specify your target city and ensure your OpenWeatherMap account is active.

  Adjust the frequency in the Schedule Trigger as needed (default: every hour).

nodes_used:
  ["n8n-nodes-base.scheduleTrigger","n8n-nodes-base.googleSheets","n8n-nodes-base.httpRequest","n8n-nodes-base.if","n8n-nodes-base.set","n8n-nodes-base.stickyNote"]

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metadata_json:
  {"categories":["Data Processing"],"complexity":"simple","use_cases":["monitor hourly weather","log weather data","track environmental conditions"],"estimated_setup_minutes":5,"required_services":["OpenWeatherMap","Google Sheets"],"key_features":["schedule based automation","API data integration","spreadsheet updates"],"target_audience":["logistics managers","environmental monitors"]}


name: Automated Email Assistant for Suppliers using OpenAI and Google Sheets
author_name: Omar Hdez
author_username: omarhdez
categories: []
created_at: 2025-05-15T06:22:30.568Z
updated_at: 2025-05-15T06:22:30.568Z
url: https://n8n.io/workflows/4067
scraped_at: 2026-05-02 08:04:50
metadata_generated_at: 2026-05-02 08:36:20
description:
  Automated Email Assistant for Busy Professionals

  This assistant is designed for people who don't have time to write and send emails to suppliers. With just one request, it drafts and sends clear, professional messages automatically.

  How It Works
  The user makes a request (e.g., “Send an email to my fruit supplier asking for a quote on 1 crate of mangoes.”).

  Workflow:

  The AI agent searches for the supplier in a Google Sheets database.

  It automatically drafts the email using OpenAI (with the tone and style you define).
   
  It sends the email using your Gmail account connected through n8n.
  This assistant uses:

  Google Sheets to manage your suppliers (name and email).

  OpenAI to generate clear, natural messages.
    
  MCP (client-server logic) to handle request processing.
    
  Gmail as the sending channel for automated emails.
  Setup Instructions

  Create a Google Sheets document with the supplier name and email, like this:

  |Supplier name|Email|
  |-|-|
  |Proveedor de frutas Alvarez|fruteriaalvarez@alvarez.com|
   
  Connect your Google Sheets and Gmail accounts within n8n.
   
  Add your OpenAI API key.

  Test the automation by chatting with the integrated assistant.
  It will generate and send the email automatically to the indicated supplier.

  Requirements
  OpenAI API key to generate email content.
  Gmail account connected via OAuth2.
  Google Sheets document with your supplier database.
  n8n instance (cloud or self-hosted).

  Customization

  Adjust the OpenAI prompt to make the email tone more formal, casual, or technical.

  Add custom fields to your supplier sheet (location, notes, special conditions).

  Replace Google Sheets with a real database like Supabase or PostgreSQL for greater scalability.

nodes_used:
  ["@n8n/n8n-nodes-langchain.mcpTrigger","n8n-nodes-base.gmailTool","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.chatTrigger","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.memoryBufferWindow","@n8n/n8n-nodes-langchain.mcpClientTool","@n8n/n8n-nodes-langchain.toolThink","n8n-nodes-base.googleSheetsTool"]

workflow_json_compressed:
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metadata_json:
  {"categories":["AI/ML","Communication","Data Processing","Administration","Operations"],"complexity":"medium","use_cases":["Drafting and sending supplier emails automatically","Querying supplier databases via Google Sheets","Managing vendor communication without manual input"],"estimated_setup_minutes":15,"required_services":["OpenAI","Google Sheets"],"key_features":["Automated email generation","AI-driven content personalization","Database lookups for contact information","One-click email initiation"],"target_audience":["busy professionals","business owners","admin assistants"]}


name: Find Reddit Prospects & Generate Personalized Responses with Llama3 AI and Google Sheets
author_name: Dhrumil Barot
author_username: barotdhrumil21
categories: []
created_at: 2025-05-15T10:00:08.976Z
updated_at: 2025-05-15T10:00:08.976Z
url: https://n8n.io/workflows/4068
scraped_at: 2026-05-02 08:04:51
metadata_generated_at: 2026-05-02 08:36:20
description:
  Turn Reddit into Your Most Powerful Lead Generation Channel

  Discover hot prospects on Reddit who are actively discussing problems your product can solve - without spending hours manually searching and responding. This intelligent workflow automatically finds relevant conversations, analyzes intent with Llama3 AI, and crafts personalized responses that drive conversions.

  🔍 Automated Prospect Discovery
  Stop wasting time manually searching Reddit. Let AI find people who genuinely need your solution - while you focus on higher-value tasks. The workflow monitors target subreddits 24/7, ensuring you never miss a potential lead.

  🧠 Intelligent Relevance Filtering
  Not all mentions are quality leads. Our sophisticated Llama3 AI engine analyzes post content, sentiment, and intent to identify true business opportunities. Say goodbye to false positives and low-quality interactions.

  💬 Personalized Response Generation
  Generic outreach gets ignored. This workflow crafts individualized responses that reference specific pain points from each post, positioning your solution as the perfect answer to their problem - dramatically increasing engagement rates.

  📊 Complete Activity Tracking
  Every interaction is automatically logged in Google Sheets, creating a comprehensive database of your Reddit prospecting activities. Track which posts received responses, measure engagement, and refine your targeting over time.

  🔄 Set It and Forget It
  Once configured, the entire process runs autonomously. No more daily Reddit searches or manual outreach - just check your dashboard to see new prospects and conversations.

  Perfect For:
  SaaS businesses targeting specific use cases
  Consultants and agencies looking for clients with specific problems
  Product companies monitoring customer pain points
  Support teams finding users who need help

  Technical Requirements:
  Reddit API credentials
  Ollama with Llama3 model
  Google account for tracking

  Get started today and transform Reddit from a time-sink into your most efficient lead generation channel!

nodes_used:
  ["n8n-nodes-base.manualTrigger","n8n-nodes-base.googleSheets","n8n-nodes-base.googleSheets","n8n-nodes-base.googleSheets","n8n-nodes-base.reddit","n8n-nodes-base.if","n8n-nodes-base.code","@n8n/n8n-nodes-langchain.lmChatOllama","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.splitInBatches","n8n-nodes-base.code","n8n-nodes-base.set","n8n-nodes-base.reddit","n8n-nodes-base.stickyNote"]

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metadata_json:
  {"categories":["Marketing","Data Processing","AI/ML"],"complexity":"medium","use_cases":["automated prospect discovery","personalized response generation","reddit lead mining","sentiment analysis","conversation intent detection"],"estimated_setup_minutes":30,"required_services":["Reddit API","Google Sheets","Llama3/LLM"],"key_features":["conversational intent detection","personalized outreach","batch processing","AI-powered content generation","automated social listening"],"target_audience":["marketers","sales representatives","growth hackers"]}


name: Complete Shopify to Odoo Integration: Sync Orders, Products & Customers
author_name: Evozard
author_username: evozardconsulting
categories: []
created_at: 2025-05-15T10:58:11.724Z
updated_at: 2025-05-15T10:58:11.724Z
url: https://n8n.io/workflows/4069
scraped_at: 2026-05-02 08:04:51
metadata_generated_at: 2026-05-02 08:36:20
description:
  This workflow functions like the integration of Shopify products with Odoo products, Shopify customers with Odoo customers, and paid Shopify orders with Odoo sales orders containing multiple products.
   
  Trigger (Shopify – Order Created & Paid): The workflow starts when a new order is created in Shopify and its status is marked as paid.
   
  Loop Through Each Line Item in the Order:
      For each product in the order:
          Check if Product Exists in Odoo (via Internal Reference/Default Code)
  	    If the product exists, proceed.
  	    If the product does not exist, create it in Odoo with the following details:
  	        Product Name
  		Description
  		Price
  		Internal Reference (Default Code)
   
  Check if Customer Contact Exists in Odoo (via Email):
      If the contact exists, proceed.
      If the contact does not exist, create a new contact in Odoo with:
          Full Name
          Email Address
          Phone Number
          Shipping or Billing Address (as available)
   
  Create a Sale Order in Odoo:
      Create a new Sale Order in Odoo using:
          The matched or newly created Customer Contact
          The matched or newly created All the Products in the Shopify order (with correct quantities and pricing)
      Each Shopify product in the order is matched to the corresponding Odoo product using the Internal Reference field
      
  Integration Setup References:
   
      Shopify Integration Setup:
      https://docs.n8n.io/integrations/builtin/credentials/shopify/
   
      Odoo Integration Setup:
      https://docs.n8n.io/integrations/builtin/credentials/odoo/

nodes_used:
  ["n8n-nodes-base.shopifyTrigger","n8n-nodes-base.odoo","n8n-nodes-base.code","n8n-nodes-base.splitOut","n8n-nodes-base.odoo","n8n-nodes-base.odoo","n8n-nodes-base.code","n8n-nodes-base.odoo","n8n-nodes-base.filter","n8n-nodes-base.odoo","n8n-nodes-base.odoo","n8n-nodes-base.filter","n8n-nodes-base.code","n8n-nodes-base.splitOut","n8n-nodes-base.code","n8n-nodes-base.odoo","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.odoo"]

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metadata_json:
  {"categories":["Data Processing","DevOps","E-commerce"],"complexity":"medium","use_cases":["automate e-commerce order syncing","synchronize product inventory","manage customer data"],"estimated_setup_minutes":30,"required_services":["Shopify","Odoo"],"key_features":["real-time order synchronization","bidirectional data mapping","order status tracking"],"target_audience":["e-commerce managers","business analysts","sysadmins"]}


name: Linking NocoDB Records via API 🔗
author_name: Max aka Mosheh
author_username: aiwithapex
categories: []
created_at: 2025-05-15T13:39:15.959Z
updated_at: 2025-05-15T13:39:15.959Z
url: https://n8n.io/workflows/4070
scraped_at: 2026-05-02 08:04:51
metadata_generated_at: 2026-05-02 08:36:20
description:
  How it works:
  The n8n flow grabs the needed IDs, fetches the current links, adds your new one, and sends a single HTTP request to NocoDB to update the record’s linked entries.

  Set up steps:

  Plan for 10 minutes setup if you’re already running n8n and NocoDB.
  You’ll need to copy/paste table IDs, set up your HTTP node, and test once.
  No coding, just copy IDs.

nodes_used:
  ["n8n-nodes-base.manualTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.nocoDb","n8n-nodes-base.set","n8n-nodes-base.httpRequest","n8n-nodes-base.nocoDb","n8n-nodes-base.httpRequest","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

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metadata_json:
  {"categories":["Data Processing"],"complexity":"medium","use_cases":["Manage database connections","Update relationship records","Bulk link management"],"estimated_setup_minutes":10,"required_services":["NocoDB"],"key_features":["Fetch linked records","Modify associations","Single HTTP update request"],"target_audience":["Database administrators","Data engineers","Operations staff"]}


name: AI-Powered RAG Q&A Chatbot with OpenAI, Google Sheets, Glide & Supabase
author_name: Sam Yassine
author_username: samyassine
categories: []
created_at: 2025-05-15T14:00:56.738Z
updated_at: 2025-05-15T14:00:56.738Z
url: https://n8n.io/workflows/4071
scraped_at: 2026-05-02 08:04:50
metadata_generated_at: 2026-05-02 08:36:20
description:
  Automate AI-Powered RAG System with Contextual Q&A, Google Sheets Integration, and Glide Frontend—Powered by n8n, OpenAI, Supabase, and Google Apps Script.

  Tools & Services Used
  Glide (Frontend for user interactions)

  Google Sheets (Stores questions and answers)

  Google Apps Script (Forms + media upload handling)

  OpenAI (Embeddings + GPT-4 to rank and generate answers)

  Supabase (Optional for image hosting)

  n8n (Automation logic and backend glue)

  Workflow Overview
  This automation performs the following steps:

  Trigger: Webhook receives a user question from a Glide frontend.

  Fetch Data: Retrieves Q&A entries (and optionally, image URLs) from a connected Google Sheet.

  Rank Relevance:

  OpenAI Embeddings rank the relevance of stored questions to the new input.

  Top matches are passed to a GPT-4 prompt for answer generation.

  Generate Answer:

  GPT-4 creates a contextual answer using the best match.

  Optional: Includes media URL if attached to the matched answer.

  Response: Sends the formatted answer back to Glide frontend (text + optional image).

  Prerequisites
  Active accounts and API keys for:

  OpenAI (API key with GPT-4 and embedding access)

  Google Sheets (linked via Service Account or OAuth2 credentials)

  Glide App (with a form to submit questions)

  Supabase (optional, if hosting user-uploaded media)

  n8n Self-hosted (for community nodes and webhook access)

  How to Use This Template
  Step 1: Import the Template
  Upload the provided JSON into your self-hosted n8n instance.

  Requires installation of the Community Node: @n8n/n8n-nodes-openai-embeddings

  Step 2: Configure Credentials
  Webhook Trigger: Replace the Glide webhook URL with your actual endpoint from your app.

  Google Sheets Node: Set the spreadsheet ID and worksheet name to fetch your Q&A dataset.

  OpenAI Nodes:

  Insert your OpenAI API key.

  Confirm that both text-embedding-ada-002 (or similar) and gpt-4 are available.

  Supabase or Apps Script (Optional): Ensure image links are correctly formed in the Sheet.

  Step 3: Customize Prompts and Thresholds
  Update the OpenAI ranking prompt or similarity threshold in the Function or Code node.

  Tailor GPT-4 prompts to return concise or detailed answers based on your use case.

  Initial Test Run
  Simulate a Question:
  Trigger the Glide form with a sample question.

  Check n8n logs for:

  Matching score/ranking success

  Correct retrieval from Sheets

  GPT-4 answer generation

  Image URL handling (if enabled)

  Production Prep
  Add error-handling nodes for cases when Sheets are empty or GPT-4 fails.

  Set up logging via Google Sheets, Supabase, or external database.

  Rate-limit or debounce requests from Glide if needed.

  Use Cases
  Customer Support Portals: Offer instant Q&A with your business data.

  Internal Knowledgebase: Employees can query training manuals and SOPs.

  AI Concierge: Combine structured answers with friendly tone for guest interactions.

  Disclaimer

  Validate Glide form inputs before full deployment.

  Ensure your OpenAI and Google Sheets usage stays within quota limits.

nodes_used:
  ["n8n-nodes-base.webhook","n8n-nodes-base.googleCalendar","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.chainLlm","n8n-nodes-base.webhook","@n8n/n8n-nodes-langchain.vectorStoreQdrant","@n8n/n8n-nodes-langchain.embeddingsOpenAi","@n8n/n8n-nodes-langchain.toolVectorStore","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.webhook","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.respondToWebhook","n8n-nodes-base.httpRequest","n8n-nodes-base.respondToWebhook","@n8n/n8n-nodes-langchain.outputParserStructured","n8n-nodes-base.respondToWebhook","n8n-nodes-base.stickyNote","n8n-nodes-base.manualTrigger","@n8n/n8n-nodes-langchain.vectorStoreQdrant","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.googleDrive","n8n-nodes-base.googleDrive","@n8n/n8n-nodes-langchain.embeddingsOpenAi","@n8n/n8n-nodes-langchain.documentDefaultDataLoader","@n8n/n8n-nodes-langchain.textSplitterTokenSplitter","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

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metadata_json:
  {"categories":["AI/ML","Communication","Developer Tools"],"complexity":"complex","use_cases":["Build custom chatbots","Implement RAG systems","Create Q&A knowledge bases"],"estimated_setup_minutes":30,"required_services":["OpenAI","Google Sheets","Glide Apps","Supabase","Vector Store DB"],"key_features":["Retrieval Augmented Generation","Contextual Q&A responses","No-code frontend integration","Vector search implementation"],"target_audience":["Developers","Product Managers","AI Enthusiasts"]}


name: Enrich Seller Data with Email & Domain Lookup using Bright Data & Google Search
author_name: Cyril Nicko Gaspar
author_username: cngaspar
categories: []
created_at: 2025-05-15T14:35:17.827Z
updated_at: 2025-05-15T14:35:17.827Z
url: https://n8n.io/workflows/4072
scraped_at: 2026-05-02 08:04:51
metadata_generated_at: 2026-05-02 08:36:20
description:
  🔍 Email Lookup with Google Search from Postgres Database

  This N8N workflow is designed to enrich seller data stored in a Postgres database by performing automated Google search lookups. It uses Bright Data's Web Unlocker to bypass search result restrictions and the HTML Extract node to parse and extract relevant information from webpages.

  The main purpose of this workflow is to discover missing contact details, company domains, and secondary emails for businesses or sellers based on existing database entries.

  🎯 Problem This Workflow Solves

  Manually searching for missing seller or business details—like secondary emails, websites, or domain names—can be time-consuming and inefficient, especially for large datasets.
  This workflow automates the search and data enrichment process, significantly reducing manual effort while improving the quality and completeness of your seller database.

  ✅ Prerequisites

  Before using this template, make sure the following requirements are met:

  ✔️ A Bright Data account with access to the Web Unlocker or Amazon Scraper API
  ✔️ A valid Bright Data API key
  ✔️ An active PostgreSQL database with seller data
  ✔️ N8N self-hosted instance (recommended for using community nodes like n8n-nodes-brightdata)
  ✔️ Installed n8n-nodes-brightdata package (custom node for Bright Data integration)

  ⚙️ Setup Instructions

  Step 1: Prepare Your Postgres Table

  Create a table in Postgres with the following structure (you can adjust field names if needed):

  CREATE TABLE sellers (
    seller_id SERIAL PRIMARY KEY,
    seller_name TEXT,
    primary_email TEXT,
    company_info TEXT,
    trade_name TEXT,
    business_address TEXT,
    coc_number TEXT,
    vat_number TEXT,
    commercial_register TEXT,
    secondary_email TEXT,
    domain TEXT,
    seller_slug TEXT,
    source TEXT
  );

  Step 2: Setup Web Unlocker on Bright Data

  Go to your Bright Data dashboard.
  Navigate to Proxies & Scraping → Web Unlocker.
  Create a new zone, selecting Web Unlocker API under Scraping Solutions.
  Whitelist your server IP if required.

  Step 3: Generate API Key

  In the Bright Data dashboard, go to the API section.
  Generate a new API key.
  In N8N, create HTTP Request Credentials using Bearer Authentication with the API key.

  Step 4: Install the Bright Data Node in N8N

  In your N8N self-hosted instance, go to Settings → Community Nodes.
  Search and install n8n-nodes-brightdata.

  🔄 Workflow Functionality

  🔁 Trigger: Can be set to run on a schedule (e.g., daily) or manually.
  📥 Read: Fetches seller records from the Postgres table.
  🌐 Search: Uses Bright Data to perform a Google search based on seller_name, company_info, or trade_name.
  🧾 Extract: Parses the HTML content using the HTML Extract node to identify potential websites and email addresses.
  📝 Update: Writes enriched data (like domain or secondary_email) back to the Postgres table.

  💡 Use Cases

  Lead enrichment for e-commerce sellers
  Domain and contact info discovery for B2B databases
  Email and web domain verification for CRM systems
  Market research automation

  🛠️ Customization Tips

  You can enhance the parsing logic in the HTML Extract node to look for phone numbers, LinkedIn profiles, or social media links.
  Modify the search query logic to include additional parameters like location or industry for more refined results.
  Integrate additional APIs (e.g., Hunter.io, Clearbit) for email validation or social profile enrichment.
  Add filtering to skip entries that already have domain or secondary_email.

nodes_used:
  ["n8n-nodes-base.manualTrigger","n8n-nodes-base.postgres","n8n-nodes-base.wait","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.postgres","n8n-nodes-base.switch","n8n-nodes-base.code","n8n-nodes-base.postgres","n8n-nodes-base.switch","n8n-nodes-base.postgres","n8n-nodes-base.wait","n8n-nodes-base.set","n8n-nodes-base.splitInBatches","n8n-nodes-brightdata.brightData","n8n-nodes-brightdata.brightData","n8n-nodes-base.html","n8n-nodes-base.html","n8n-nodes-base.splitOut","n8n-nodes-base.filter","n8n-nodes-base.aggregate","n8n-nodes-base.code","n8n-nodes-base.splitOut","n8n-nodes-base.filter","n8n-nodes-base.if","n8n-nodes-base.aggregate","n8n-nodes-base.stickyNote","n8n-nodes-base.if","n8n-nodes-base.code","n8n-nodes-base.postgres","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 6756 characters]

metadata_json:
  {"categories":["Data Processing","DevOps"],"complexity":"medium","use_cases":["enrich database records","discover contact details","find company domains","extract secondary emails"],"estimated_setup_minutes":45,"required_services":["Postgres","Bright Data"],"key_features":["automated web scraping","bypass search restrictions","sequential data enrichment","database persistence"],"target_audience":["data analysts","operations","researchers"]}


name: Automate GitHub PR Linting with Google Gemini AI and Auto-Fix PRs
author_name: Adam Bertram
author_username: adbertram
categories: []
created_at: 2025-05-15T15:00:58.877Z
updated_at: 2025-05-15T15:00:58.877Z
url: https://n8n.io/workflows/4073
scraped_at: 2026-05-02 08:04:51
metadata_generated_at: 2026-05-02 08:36:21
description:
  LintGuardian: Automated PR Linting with n8n & AI

  What It Does

  LintGuardian is an n8n workflow template that automates code quality enforcement for GitHub repositories. When a pull request is created, the workflow automatically analyzes the changed files, identifies linting issues, fixes them, and submits a new PR with corrections. This eliminates manual code style reviews, reduces back-and-forth comments, and lets your team focus on functionality rather than formatting.

  How It Works

  The workflow is triggered by a GitHub webhook when a PR is created. It fetches all changed files from the PR using the GitHub API, processes them through an AI-powered linting service (Google Gemini), and automatically generates fixes. The AI agent then creates a new branch with the corrected files and submits a "linting fixes" PR against the original branch. Developers can review and merge these fixes with a single click, keeping code consistently formatted with minimal effort.

  Prerequisites

  To use this template, you'll need:

  n8n instance: Either self-hosted or using n8n.cloud
  GitHub repository: Where you want to enforce linting standards
  GitHub Personal Access Token: With permissions for repo access (repo, workflow, admin:repo_hook)
  Google AI API Key: For the Gemini language model that powers the linting analysis
  GitHub webhook: Configured to send PR creation events to your n8n instance

  Setup Instructions

  Import the template into your n8n instance
  Configure credentials:
     Add your GitHub Personal Access Token under Credentials → GitHub API
     Add your Google AI API key under Credentials → Google Gemini API
  Update repository information:
     Locate the "Set Common Fields" code node at the beginning of the workflow
     Change the gitHubRepoName and gitHubOrgName values to match your repository
        const commonFields = {
       'gitHubRepoName': 'your-repo-name',
       'gitHubOrgName': 'your-org-name'
     }
     Configure the webhook:
   Create a file named .github/workflows/lint-guardian.yml in your repository replacing the Trigger n8n Workflow step with your webhook:
            name: Lint Guardian
       
       on:
         pull_request:
           types: [opened, synchronize]
       
       jobs:
         trigger-linting:
           runs-on: ubuntu-latest
           steps:
             name: Trigger n8n Workflow
               uses: fjogeleit/http-request-action@v1
               with:
                 url: 'https://your-n8n-instance.com/webhook/1da5a6e1-9453-4a65-bbac-a1fed633f6ad'
                 method: 'POST'
                 contentType: 'application/json'
                 data: |
                   {
                     "pull_request_number": ${{ github.event.pull_request.number }},
                     "repository": "${{ github.repository }}",
                     "branch": "${{ github.event.pull_request.head.ref }}",
                     "base_branch": "${{ github.event.pull_request.base.ref }}"
                   }
                 preventFailureOnNoResponse: true
       Customize linting rules (optional):
     Modify the AI Agent's system message to specify your team's linting preferences
     Adjust file handling if you have specific file types to focus on or ignore

  Security Considerations

  When creating your GitHub Personal Access Token, remember to:
  Choose the minimal permissions needed (repo, workflow, admin:repo_hook)
  Set an appropriate expiration date
  Treat your token like a password and store it securely
  Consider using GitHub's fine-grained personal access tokens for more limited scope

  As GitHub documentation notes: "Personal access tokens are like passwords, and they share the same inherent security risks."

  Extending the Template

  You can enhance this workflow by:
  Adding Slack notifications when linting fixes are submitted
  Creating custom linting rules specific to your team's needs
  Expanding it to handle different types of code quality checks
  Adding approval steps for more controlled environments

  This template provides an excellent starting point that you can customize to fit your team's exact workflow and code style requirements.

nodes_used:
  ["n8n-nodes-base.webhook","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.respondToWebhook","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.convertToFile","n8n-nodes-base.extractFromFile","n8n-nodes-base.set","n8n-nodes-base.aggregate","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequestTool","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","n8n-nodes-base.code"]

workflow_json_compressed:
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metadata_json:
  {"categories":["DevOps","AI/ML"],"complexity":"medium","use_cases":["automate code linting checks","fix git repositories automatically","enforce code style standards"],"estimated_setup_minutes":10,"required_services":["GitHub","Google Gemini"],"key_features":["real-time PR analysis","auto-fix linting issues","submit corrected PRs"],"target_audience":["developers","devops engineers","tech leads"]}


