# templates

name: Auto-Publish Web Articles as Social Posts for X, LinkedIn, Reddit & Threads with Gemini AI
author_name: Juan Carlos Cavero Gracia
author_username: carlosgracia
categories: []
created_at: 2025-06-22T12:59:23.111Z
updated_at: 2025-06-22T12:59:23.111Z
url: https://n8n.io/workflows/5128
scraped_at: 2026-05-02 08:04:48
metadata_generated_at: 2026-05-02 08:36:20
description:
  This workflow contains community nodes that are only compatible with the self-hosted version of n8n. 

  Description
  This automation template is designed for content curators, marketers, and anyone looking to supercharge their content sharing strategy. It transforms any web article, blog post, or news link into a series of platform-specific social media posts, generated by AI. It also captures a live screenshot of the webpage to use as the post image, automating the entire process of publishing them across X (Twitter), LinkedIn, Threads, and Reddit.

  Note: The default example is configured to share n8n templates, but this workflow can promote any web page, article, or news story. Just change the URL! The upload-post node only works for self-hosted n8n instances, but you can use the standard http node for uploading the content*

  Who Is This For?
  Content Curators & Marketers:** Effortlessly share valuable industry news and articles with tailored messages and visuals for each audience.
  Social Media Managers:** Keep your social feeds consistently active with relevant, high-quality content without the manual overhead.
  Community Builders & Brand Evangelists:** Quickly disseminate product updates, tutorials, and blog posts to your community on all relevant platforms.
  Professionals & Thought Leaders:** Build your personal brand by easily sharing insightful articles with automated visuals, adding your unique perspective.

  What Problem Does This Workflow Solve?
  Sharing a single piece of content across multiple social platforms is tedious. You need to manually write unique posts, create visuals, and then publish everything. This workflow addresses these challenges by:
  Automating Content Creation:** Uses a powerful AI agent (Google Gemini) to read any URL and write compelling, unique posts for each social network.
  Generating Visuals Automatically:** Captures a high-quality screenshot of the source webpage to use as a visually appealing image in your posts, increasing engagement.
  Ensuring Platform-Specific Tone:** The AI is instructed to generate professional posts for LinkedIn, concise threads for X, conversational updates for Threads, and community-focused posts for Reddit.
  One-Click Distribution:** Takes a single URL as input and handles the entire content creation and sharing process across multiple platforms automatically.

  How It Works
  Input a URL: In the "Set Input Data" node, simply paste the URL of the article or page you want to share.
  AI Analysis & Generation: The workflow sends the URL to the AI agent, which scrapes the content and generates four distinct, ready-to-publish posts.
  Screenshot Generation: At the same time, it uses the ScreenshotOne service to capture a high-quality image of the provided URL.
  Cross-Platform Publishing: The generated content and the screenshot are automatically sent to the corresponding nodes to be posted on X, LinkedIn, and Threads, while the text-only version is sent to Reddit.

  Setup
  AI Model Credentials: Add your Google Gemini API key to the Google Gemini Chat Model node to power the AI agent.
  Screenshot Service (ScreenshotOne): The workflow uses ScreenshotOne to generate images for your posts.
      Create a free account at screenshotone.com to get your own API key. The free plan includes 100 screenshots per month.
      In the Upload Post X, Upload Post LinkedIn, and Upload Post Threads nodes, go to the Photos parameter (under Additional Fields) and replace the existing access_key in the URL with your own.
  Upload-Post Account: This workflow uses upload-post.com for multi-platform posting.
      Create a free account at upload-post.com to get your API Token and User ID.
      Add the credentials in the Upload Post X, Upload Post LinkedIn, and Upload Post Threads nodes.
  Reddit Credentials: Connect your Reddit account using OAuth2 in the Reddit node to enable posting.
  Customize the AI: (Optional) Edit the prompt in the Social Media Agent node to match your content. The default prompt is optimized for sharing n8n templates, but you can easily adapt it for any topic to fit your brand's voice and style.

  Requirements
  Accounts:** n8n, Google (for Gemini API), ScreenshotOne, upload-post.com, Reddit.
  API Keys & Credentials:** Google Gemini API Key, ScreenshotOne API Key, Upload-post.com API Token & User ID, Reddit OAuth2 credentials.

  Use this template to become a content-sharing powerhouse, saving hours of work while increasing your reach and engagement across the web.

nodes_used:
  ["n8n-nodes-base.manualTrigger","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","n8n-nodes-base.httpRequestTool","@n8n/n8n-nodes-langchain.outputParserStructured","n8n-nodes-upload-post.uploadPost","n8n-nodes-upload-post.uploadPost","n8n-nodes-upload-post.uploadPost","n8n-nodes-base.reddit","n8n-nodes-base.wait","n8n-nodes-base.if"]

workflow_json_compressed:
  [encoded data, 11296 characters]

metadata_json:
  {"categories":["AI/ML","Marketing"],"complexity":"medium","use_cases":["Social media posting","Content curation","Screenshot automation"],"estimated_setup_minutes":30,"required_services":["Google Gemini","Reddit","LinkedIn","X","Threads","Unsplash"],"key_features":["AI content summarization","Platform-specific formatting","Automated screenshot capture","Multi-platform publishing"],"target_audience":["Marketers","Content curators","Social media managers"]}


name: AI-Powered Accounting Reports from Sabre EDI with GPT-4 and Pinecone RAG
author_name: Mohan Gopal
author_username: mohan
categories: []
created_at: 2025-06-22T16:45:54.084Z
updated_at: 2025-06-22T16:45:54.084Z
url: https://n8n.io/workflows/5130
scraped_at: 2026-05-02 08:04:49
metadata_generated_at: 2026-05-02 08:36:20
description:
  This workflow automates the process of reading EDI files generated by Sabre, parsing them using an AI Agent, and producing structured accounting reports like:

  📌 Accounts Receivable (AR) Summary
  📌 Tax and Surcharges Report

  It also uses Retrieval-Augmented Generation (RAG) to vectorize the Sabre Interface User Record (IUR)—a 154-page technical document—so that the AI agent can reference it when clarification is required while generating reports.

  ⚙️ Tools & Integrations Used
  Component:Tool/Service:Purpose:Workflow Engine:n8n:Automation & orchestration
  LLM Model:OpenAI GPT-4 / Chat Model:Natural language understanding and parsing
  Embeddings Model:OpenAI Embeddings:Convert text into semantic vector format
  Vector Database:Pinecone:Store and retrieve document chunks semantically
  Storage:Google Drive:Source of raw EDI text files and PDF documentation
  DataLoader + Splitter:n8n Node + Recursive Splitter:Loads and prepares documents for embedding
  AI Agents:n8n AI Agent Node:Runs context-aware prompts and parses reports

  🧱 Workflow Breakdown
  🧠 1. Vectorizing the Sabre IUR Document (RAG Setup)
  📘 Objective: Enable the AI Agent to refer to the IUR document (154 pages) for detailed explanations of EDI terms, formats, and rules.

  Flow Steps:

  Google Drive Search + Download – Find and pull the IUR PDF file.

  Default Data Loader – Load the file and preprocess it for semantic splitting.

  Recursive Character Splitter – Break down large pages into meaningful chunks.

  OpenAI Embeddings – Vectorize each chunk.

  Pinecone Vector Store – Save into a Pinecone namespace for future retrieval.

  ✅ Result: The IUR is now searchable via semantic queries from the AI Agent.

  📁 2. Reading and Extracting Data from EDI Files
  📘 Objective: Parse raw EDI files for financial records and summaries.

  Flow Steps:

  Trigger – Manual or scheduled execution of the workflow.

  Google Drive Search – Finds all new .edi or .txt files.

  Download File Contents – Loads content of each file into memory.

  Extract from File – Raw text extraction.

  📊 3. Report Generation Using AI Agents
  📘 Objective: AI Agents parse the extracted data to generate structured accounting reports.

  a. Accounts Receivable Report Agent
  The extracted text is passed to an AI Agent.

  Model is connected to:

  OpenAI Chat Model (LLM)

  Pinecone Vector DB (IUR reference)

  Outputs a structured AR Summary Report.

  b. Tax and Surcharges Report Agent
  Same steps as above.

  Prompts adjusted to extract tax, fees, surcharges, and amounts.

  ✅ Output Format: Can be mapped to columns and inserted into a Google Sheet or exported as a CSV/JSON.

  📑 Sample Reports You Can Build
  Already implemented:

  ✅ Accounts Receivable (AR) Summary Report

  ✅ Tax and Surcharges Report

  Can be extended to:
  Accounts Payable (AP)
  Passenger Revenue
  Daily Sales
  Commission Report
  Net Profit Margin (if supplier cost + commission is available)

  💡 Key Advantages
  ✅ No-code automation with n8n

  ✅ Semantic reasoning using AI + Vector DB (RAG)

  ✅ Can work with various Sabre outputs without manual parsing

  ✅ Modular: Easy to add new report types

  ✅ Cloud-integrated (Drive, Pinecone, OpenAI)

  🧪 Potential Improvements
  Area	Suggestions
  Testing	Add a “Preview” step to validate extracted data before writing
  Scalability	Batch mode + Google Sheet batching for multiple reports
  Audit Trail	Log every file name, timestamp, report type in a Google Sheet
  Notification	Send Slack/Email when a new report is generated
  Multi-model support	Add Claude/Gemini fallback if OpenAI usage limit is hit

nodes_used:
  ["n8n-nodes-base.manualTrigger","@n8n/n8n-nodes-langchain.vectorStorePinecone","@n8n/n8n-nodes-langchain.embeddingsOpenAi","@n8n/n8n-nodes-langchain.documentDefaultDataLoader","@n8n/n8n-nodes-langchain.textSplitterRecursiveCharacterTextSplitter","n8n-nodes-base.googleDrive","n8n-nodes-base.googleDrive","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.vectorStorePinecone","@n8n/n8n-nodes-langchain.embeddingsOpenAi","n8n-nodes-base.extractFromFile","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.stickyNote","n8n-nodes-base.googleDrive","n8n-nodes-base.googleDrive","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.vectorStorePinecone","@n8n/n8n-nodes-langchain.embeddingsOpenAi","@n8n/n8n-nodes-langchain.agent"]

workflow_json_compressed:
  [encoded data, 4152 characters]

metadata_json:
  {"categories":["Accounting","Data Processing","AI/ML","Enterprise Automation"],"complexity":"medium","use_cases":["Extract structured data from EDI files","Generate accounting documentation","Apply RAG for technical clarification"],"estimated_setup_minutes":60,"required_services":["Sabre API","GPT-4","Pinecone","Google Drive"],"key_features":["AI parsing of EDI transactions","RAG-powered technical document referencing","Automated report generation","Document embedding and storage"],"target_audience":["accounting professionals","data analysts","accounting managers"]}


name: Manage GoHighLevel CRM with Conversational AI Assistant and GPT-4o
author_name: Abdellah Homrani
author_username: adamcrafts
categories: []
created_at: 2025-06-22T19:08:36.160Z
updated_at: 2025-06-22T19:08:36.160Z
url: https://n8n.io/workflows/5131
scraped_at: 2026-05-02 08:04:50
metadata_generated_at: 2026-05-02 08:36:21
description:
  🌟 Your Conversational GoHighLevel CRM Assistant: Instantly manage contacts, deals, and tasks in GoHighLevel using simple chat commands.

  🚀 Overview

  This automation sets up an intelligent AI assistant directly connected to your GoHighLevel CRM. Instead of clicking through menus and forms, you can now manage your entire sales pipeline through a simple chat conversation. It's like having a dedicated, 24/7 sales operations expert on your team, ready to act on your commands instantly.

  😩 The Problem

  Managing a powerful CRM like GoHighLevel is essential, but it can be incredibly time-consuming. You're constantly jumping between screens to add a new contact after a call, update a deal's status, create a follow-up task, or check calendar availability. Each small action requires navigating different menus, filling out multiple fields, and saving your work. This constant context-switching kills productivity, creates opportunities for human error, and slows down your entire sales cycle.

  ✨ The Solution

  This workflow acts as your personal "automated employee," transforming your GoHighLevel experience by giving you an AI-powered conversational assistant. Now, you can simply tell the AI what you need in plain English, and it gets done.

  When you send a message like, "Create a new contact for John Doe at john@email.com" the automation instantly captures the information and creates the contact. Ask it to "Find all open deals for ABC Corp" and it will search your pipeline. Need to schedule a follow-up? Just say "Create a task to call John Doe next Tuesday." 📅 This assistant handles everything from contact creation and opportunity management to task setting and appointment booking, turning tedious CRM admin into a fast and simple conversation.

  ⚙️ Simple Setup

  This workflow is a pre-built blueprint, designed to be up and running in minutes!

  Upload:** Simply upload the provided JSON file into your n8n instance.
  Connect:** Connect your app credentials (e.g., your GoHighLevel and OpenAI accounts). The workflow will show you exactly where.
  Activate:** Turn the workflow on, and it's ready to go! Let your new automated employee get to work.

  🌐 Explore more workflows
  ❤️ Buy more workflows at: adamcrafts
  🦾 Custom workflows at: adamcrafts@cloudysoftwares.com
  adamaicrafts@gmail.com


  &gt; Build once, customize endlessly, and scale your video content like never before.

nodes_used:
  ["@n8n/n8n-nodes-langchain.memoryBufferWindow","n8n-nodes-base.stickyNote","n8n-nodes-base.highLevelTool","n8n-nodes-base.stickyNote","n8n-nodes-base.highLevelTool","n8n-nodes-base.highLevelTool","n8n-nodes-base.stickyNote","n8n-nodes-base.highLevelTool","n8n-nodes-base.highLevelTool","n8n-nodes-base.highLevelTool","n8n-nodes-base.highLevelTool","n8n-nodes-base.highLevelTool","n8n-nodes-base.highLevelTool","n8n-nodes-base.highLevelTool","n8n-nodes-base.highLevelTool","n8n-nodes-base.highLevelTool","n8n-nodes-base.stickyNote","n8n-nodes-base.highLevelTool","n8n-nodes-base.highLevelTool","@n8n/n8n-nodes-langchain.chatTrigger","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 4856 characters]

metadata_json:
  {"categories":["CRM","Artificial Intelligence","Business Management"],"complexity":"medium","use_cases":["Manage contacts via chat","Handle sales pipeline","Perform CRM tasks","Conversational database management"],"estimated_setup_minutes":25,"required_services":["GoHighLevel","OpenAI","Twilio (implied for chat)"],"key_features":["Chat-based interface","GPT-4o integration","Real-time CRM updates","Natural language commands","Task automation"],"target_audience":["Sales Managers","CRM Administrators","Small Business Owners"]}


name: Smart Lead Outreach with Explorium MCP Using Google Sheets and Telegram
author_name: David Olusola
author_username: dae221
categories: []
created_at: 2025-06-22T21:30:08.367Z
updated_at: 2025-06-22T21:30:08.367Z
url: https://n8n.io/workflows/5133
scraped_at: 2026-05-02 08:04:49
metadata_generated_at: 2026-05-02 08:36:21
description:
  🚀 Smart Outreach: Auto-Personalized Lead Sequences

  🧠 What It Does

  This n8n workflow turns your Telegram bot into an AI-powered B2B lead enrichment and outreach engine.

  It uses Explorium MCP's premium business data, combined with GPT-4 intelligence, to deliver:

  Enriched lead profiles (person or company)
  AI-personalized 4-step cold email sequences
  Real-time interaction via Telegram
  Google Sheets logging for CRM or follow-up
  🖥️ Demo: https://www.loom.com/share/4c2ae62154d74b66b4a59a6926282fab
  🔄 How It Works

  Telegram Input
  Users message a company or person’s name to your Telegram bot.

  GPT-4 AI Agent Analyzes the Request
  Determines if input is a person or company
  Starts the enrichment process
  Explorium MCP Client Fetches B2B Data
  Pulls from enterprise-grade business databases
  Finds company size, revenue, funding, contact names, tech stack, and more
  Augments with Tavily search where needed
  Smart Data Processor
  Structures the info
  Classifies it
  Adds enrichment and processing timestamps
  GPT-4 Generates Email Sequence
  4-email cold outreach campaign
  Personalized based on enriched profile
  Professional tone with soft CTA and clear value
  Google Sheets Logging
  People Sheet: name, role, LinkedIn, experience, education, skills
  Companies Sheet: size, HQ, tech stack, funding, lead score, outreach emails
  Telegram Responds in Real-Time
  Sends back structured summary
  Clean JSON or readable text
  🧰 Requirements

  To run this workflow, you’ll need:

  ✅ Telegram Bot (via BotFather)
  ✅ OpenAI API Key (GPT-4 or GPT-4o)
  ✅ Explorium MCP credentials (for B2B enrichment)
  ✅ Tavily API key (for supplemental web results)
  ✅ Google Sheets account (OAuth2 connected to n8n)

  ⚙️ Setup Instructions

  Import the Template into n8n
  Use the JSON file to create a new workflow.
  Configure Telegram Trigger
  Set up your bot via BotFather
  Connect your Telegram API credentials in n8n
  Connect External APIs
  Set up Explorium MCP credentials (via header auth)
  Add Tavily and OpenAI credentials in their respective nodes
  Replace Google Sheets Links
  Update documentId and sheetName to point to your target Sheets
  Customize (Optional)
  Tweak prompt logic, email tone, or data mapping
  Add Slack alerts or CRM pushes
  Test the Flow
  DM a name or company to your Telegram bot
  Wait a few seconds for a full enriched reply + email sequence
  📥 Output Includes:

  Full structured profile in JSON format
  4 cold outreach emails tailored to the lead
  Stored copy in Google Sheets for sales or follow-up
  💼 Who This Is For:

  SDRs & Sales Teams
  AI/Marketing Agencies
  Growth Hackers
  Founders doing outbound manually

nodes_used:
  ["n8n-nodes-base.telegramTrigger","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.memoryPostgresChat","@n8n/n8n-nodes-langchain.mcpClientTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.code","n8n-nodes-base.telegram","n8n-nodes-base.if","n8n-nodes-base.if","n8n-nodes-base.googleSheets","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.agent","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.code"]

workflow_json_compressed:
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metadata_json:
  {"categories":["Marketing","Communication","Data Processing"],"complexity":"medium","use_cases":["automatic lead enrichment","personalized email outreach","telegram-based customer communication","crm lead tracking"],"estimated_setup_minutes":15,"required_services":["Telegram","Google Sheets","GPT-4 (Google Gemini API)","Explorium MCP","Postgres Chat Memory"],"key_features":["AI-powered lead profiling","personalized cold email generation","real-time chat interaction","data enrichment via MCP tools","automated follow-up sequence"],"target_audience":["sales professionals","marketing managers","outreach specialists"]}


name: Multi-Channel Customer Support Automation Suite
author_name: Elie Kattar
author_username: solutionflows
categories: []
created_at: 2025-06-22T22:08:29.964Z
updated_at: 2025-06-22T22:08:29.964Z
url: https://n8n.io/workflows/5135
scraped_at: 2026-05-02 08:04:49
metadata_generated_at: 2026-05-02 08:36:20
description:
  Multi-Channel Customer Support Automation Suite

  Transform your customer support operations with this enterprise-grade automation workflow that unifies, categorizes, and intelligently routes support tickets from multiple channels.

  🎯 Overview

  This comprehensive n8n workflow automates your entire customer support pipeline, reducing response times by up to 80% while ensuring no customer inquiry goes unnoticed. It seamlessly integrates email, web forms, and webhooks into a single, intelligent support system that works 24/7.

  💡 Key Benefits

  Unified Inbox**: Consolidate support requests from email, web forms, chat, and social media into one streamlined workflow
  Instant Response**: Automatically acknowledge tickets with intelligent, category-specific responses within seconds
  Smart Routing**: Use AI-powered categorization to route tickets to the right team instantly
  Priority Detection**: Automatically identify and escalate urgent issues and VIP customers
  Team Collaboration**: Real-time Slack notifications with color-coded priority alerts
  Zero Setup Hassle**: Pre-configured with industry best practices and ready to deploy

  🚀 Core Features

  Intelligent Ticket Processing
  Automatic categorization into billing, technical, account, feature requests, and complaints
  Sentiment analysis to detect frustrated customers
  Priority assignment based on keywords, customer status, and urgency indicators
  Custom tagging for easy tracking and reporting

  Multi-Channel Integration
  IMAP email monitoring for support inboxes
  Webhook endpoints for web forms and chat widgets
  Expandable architecture for social media channels
  Unified message format regardless of source

  Automated Response System
  Category-specific email templates
  Personalized responses with ticket IDs
  Smart logic to skip auto-responses for urgent/negative cases
  Customizable templates for your brand voice

  Team Notifications & Escalation
  Real-time Slack alerts with full ticket context
  Color-coded priorities (red/urgent, orange/high, green/normal)
  One-click actions to view or claim tickets
  Automatic escalation rules for time-sensitive issues

  CRM & Analytics Ready
  Pre-configured for major CRM systems (Zendesk, HubSpot, Salesforce)
  Comprehensive logging for performance metrics
  Error handling with admin notifications
  Built-in success/failure tracking

  📊 Use Cases

  SaaS Companies: Handle subscription issues, technical bugs, and feature requests with specialized routing to product, engineering, and billing teams.

  E-commerce: Manage order inquiries, shipping issues, and returns while maintaining high customer satisfaction scores.

  Agencies: Provide white-label support services with customizable branding and client-specific routing rules.

  Startups: Scale support operations without hiring additional staff by automating 70% of routine inquiries.

  🛠️ Technical Specifications

  Channels Supported**: Email (IMAP), Web Forms, Webhooks, expandable to social media
  Response Time**: &lt; 2 seconds for auto-responses
  Categorization Accuracy**: 85%+ with keyword matching, 95%+ with AI enhancement
  Scalability**: Handles 1,000+ tickets/day on standard n8n infrastructure
  Integration Ready**: Slack, all major CRMs, SMTP, custom APIs

  💰 ROI & Impact

  Typical results from implementing this workflow:
  80% reduction** in first response time
  60% decrease** in ticket handling time
  40% of tickets** resolved automatically
  95% customer satisfaction** for auto-responded tickets
  Save 20+ hours/week** of manual ticket sorting

  🎁 What's Included

  Complete n8n workflow JSON (ready to import)
  5 pre-configured auto-response templates
  Intelligent categorization rules for common support scenarios
  Priority detection algorithms
  Slack notification formatting
  Error handling and recovery logic
  Setup documentation and customization guide

  🔧 Requirements

  n8n instance (self-hosted or cloud)
  Email account with IMAP/SMTP access
  Slack workspace (for notifications)
  CRM system (optional but recommended)

  🚦 Quick Setup

  Import the workflow JSON
  Configure email and Slack credentials
  Customize auto-response templates
  Connect your CRM
  Go live in under 30 minutes

  Perfect for businesses handling 50-5,000 support tickets monthly who want to deliver exceptional customer service while reducing operational costs.

nodes_used:
  ["n8n-nodes-base.emailReadImap","n8n-nodes-base.webhook","n8n-nodes-base.function","n8n-nodes-base.function","n8n-nodes-base.if","n8n-nodes-base.function","n8n-nodes-base.emailSend","n8n-nodes-base.slack","n8n-nodes-base.function","n8n-nodes-base.function","n8n-nodes-base.function","n8n-nodes-base.merge","n8n-nodes-base.httpRequest","n8n-nodes-base.stickyNote","n8n-nodes-base.respondToWebhook"]

workflow_json_compressed:
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metadata_json:
  {"categories":["Customer Support","Operations","Communication"],"complexity":"medium","use_cases":["unify support channels","categorize tickets","route inquiries","automate responses","track customer issues"],"estimated_setup_minutes":30,"required_services":["Email","Webhooks","Web Forms"],"key_features":["multi-channel aggregation","intelligent ticket routing","automated response handling","channel unification","support workflow management"],"target_audience":["support managers","operations staff","customer success teams"]}


name: Facebook/Meta Conversion API for eCommerce Leads/Orders
author_name: Omar Akoudad
author_username: mediaplusma
categories: []
created_at: 2025-06-23T00:59:02.029Z
updated_at: 2025-06-23T00:59:02.029Z
url: https://n8n.io/workflows/5136
scraped_at: 2026-05-02 08:04:49
metadata_generated_at: 2026-05-02 08:36:20
description:
  This n8n workflow helps eCommerce businesses (especially in the Cash on Delivery space) send real-time order events to the Meta (Facebook) Conversions API, ensuring accurate event tracking and better ad attribution.

  Features
  Webhook Listener**: Accepts incoming order data (name, phone, IP, user-agent, etc.) via HTTP POST/GET.

  Data Normalization**: Cleans and formats first_name, last_name, phone, and event_time according to Facebook's strict specs.

  Data Hashing**: Securely hashes sensitive user data (SHA256), as required by Meta.

  Full Custom Data Suppor**t: Pass order value, currency, and more.

  Ideal For:
  Shopify, WooCommerce, custom stores (Laravel, Node, etc.)

  Businesses using Meta Ads and needing high-quality server-side tracking

  Teams without access to full dev resources, but using n8n for automation

  How It Works:

  Receive Order from your store via Webhook or API.

  Format & Normalize fields to match Facebook’s expected structure.

  Encrypt Sensitive Fields using SHA256 (name, phone, email).

  Send to Facebook via the Conversions API endpoint.

  Requirements:
  A Meta Business Manager account with Conversions API access

  Your Access Token and Pixel ID set up in n8n credentials

nodes_used:
  ["n8n-nodes-base.set","n8n-nodes-base.stickyNote","n8n-nodes-base.set","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.facebookGraphApi","n8n-nodes-base.webhook","n8n-nodes-base.stickyNote","n8n-nodes-base.code","n8n-nodes-base.stickyNote","n8n-nodes-base.manualTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.code","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

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metadata_json:
  {"categories":["Marketing","Data Processing"],"complexity":"medium","use_cases":["track eCommerce orders","send leads to Meta API","improve ad attribution"],"estimated_setup_minutes":30,"required_services":["Facebook/Meta Graph API","Webhooks","External Payment Gateways (implicit)"],"key_features":["HTTP endpoint for data ingestion","Data normalization","Sensitive data hashing","Event tracking"],"target_audience":["ecommerce managers","marketers","developers"]}


name: Extract Facebook Group Posts with Airtop
author_name: Airtop
author_username: cesar-at-airtop
nodes_used: ["n8n-nodes-base.formTrigger","n8n-nodes-base.airtop","n8n-nodes-base.stickyNote"]
categories: []
created_at: 2025-06-23T05:35:12.640Z
updated_at: 2025-06-23T05:35:12.640Z
url: https://n8n.io/workflows/5138
scraped_at: 2026-05-02 08:04:49
metadata_generated_at: 2026-05-02 08:36:20
description:
  Extract Facebook Group Posts with Airtop

  Use Case

  Extracting content from Facebook Groups allows community managers, marketers, and researchers to gather insights, monitor discussions, and collect engagement metrics efficiently. This automation streamlines the process of retrieving non-sponsored post data from group feeds.

  What This Automation Does

  This automation extracts key post details from a Facebook Group feed using the following input parameters:

  Facebook Group URL**: The URL of the Facebook Group feed you want to scrape.
  Airtop Profile**: The name of your Airtop Profile authenticated to Facebook.

  It returns up to 5 non-sponsored posts with the following attributes for each:

  Post text
  Post URL
  Page/profile URL
  Timestamp
  Number of likes
  Number of shares
  Number of comments
  Page or profile details
  Post thumbnail

  How It Works

  Form Trigger: Collects the Facebook Group URL and Airtop Profile via a form.
  Browser Automation:

     Initiates a new browser session using Airtop.
     Navigates to the provided Facebook Group feed.
     Uses an AI prompt to extract post data, including interaction metrics and profile information.
  Structured Output: The results are returned in a defined JSON schema, ready for downstream use.

  Setup Requirements

  Airtop API Key — Free to generate.
  An Airtop Profile logged into Facebook.

  Next Steps

  Integrate With Analytics Tools**: Feed the output into dashboards or analytics platforms to monitor community engagement.
  Automate Alerts**: Trigger notifications for posts matching certain criteria (e.g., high engagement, keywords).
  Combine With Comment Automation**: Extend this to reply to posts or engage with users using other Airtop automations.

  Let me know if you’d like this saved as a .md file or included in your Airtop automation library.

  Read more about how to extract posts from Facebook groups

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metadata_json:
  {"categories":["Marketing","Data Processing","Communication"],"complexity":"medium","use_cases":["extract social media content","monitor group discussions","collect engagement metrics","gather insights from posts"],"estimated_setup_minutes":15,"required_services":[],"key_features":["extract group posts automatically","support various input parameters"],"target_audience":["community managers","marketers","researchers"]}


name: Automated Instagram Reels Workflow
author_name: Iniyavan JC
author_username: netwithjc
categories: []
created_at: 2025-06-23T05:42:27.177Z
updated_at: 2025-06-23T05:42:27.177Z
url: https://n8n.io/workflows/5139
scraped_at: 2026-05-02 08:04:48
metadata_generated_at: 2026-05-02 08:36:19
description:
  This workflow automates the process of creating and posting Instagram Reels, combining Google Drive, AI, Airtable, and the Facebook Graph API. It supports two content creation paths:

  Scheduled Random Video Selection & Posting

  Selects a random video from a Google Drive folder named "Random video mover" based on a schedule.

  Moves the video to a processing folder for posting.

  Manual Upload Trigger & Posting

  Watches a specific Google Drive folder ("n8n reels automation on instagram").

  Triggers the workflow when a new video is uploaded.

  Core Process (applies to both paths)

  Download Video from Google Drive.

  AI Caption Generation with Google Gemini, using the file name as context. The AI creates concise captions with hashtags and a call-to-action.

  Airtable Logging to store video name, caption, and URL.

  Instagram Reels Posting via the Facebook Graph API.

  Recent Change
  In early 2025, Meta tightened its requirements for video_url and image_url parameters. URLs must now be direct, public links to the raw media file with no redirects or authentication. Google Drive links no longer work.

  Our Fix

  Store the binary file locally on the n8n server at /tmp/video.mp4.

  Serve the file through a public n8n webhook with the correct Content-Type.

  Use the webhook URL in the Facebook Graph API request.

  Upload succeeds without the “Media download has failed” error.

  Cleanup

  Deletes the temporary file after posting.

  Benefits

  Saves time with full automation.

  Improves engagement through AI-generated captions.

  Keeps content organized in Airtable.

  Works with Meta’s updated API requirements by hosting files directly from the n8n server.

nodes_used:
  ["n8n-nodes-base.googleDriveTrigger","n8n-nodes-base.googleDrive","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.airtable","n8n-nodes-base.facebookGraphApi","n8n-nodes-base.facebookGraphApi","n8n-nodes-base.googleDrive","n8n-nodes-base.wait","n8n-nodes-base.wait","n8n-nodes-base.code","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.code","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.wait","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.readWriteFile","n8n-nodes-base.respondToWebhook","n8n-nodes-base.webhook","n8n-nodes-base.readWriteFile","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
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metadata_json:
  {"categories":["Social Media","Marketing","AI/ML"],"complexity":"medium","use_cases":["Generate Instagram reels from existing videos","Automate scheduled content posting","Trigger on-demand content uploads"],"estimated_setup_minutes":45,"required_services":["Google Drive","Google AI (Gemini)","Facebook Graph API","Airtable"],"key_features":["Scheduled random video selection","Manual webhook-triggered uploads","AI-enhanced content creation","File automation between folders"],"target_audience":["social media managers","content creators","marketing teams"]}


name: Build and Update RAG System with Google Drive, Qdrant, and Gemini Chat
author_name: Davide Boizza
author_username: n3witalia
categories: []
created_at: 2025-06-23T08:09:25.952Z
updated_at: 2025-06-23T08:09:25.952Z
url: https://n8n.io/workflows/5140
scraped_at: 2026-05-02 08:04:48
metadata_generated_at: 2026-05-02 08:36:19
description:
  This workflow automates the creation and management of a Retrieval-Augmented Generation (RAG) system using Qdrant as a vector store and Google Drive as the document source. It enables full or incremental updates to documents in the Qdrant vector database and integrates with a chatbot using Google Gemini for question answering.

  Here is a clear and professional description in English of the n8n workflow “Create a RAG with Qdrant and update single files”, including its benefits:

  Benefits

  Efficient RAG Setup**
    Seamlessly integrates OpenAI, Qdrant, and Google Drive to create a scalable RAG pipeline.

  Single File Update**
    You can replace the vector representation of a single file without reprocessing the entire collection—ideal for maintaining document freshness.

  Flexible File Source**
    Works with Google Drive, allowing document management and updates from a familiar interface.
  How It Works  
  This workflow is designed to create a Retrieval-Augmented Generation (RAG) system using Qdrant as a vector store and Google Drive as a document source. It consists of four main phases:  

  Collection Setup**:  
    Creates or clears a Qdrant collection to store vectorized documents.  
    Configures the collection with cosine distance metrics and other parameters.  

  Document Processing**:  
    Retrieves files from a specified Google Drive folder.  
    Downloads and processes each file (text extraction, chunking, and embedding using OpenAI).  
    Stores the embeddings in Qdrant for vector search.  

  Single-File Update**:  
    Allows updating or deleting a specific file in the Qdrant collection by referencing its Google Drive ID.  
    Re-embeds the file and updates the vector store.  

  RAG Querying**:  
    Uses a chat trigger to receive user questions.  
    Retrieves relevant documents from Qdrant using vector similarity.  
    Generates answers using Google Gemini as the language model.  

  Set Up Steps  

  Configure Qdrant:  
     Replace QDRANTURL and COLLECTION in the "Create collection" and "Clear collection" HTTP nodes.  
     Ensure Qdrant API credentials are correctly set in the credentials section.  

  Google Drive Integration:  
     Specify the Google Drive folder ID in the "Get files" node.  
     Ensure Google Drive OAuth credentials are configured.  

  OpenAI and Gemini Keys:  
     Add OpenAI API credentials for embeddings (used in "Embeddings OpenAI" nodes).  
     Configure Google Gemini credentials for the chat model.  

  Single-File Update:  
     Set the file_id in the "Edit Fields3" node to target a specific Google Drive file for updates.  

  Testing:  
     Trigger the workflow manually to populate the Qdrant collection.  
     Use the chat interface to test RAG responses.  
  Need help customizing?  
  Contact me for consulting and support or add me on Linkedin. 

nodes_used:
  ["n8n-nodes-base.manualTrigger","@n8n/n8n-nodes-langchain.embeddingsOpenAi","@n8n/n8n-nodes-langchain.documentDefaultDataLoader","@n8n/n8n-nodes-langchain.vectorStoreQdrant","n8n-nodes-base.httpRequest","@n8n/n8n-nodes-langchain.textSplitterRecursiveCharacterTextSplitter","n8n-nodes-base.splitInBatches","n8n-nodes-base.wait","@n8n/n8n-nodes-langchain.embeddingsOpenAi","@n8n/n8n-nodes-langchain.documentDefaultDataLoader","@n8n/n8n-nodes-langchain.textSplitterRecursiveCharacterTextSplitter","n8n-nodes-base.httpRequest","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequest","n8n-nodes-base.googleDrive","n8n-nodes-base.googleDrive","n8n-nodes-base.googleDrive","@n8n/n8n-nodes-langchain.chatTrigger","@n8n/n8n-nodes-langchain.chainRetrievalQa","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","@n8n/n8n-nodes-langchain.retrieverVectorStore","@n8n/n8n-nodes-langchain.vectorStoreQdrant","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.embeddingsOpenAi","n8n-nodes-base.stickyNote","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.vectorStoreQdrant","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
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metadata_json:
  {"categories":["AI/ML","Data Processing","DevOps"],"complexity":"medium","use_cases":["build RAG systems","update vector databases","create chatbots","process Google Drive documents"],"estimated_setup_minutes":45,"required_services":["Qdrant","Google Drive","Google Gemini"],"key_features":["full RAG pipeline automation","incremental document updates","vector database management","chatbot integration"],"target_audience":["data scientists","developers","qa engineers"]}


name: Auto Icon & Cover for New Notion Pages
author_name: TreyDong
author_username: trey-dong
categories: []
created_at: 2025-06-23T08:17:34.157Z
updated_at: 2025-06-23T08:17:34.157Z
url: https://n8n.io/workflows/5141
scraped_at: 2026-05-02 08:04:50
metadata_generated_at: 2026-05-02 08:36:21
description:
  How it works
  • Automatically detects when new pages are created in your Notion workspace
  • Uses AI to generate contextually relevant icons based on page titles for perfect visual representation
  • Fetches random high-quality cover images from Unsplash to add visual appeal to each page
  • Seamlessly integrates with your existing Notion workflow without manual intervention

  Set up steps
  • Connect your Notion workspace using API credentials - takes about 5 minutes to configure
  • Set up AI service integration for intelligent icon generation based on page titles
  • Configure Unsplash API access for random cover image fetching
  • Configure webhook triggers to monitor new page creation events
  • Test the workflow with a sample page to ensure proper functionality
  • Keep detailed setup instructions and troubleshooting tips in the workflow notes for future reference

  This template helps streamline your Notion workspace by automatically beautifying new pages with AI-generated icons and stunning Unsplash covers, saving you time while maintaining a visually appealing and professional appearance across your knowledge base.

nodes_used:
  ["n8n-nodes-base.httpRequest","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.splitInBatches","n8n-nodes-base.webhook","@n8n/n8n-nodes-langchain.lmChatOpenRouter","@n8n/n8n-nodes-langchain.chainLlm","n8n-nodes-base.code","n8n-nodes-base.stickyNote","n8n-nodes-base.code","n8n-nodes-base.httpRequest","n8n-nodes-base.code","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
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metadata_json:
  {"categories":["AI/ML","Communication"],"complexity":"medium","use_cases":["auto-generate page icons","fetch random cover images","integrate with Notion"],"estimated_setup_minutes":5,"required_services":["Notion","OpenRouter","Unsplash"],"key_features":["AI-powered icon creation","automatic image fetching","zero manual configuration"],"target_audience":["content creators","productivity managers","team leads"]}


name: AI-Powered Email Replies with Spam Filtering & FAQ Lookup using GPT-4o mini & Pinecone
author_name: Matteo
author_username: mattabott
categories: []
created_at: 2025-06-23T09:18:25.356Z
updated_at: 2025-06-23T09:18:25.356Z
url: https://n8n.io/workflows/5142
scraped_at: 2026-05-02 08:04:49
metadata_generated_at: 2026-05-02 08:36:20
description:
  This n8n workflow automates the handling of incoming emails. It detects and filters out spam, searches a knowledge base (FAQ) stored in a Pinecone vector database, and sends a reply using Gmail — all powered by an AI model (GPT-4o mini).

  How It Works
  Receiving Emails

  The Gmail Trigger node checks a Gmail inbox every hour.

  When a new email arrives, it starts the workflow.

  Fetching Full Email Content

  The get_message node retrieves all the details of the message: sender, subject, text, message ID, etc.

  Spam Filtering

  The Spam checker node uses GPT-4o mini to classify the email as either "spam" or "no spam".

  It detects not only classic spam but also automated messages (e.g. from Google or Microsoft).

  If marked as "spam", the workflow ends and nothing is processed.

  Conditional Filter

  The If node checks the spam result.

  Only "no spam" emails proceed to the AI Agent.

  AI-Based Reply

  The AI Agent node generates a response based on:

  	The email content

  	A system prompt defining the assistant’s behavior (polite, professional, under the name “Total AI Solutions”)

  	Information retrieved from the Pinecone Vector Store, which contains FAQs

  The AI is instructed to always check the vector store before replying.

  The AI prepares both the subject and the body of the reply.

  Sending the Reply

  The Gmail node sends the reply to the original sender.

  It uses the original email's ID to keep the thread intact.

  Language Model

  The OpenAI Chat Model node provides GPT-4o mini as the language engine for generating responses.

  Memory Support

  The Simple Memory node maintains short-term context, helpful in multi-turn conversations.

  Knowledge Base (FAQ)

  The Pinecone Vector Store node connects to a Pinecone index (faqmattabott) containing vectorized FAQ content.

  Vectors are created using the Embeddings OpenAI node.

nodes_used:
  ["@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.memoryBufferWindow","n8n-nodes-base.gmailTool","n8n-nodes-base.gmailTrigger","n8n-nodes-base.gmail","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.vectorStorePinecone","@n8n/n8n-nodes-langchain.embeddingsOpenAi","n8n-nodes-base.if","@n8n/n8n-nodes-langchain.openAi"]

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metadata_json:
  {"categories":["AI/ML","Communication","Data Processing"],"complexity":"medium","use_cases":["automate email replies","filter spam","search knowledge base","build AI chatbots"],"estimated_setup_minutes":15,"required_services":["Gmail","OpenAI","Pinecone"],"key_features":["spam detection","vector search","LLM content generation","conditional logic"],"target_audience":["operators","support teams","developers"]}


name: 🛠️ Transform JSON to XML for Enhanced AI Prompt Formatting
author_name: Lucas Peyrin
author_username: lucaspeyrin
categories: []
created_at: 2025-06-23T09:48:08.695Z
updated_at: 2025-06-23T09:48:08.695Z
url: https://n8n.io/workflows/5144
scraped_at: 2026-05-02 08:04:50
metadata_generated_at: 2026-05-02 08:36:19
description:
  Overview

  This template provides a powerful and configurable utility to convert JSON data into a clean, well-structured XML format. It is designed for developers, data analysts, and n8n users who need to interface with legacy systems, generate structured reports, or prepare data for consumption by Large Language Models (LLMs), which often exhibit improved understanding and parsing with XML-formatted input.

  Use Cases

  This workflow is ideal for solving several common data transformation problems:

  Preparing Data for AI Prompts:** LLMs like GPT-4 often parse XML more reliably than JSON within a prompt. The explicit closing tags and hierarchical nature of XML reduce ambiguity, leading to better and more consistent responses from the AI.
  Interfacing with Legacy Systems:** Many enterprise systems, SOAP APIs, and older software exclusively accept or produce data in XML format. This template acts as a bridge, allowing modern JSON-based services to communicate with them seamlessly.
  Generating Structured Reports:** Create XML files for reporting or data interchange standards that require a specific, well-defined structure.
  Improving Data Readability:** For complex nested data, a well-formatted XML can be easier for humans to read and debug than a compact JSON string.

  How it works

  This workflow acts as a powerful, configurable JSON to XML converter. It takes a JSON object as input and performs the following steps:

  Recursively Parses JSON: It intelligently navigates through the entire JSON structure, including nested objects and arrays.
  Handles Data Types:
      Primitive Arrays (e.g., ["a", "b", "c"]) are joined into a single string with a safe delimiter.
      Complex Arrays (of objects) are converted into indexed XML tags (&lt;0&gt;, &lt;1&gt;, etc.).
      Dates are automatically detected and formatted into a readable YYYY-MM-DD HH:mm:ss format.
  Generates XML String: It constructs a final XML string based on the logic and configuration set inside the Code node. The output is provided in a single xml field, ready for use.

  Set up steps

  Setup time: ~1 minute

  This workflow is designed to be used as a sub-workflow (or "child workflow").

  In your main workflow, add an Execute Workflow node.
  In the Workflow parameter of that node, select this "JSON to XML Converter" workflow.
  That's it! You can now send JSON data to the Execute Workflow node and it will return the converted XML string in the xml field.

  Customization Options

  The true power of this template lies in its customizability, all managed within the configuration section at the top of the Code node. This allows you to fine-tune the output XML to your exact needs.

  REMOVE_EMPTY_VALUES**: Set to true (default) to completely omit tags for null, undefined, or empty string values, resulting in a cleaner XML. Set to false to include empty tags like &lt;myTag&gt;&lt;/myTag&gt;.
  Newline Formatting**: Control the spacing and readability of the output with four distinct settings:
      NEWLINES_TOP_LEVEL: Adjusts the newlines between root-level elements.
      NEWLINES_ARRAY_ITEMS: Controls spacing between items in a complex array (e.g., between &lt;0&gt; and &lt;1&gt;).
      NEWLINES_OBJECT_PROPERTIES: Manages newlines between the properties of an object.
      NEWLINES_WITHIN_TAGS: Adds newlines between an opening/closing tag and its content for an "indented" look.

  Prerequisites

  An active n8n instance.
  Basic familiarity with JSON and XML data structures.
  Understanding of how to use the Execute Workflow node to run sub-workflows.

nodes_used:
  ["n8n-nodes-base.code","n8n-nodes-base.executeWorkflowTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
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metadata_json:
  {"categories":["Data Processing"],"complexity":"medium","use_cases":["Convert JSON to XML","Format data for LLMs","Integrate legacy systems","Generate structured reports"],"estimated_setup_minutes":15,"required_services":["GitHub Copilot","Code Interpreter"],"key_features":["JSON to XML transformation","Configurable parameters","LLM-optimized output","Modular workflow structure"],"target_audience":["developers","data analysts","machine learning engineers"]}


name: Trustpilot Insights Scraper: Auto Reviews via Bright Data + Google Sheets Sync
author_name: Shiv Gupta
author_username: shivgupta
categories: []
created_at: 2025-06-23T10:00:18.093Z
updated_at: 2025-06-23T10:00:18.093Z
url: https://n8n.io/workflows/5145
scraped_at: 2026-05-02 08:04:50
metadata_generated_at: 2026-05-02 08:36:21
description:
  Trustpilot Insights Scraper: Auto Reviews via Bright Data + Google Sheets Sync

  Overview
  A comprehensive n8n automation that scrapes Trustpilot business reviews using Bright Data and automatically stores structured data in Google Sheets.

  Workflow Architecture

  1. 📝 Form Trigger Node
  Purpose: Manual input interface for users
  Type**: n8n-nodes-base.formTrigger
  Configuration**:
    Form Title: "Website URL"
    Field: "Trustpilot Website URL"
  Function**: Accepts Trustpilot URL input from users to initiate the scraping process

  2. 🌐 HTTP Request (Trigger Scraping)
  Purpose: Initiates scraping on Bright Data platform
  Type**: n8n-nodes-base.httpRequest
  Method**: POST
  Endpoint**: https://api.brightdata.com/datasets/v3/trigger
  Configuration**:
    Query Parameters:
      dataset_id: gd_lm5zmhwd2sni130p
      include_errors: true
      limit_multiple_results: 2
    Headers:
      Authorization: Bearer BRIGHT_DATA_API_KEY
    Body: JSON with input URL and 35+ custom output fields

  Custom Output Fields
  The workflow extracts the following data points:
  Company Information**: company_name, company_logo, company_overall_rating, company_total_reviews, company_about, company_email, company_phone, company_location, company_country, company_category, company_id, company_website
  Review Data**: review_id, review_date, review_rating, review_title, review_content, review_date_of_experience, review_url, date_posted
  Reviewer Information**: reviewer_name, reviewer_location, reviews_posted_overall
  Review Metadata**: is_verified_review, review_replies, review_useful_count
  Rating Distribution**: 5_star, 4_star, 3_star, 2_star, 1_star
  Additional Fields**: url, company_rating_name, is_verified_company, breadcrumbs, company_other_categories

  3. ⌛ Snapshot Progress Check
  Purpose: Monitors scraping job status
  Type**: n8n-nodes-base.httpRequest
  Method**: GET
  Endpoint**: https://api.brightdata.com/datasets/v3/progress/{{ $json.snapshot_id }}
  Configuration**:
    Query Parameters: format=json
    Headers: Authorization: Bearer BRIGHT_DATA_API_KEY
  Function**: Receives snapshot_id from previous step and checks if data is ready

  4. ✅ IF Node (Status Check)
  Purpose: Determines next action based on scraping status
  Type**: n8n-nodes-base.if
  Condition**: $json.status === "ready"
  Logic**:
    If True: Proceeds to data download
    If False: Triggers wait cycle

  5. 🕒 Wait Node
  Purpose: Implements polling delay for incomplete jobs
  Type**: n8n-nodes-base.wait
  Duration**: 1 minute
  Function**: Pauses execution before re-checking snapshot status

  6. 🔄 Loop Logic
  Purpose: Continuous monitoring until completion
  Flow**: Wait → Check Status → Evaluate → (Loop or Proceed)
  Prevents**: API rate limiting and unnecessary requests

  7. 📥 Snapshot Download
  Purpose: Retrieves completed scraped data
  Type**: n8n-nodes-base.httpRequest
  Method**: GET
  Endpoint**: https://api.brightdata.com/datasets/v3/snapshot/{{ $json.snapshot_id }}
  Configuration**:
    Query Parameters: format=json
    Headers: Authorization: Bearer BRIGHT_DATA_API_KEY

  8. 📊 Google Sheets Integration
  Purpose: Stores extracted data in spreadsheet
  Type**: n8n-nodes-base.googleSheets
  Operation**: Append
  Configuration**:
    Document ID: 1yQ10Q2qSjm-hhafHF2sXu-hohurW5_KD8fIv4IXEA3I
    Sheet Name: "Trustpilot"
    Mapping: Auto-map all 35+ fields
    Credentials: Google OAuth2 integration

  Data Flow

  User Input (URL) 
      ↓
  Bright Data API Call
      ↓
  Snapshot ID Generated
      ↓
  Status Check Loop
      ↓
  Data Ready Check
      ↓
  Download Complete Dataset
      ↓
  Append to Google Sheets

  Technical Specifications

  Authentication
  Bright Data**: Bearer token authentication
  Google Sheets**: OAuth2 integration

  Error Handling
  Includes error tracking in Bright Data requests
  Conditional logic prevents infinite loops
  Wait periods prevent API rate limiting

  Data Processing
  Mapping Mode**: Auto-map input data
  Schema**: 35+ predefined fields with string types
  Conversion**: No type conversion (preserves raw data)

  Setup Requirements

  Prerequisites
  Bright Data Account: Active account with API access
  Google Account: With Sheets API enabled
  n8n Instance: Self-hosted or cloud version

  Configuration Steps
  API Keys: Configure Bright Data bearer token
  OAuth Setup: Connect Google Sheets credentials
  Dataset ID: Verify correct Bright Data dataset ID
  Sheet Access: Ensure proper permissions for target spreadsheet

  Environment Variables
  BRIGHT_DATA_API_KEY: Your Bright Data API authentication token

  Use Cases

  Business Intelligence
  Competitor analysis and market research
  Customer sentiment monitoring
  Brand reputation tracking

  Data Analytics
  Review trend analysis
  Rating distribution studies
  Customer feedback aggregation

  Automation Benefits
  Scalability**: Handle multiple URLs sequentially
  Reliability**: Built-in error handling and retry logic
  Efficiency**: Automated data collection and storage
  Consistency**: Standardized data format across all scrapes

  Limitations and Considerations

  Rate Limits
  Bright Data API has usage limitations
  1-minute wait periods help manage request frequency

  Data Volume
  Limited to 2 results per request (configurable)
  Large datasets may require multiple workflow runs

  Compliance
  Ensure compliance with Trustpilot's terms of service
  Respect robots.txt and rate limiting guidelines

  Monitoring and Maintenance

  Status Tracking
  Monitor workflow execution logs
  Check Google Sheets for data accuracy
  Review Bright Data usage statistics

  Regular Updates
  Update API keys as needed
  Verify dataset ID remains valid
  Test workflow functionality periodically

  Workflow Metadata

  Version ID**: dd3afc3c-91fc-474e-99e0-1b25e62ab392
  Instance ID**: bc8ca75c203589705ae2e446cad7181d6f2a7cc1766f958ef9f34810e53b8cb2
  Execution Order**: v1
  Active Status**: Currently inactive (requires manual activation)
  Template Status**: Credentials setup completed

  For any questions or support, please contact: Email
  or fill out this form

nodes_used:
  ["n8n-nodes-base.if","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.formTrigger","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.wait","n8n-nodes-base.if","n8n-nodes-base.httpRequest","n8n-nodes-base.googleSheets"]

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metadata_json:
  {"categories":["Data Processing"],"complexity":"medium","use_cases":["collect customer reviews","sync data to spreadsheets","manual audit triggers"],"estimated_setup_minutes":15,"required_services":["Bright Data","Google Sheets"],"key_features":["web scraping","form input","structured data storage"],"target_audience":["analysts","marketers"]}


name: 🛠️ Process AI Output to Structured JSON with Robust JSON Parser
author_name: Lucas Peyrin
author_username: lucaspeyrin
categories: []
created_at: 2025-06-23T10:13:09.027Z
updated_at: 2025-06-23T10:13:09.027Z
url: https://n8n.io/workflows/5146
scraped_at: 2026-05-02 08:04:50
metadata_generated_at: 2026-05-02 08:36:19
description:
  How it works

  This workflow is a robust and forgiving JSON parser designed to handle malformed or "dirty" JSON strings often returned by AI models or scraped from web pages. It takes a text string as input and attempts to extract and parse a valid JSON object from it.

  Cleans Input: It starts by trimming whitespace and removing common Markdown code fences (like ` Applies Multiple Fixes: It systematically attempts to correct common JSON errors in a specific order:
      Escapes unescaped control characters (like newlines) within strings.
      Fixes invalid backslash escape sequences.
      Removes trailing commas.
      Intelligently attempts to fix unescaped double quotes inside string values.
  Parses Strategically: If a direct parse fails, it tries to extract a potential JSON object from the text (e.g., finding a {...} block inside a larger sentence) and then re-applies the cleaning logic to that extracted portion.
  Outputs Clean Data: If successful, it outputs the parsed JSON fields. By default, it removes the detailed parsing_status object, but you can deactivate the final "Set" node to keep it for debugging.

  Set up steps

  Setup time: ~1 minute

  This workflow is designed to be used as a sub-workflow and requires no internal setup.

  In your main workflow, add an Execute Sub-Workflow node where you need to parse a messy JSON string.
  In the Workflow parameter, select this "Robust JSON Parser" workflow.
  Ensure the data you send to the node is a JSON object containing a text field, where the value of text is the string you want to parse. For example: { "text": "{\\\"key\\\": \\\"some broken json...\\\"}" }.
  The workflow will return the successfully parsed data. To see a detailed log of the cleaning process, simply deactivate the final Remove parsing_status node inside this workflow.

nodes_used:
  ["n8n-nodes-base.executeWorkflowTrigger","n8n-nodes-base.code","n8n-nodes-base.set","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.set","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

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metadata_json:
  {"categories":["Data Processing","AI/ML"],"complexity":"medium","use_cases":["normalize AI JSON output","extract structured data from text","handle malformed JSON","clean web-scraped content","validate JSON structure"],"estimated_setup_minutes":15,"required_services":["language_models","web_scrapers","api_integrations"],"key_features":["graceful error handling","regression-based cleanup","multi-step JSON repair","code_node execution for validation","markdown fence detection"],"target_audience":["data_engineers","developers","automation_specialists"]}


name: Convert Markdown content to Google Docs document with automatic formatting
author_name: Roman Rozenberger
author_username: romek
categories: []
created_at: 2025-06-23T10:24:50.224Z
updated_at: 2025-06-23T10:24:50.224Z
url: https://n8n.io/workflows/5147
scraped_at: 2026-05-02 08:04:49
metadata_generated_at: 2026-05-02 08:36:20
description:
  This workflow is perfect for technical writers, content creators, marketers, and developers who write in Markdown but need to collaborate or publish using Google Docs format. Ideal for teams that want to streamline their content creation and review process.

  What problem does this workflow solve?

  Manual conversion from Markdown to Google Docs is time-consuming and often loses formatting. This workflow eliminates the tedious copy-paste process, automatically preserves formatting, and creates organized, timestamped documents in your Google Drive. Perfect for content teams who write in Markdown but need Google Docs for collaboration and review.

  What this workflow does

  Converts Markdown to HTML** with proper formatting preservation (headers, lists, links, tables)
  Creates timestamped Google Docs** documents with automatic naming
  Adds Drive location metadata** for better organization and reference
  Maintains document structure** including emojis, tables, and text formatting
  Automates file creation** in specified Google Drive folders

  Setup

  Google Drive OAuth2 credentials configured in n8n
  Target Google Drive folder URL
  Input your content title and Markdown text in the "Set Input Data" node

  How to customize this workflow to your needs

  Modify HTML formatting options** in the Markdown conversion node
  Change file naming patterns** to match your organization system  
  Adjust Drive folder structure** and metadata inclusion
  Update MIME type handling** for different output requirements
  Add additional processing steps** like notifications or integrations

  Perfect for technical documentation workflows, content publishing pipelines, blog preparation, and automated report generation.

  Setup Instructions - Markdown to Google Docs Converter

  Prerequisites

  n8n instance** (local or cloud)
  Google account** with Google Drive access
  Basic understanding** of n8n workflow configuration

  Step 1: Import the Workflow

  Open n8n and navigate to Workflows
  Click "Add workflow" → "Import from JSON"
  Upload the Export_Markdown_Content_do_Google_Docs_Document.json file
  Save the workflow with a descriptive name

  Step 2: Configure Google Drive Credentials

  Create Google Drive OAuth2 Credentials

  In n8n, go to Settings → Credentials
  Click "Add credential" → "Google Drive OAuth2 API"
  Follow the OAuth setup to authorize n8n access to Google Drive:
     Visit Google Cloud Console
     Create or select a project
     Enable Google Drive API
     Create OAuth2 credentials
     Add authorized redirect URI for your n8n instance
  Name the credential (e.g., "Google Drive - Markdown Converter")

  Configure Google Drive Nodes

  Update these nodes with your Google Drive credentials:
  Create Empty File
  Update Document with Correct HTML Formatting

  In each node:
  Select your Google Drive credential from the dropdown
  Test the connection to ensure it works properly

  Step 3: Prepare Your Google Drive

  Create Target Folder

  Go to Google Drive (drive.google.com)
  Create a new folder for your converted documents
  Copy the folder URL (will look like: https://drive.google.com/drive/folders/FOLDER_ID)
  Ensure the folder has proper permissions for your Google account

  Step 4: Configure Input Data

  Set Your Default Values

  Open the "Set Input Data" node
  Update the assignments with your preferences:

     Google Drive URL:
     Replace the example URL with your target folder URL
     Format: https://drive.google.com/drive/folders/YOUR_FOLDER_ID

     Content Title:
     Set a default title or leave placeholder text
     This will be used in the document filename

     Content in Markdown:
     Add your Markdown content or keep example for testing
     Supports standard Markdown syntax (headers, lists, links, tables)

  Step 5: Test the Workflow

  Initial Test Run

  Ensure all credentials are configured
  Click the "Test workflow" button on the Manual Trigger node
  Monitor the execution - check for any errors in node outputs
  Verify the result:
     Check your Google Drive folder
     Look for a new document with timestamp in the name
     Open the document to verify formatting

  Troubleshooting Common Issues

  Google Drive Permission Errors:
  Verify OAuth2 credentials are properly configured
  Check that the target folder exists and is accessible
  Ensure Google Drive API is enabled in Google Cloud Console

  Markdown Conversion Issues:
  Check that your Markdown syntax is valid
  Test with simple content first (headers, paragraphs, lists)
  Verify the "Change Markdown To HTML" node settings

  File Creation Problems:
  Confirm the Google Drive folder URL format is correct
  Check that the folder ID in the URL is valid
  Ensure your Google account has write permissions to the folder

  Step 6: Customize for Your Needs

  Modify HTML Formatting Options

  In the "Change Markdown To HTML" node:
  Enable/disable emoji support** (currently enabled)
  Adjust table formatting** (currently enabled)
  Modify header ID generation** (currently disabled)
  Configure space requirements** for headers

  Update File Naming Pattern

  In the "Create Empty File" node:
  Change the naming convention**: Currently uses _PUB {Content Title} {timestamp}
  Modify timestamp format**: Currently yyyy-MM-dd HH:mm:ss
  Add prefixes or suffixes** as needed for your organization

  Step 7: Production Usage

  Regular Workflow Execution

  Update the "Set Input Data" node with new content
  Execute the workflow manually or set up triggers
  Monitor execution logs for any issues
  Check Google Drive for generated documents

  Integration Options

  Webhook Integration:
  Add a Webhook trigger to accept external Markdown content
  Useful for automated content publishing workflows

  Email Integration:
  Add email notifications when documents are created
  Include links to generated Google Docs

  Advanced Configuration

  Error Handling

  Add error handling nodes after critical operations
  Implement retry logic for API failures
  Set up notifications for failed executions

  Performance Optimization

  Adjust the "Wait for Document Creation" timing if needed
  Consider file size limits for Google Docs

  Support and Troubleshooting

  Common Solutions

  Timeout errors**: Increase wait time in "Wait for Document Creation"
  Authentication failures**: Refresh Google OAuth2 credentials
  Formatting issues**: Test with simpler Markdown first

  Getting Help

  Check n8n community forums for Google Drive integration issues
  Review Google Drive API documentation for rate limits
  Test with minimal Markdown content to isolate problems

  Total setup time: ~15-20 minutes  
  Difficulty level: Intermediate  
  Requirements: Google account, n8n instance, basic OAuth2 setup knowledge

nodes_used:
  ["n8n-nodes-base.manualTrigger","n8n-nodes-base.markdown","n8n-nodes-base.set","n8n-nodes-base.convertToFile","n8n-nodes-base.googleDrive","n8n-nodes-base.merge","n8n-nodes-base.wait","n8n-nodes-base.code","n8n-nodes-base.set","n8n-nodes-base.googleDrive","n8n-nodes-base.stickyNote"]

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metadata_json:
  {"categories":["Productivity"],"complexity":"medium","use_cases":["convert markdown to Google Docs","automate document formatting","streamline content creation","publish markdown content","collaborate on documents"],"estimated_setup_minutes":15,"required_services":["Google Drive"],"key_features":["automatic markdown parsing","preserves document formatting","eliminates manual copy-paste","creates organized Google Docs files"],"target_audience":["technical writers","content creators","developers"]}


name: Local Chatbot with Retrieval Augmented Generation (RAG)
author_name: Thomas Janssen
author_username: thomasjanssen-tech
categories: []
created_at: 2025-06-23T10:40:17.187Z
updated_at: 2025-06-23T10:40:17.187Z
url: https://n8n.io/workflows/5148
scraped_at: 2026-05-02 08:04:48
metadata_generated_at: 2026-05-02 08:36:19
description:
  Build a 100% local RAG with n8n, Ollama and Qdrant. This agent uses a semantic database (Qdrant) to answer questions about PDF files.

  Tutorial

  Click here to view the YouTube Tutorial

  How it works
  Build a chatbot that answers based on documents you provide it (Retrieval Augmented Generation). You can upload as many PDF files as you want to the Qdrant database. The chatbot will use its retrieval tool to fetch the chunks and use them to answer questions.

  Installation
  Install n8n + Ollama + Qdrant using the Self-hosted AI starter kit
  Make sure to install Llama 3.2 and mxbai-embed-large as embeddings model.

  How to use it
  First run the "Data Ingestion" part and upload as many PDF files as you want
  Run the Chatbot and start asking questions about the documents you uploaded

nodes_used:
  ["n8n-nodes-base.formTrigger","@n8n/n8n-nodes-langchain.vectorStoreQdrant","@n8n/n8n-nodes-langchain.embeddingsOllama","@n8n/n8n-nodes-langchain.documentDefaultDataLoader","@n8n/n8n-nodes-langchain.textSplitterRecursiveCharacterTextSplitter","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.chatTrigger","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatOllama","@n8n/n8n-nodes-langchain.memoryBufferWindow","@n8n/n8n-nodes-langchain.vectorStoreQdrant","@n8n/n8n-nodes-langchain.embeddingsOllama","n8n-nodes-base.stickyNote"]

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metadata_json:
  {"categories":["AI/ML"],"complexity":"medium","use_cases":["build local chatbot","retrieve document chunks","generate answers from context"],"estimated_setup_minutes":15,"required_services":["Ollama","Qdrant"],"key_features":["semantic search","document indexing","local LLM integration","context-aware responses"],"target_audience":["developers","data scientists"]}


name: 🛠️ Create PDF from HTML with Gotenberg
author_name: Lucas Peyrin
author_username: lucaspeyrin
categories: []
created_at: 2025-06-23T10:48:23.572Z
updated_at: 2025-06-23T10:48:23.572Z
url: https://n8n.io/workflows/5149
scraped_at: 2026-05-02 08:04:50
metadata_generated_at: 2026-05-02 08:36:19
description:
  How it works

  This workflow converts an HTML string into a polished PDF file using the powerful open-source Gotenberg service. It's designed to be a reusable utility in your automation stack.

  Receives Input: The workflow is triggered with a JSON object containing the full html code as a string and a desired file_name for the output.
  Prepares File: It converts the incoming HTML string into a binary index.html file, which is required for the API call.
  Calls Gotenberg API: It sends the HTML file to a running Gotenberg instance via an HTTP request. It also dynamically sets the output filename and embeds metadata (like Author, Title, and Creation Date) directly into the PDF.
  Returns PDF: The workflow outputs the final binary PDF file, ready to be saved, sent in an email, or used in the next step of your main workflow.

  Set up steps

  Setup time: ~3 minutes

  This workflow has one critical prerequisite: a running Gotenberg instance that your n8n can connect to.

  1. Prerequisite: Run Gotenberg

  You need to have the Gotenberg service running. The easiest way is with Docker. Add the following service to your docker-compose.yml file (the same one you use for n8n):

  services:
  ... your n8n service ...

    gotenberg:
      image: gotenberg/gotenberg:8
      restart: always

  Then, restart your stack with docker compose up -d. This makes Gotenberg available at the address http://gotenberg:3000 from within your n8n container.

  2. Use as a Sub-Workflow

  This workflow is ready to be used as a sub-workflow.

  In your main workflow, add an Execute Sub-Workflow node.
  In the Workflow parameter, select this "Create PDF from HTML" workflow.
  Provide the input data in the required format: a JSON object with html and file_name keys.

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

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metadata_json:
  {"categories":["Data Processing"],"complexity":"complex","use_cases":["Convert HTML to PDF","Generate printable documents"],"estimated_setup_minutes":20,"required_services":["Gotenberg"],"key_features":["REST API integration","File Conversion"],"target_audience":["Developers","Content Creators"]}


name: Translate RSS Feed Content to Hindi and Publish to WordPress with OpenAI
author_name: The Higher Pitch
author_username: digvijay
categories: []
created_at: 2025-06-23T10:52:16.997Z
updated_at: 2025-06-23T10:52:16.997Z
url: https://n8n.io/workflows/5150
scraped_at: 2026-05-02 08:04:50
metadata_generated_at: 2026-05-02 08:36:20
description:
  This workflow automatically pulls articles from an RSS feed, translates the content and title from English to Hindi using OpenAI, extracts the featured image from the HTML content, and publishes the translated post as a draft on a connected WordPress site.

  🔧 Key Features:

  Polls RSS feed every 10 minutes for new articles

  Extracts and parses the featured image from custom HTML tags

  Translates content and title from English to Hindi using OpenAI Assistant

  Uploads the featured image to WordPress media library

  Associates the image with the new draft post

  Publishes the translated article as a draft for review

  🎯 Use Case:
  Ideal for multi-language blog automation or content localization workflows where original content is in English and needs to be localized into Hindi before publishing.

nodes_used:
  ["n8n-nodes-base.rssFeedReadTrigger","n8n-nodes-base.wordpress","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.openAi","@n8n/n8n-nodes-langchain.openAi","n8n-nodes-base.code"]

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metadata_json:
  {"categories":["AI/ML","Marketing","Content Management"],"complexity":"medium","use_cases":["translate RSS articles","auto-publish to WordPress","multilingual content syndication"],"estimated_setup_minutes":15,"required_services":["OpenAI","WordPress","RSS to Web Feed reader"],"key_features":["real-time RSS monitoring","AI-powered translation","automatic image extraction","draft post creation"],"target_audience":["content managers","multilingual marketers","blog operators"]}


name: Automate Customer Support with Gmail, Google Sheets, ERP Data & GPT-4o AI
author_name: AOE Agent Lab
author_username: aoepeople
categories: []
created_at: 2025-06-23T11:45:30.982Z
updated_at: 2025-06-23T11:45:30.982Z
url: https://n8n.io/workflows/5152
scraped_at: 2026-05-02 08:04:49
metadata_generated_at: 2026-05-02 08:36:20
description:
  🌐 AI Customer Support Assistant - Cloud Version

  What this workflow does:

  This AI-powered customer support automation processes incoming support requests via email or chat, analyzes them using AI, retrieves relevant context, and generates draft responses for support agents.

  Key Features:

  ✅ Multi-channel Input: Email & chat triggers
  ✅ AI-powered Analysis: Extracts sentiment, urgency, and key information
  ✅ Context Integration: Combines product manuals, ERP data, and support history
  ✅ Draft Response Generation: Creates professional responses in German
  ✅ Human-in-the-loop: Approval workflow before sending to customers

  Demo Instructions:
  Use the Chat interface to test with sample customer queries
  Or send test emails to trigger the email workflow
  Watch how AI analyzes and generates contextual responses

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.gmailTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.stickyNote","n8n-nodes-base.googleSheets","n8n-nodes-base.aggregate","n8n-nodes-base.stickyNote","n8n-nodes-base.googleDrive","n8n-nodes-base.extractFromFile","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequest","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.chainLlm","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.stickyNote","n8n-nodes-base.if","n8n-nodes-base.gmail","n8n-nodes-base.gmail","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.chatTrigger","@n8n/n8n-nodes-langchain.informationExtractor","n8n-nodes-base.stickyNote"]

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metadata_json:
  {"categories":["AI/ML","Customer Service"],"complexity":"medium","use_cases":["Process support requests","Generate response drafts","Analyze customer sentiment","Retrieve product data"],"estimated_setup_minutes":45,"required_services":["Gmail","Google Sheets","ERP API","OpenAI GPT-4o","Google Drive"],"key_features":["multi-channel input","sentiment analysis","context integration","draft generation"],"target_audience":["support agents","customer success managers","IT admins"]}


name: TikTok Post Scraper via Keywords | Bright Data + Sheets Integration
author_name: Shiv Gupta
author_username: shivgupta
categories: []
created_at: 2025-06-23T11:59:55.041Z
updated_at: 2025-06-23T11:59:55.041Z
url: https://n8n.io/workflows/5153
scraped_at: 2026-05-02 08:04:49
metadata_generated_at: 2026-05-02 08:36:20
description:
  🎵 TikTok Post Scraper via Keywords | Bright Data + Sheets Integration

  📝 Workflow Description
  Automatically scrapes TikTok posts based on keyword search using Bright Data API and stores comprehensive data in Google Sheets for analysis and monitoring.

  🔄 How It Works

  This workflow operates through a simple, automated process:

  Keyword Input:** User submits search keywords through a web form
  Data Scraping:** Bright Data API searches TikTok for posts matching the keywords
  Processing Loop:** Monitors scraping progress and waits for completion
  Data Storage:** Automatically saves all extracted data to Google Sheets
  Result Delivery:** Provides comprehensive post data including metrics, user info, and media URLs

  ⏱️ Setup Information

  Estimated Setup Time: 10-15 minutes

  This includes importing the workflow, configuring credentials, and testing the integration. Most of the process is automated once properly configured.

  ✨ Key Features

  📝 Keyword-Based Search
  Search TikTok posts using specific keywords

  📊 Comprehensive Data Extraction
  Captures post metrics, user profiles, and media URLs

  📋 Google Sheets Integration
  Automatically organizes data in spreadsheets

  🔄 Automated Processing
  Handles scraping progress monitoring

  🛡️ Reliable Scraping
  Uses Bright Data's professional infrastructure

  ⚡ Real-time Updates
  Live status monitoring and data processing

  📊 Data Extracted

  | Field | Description | Example |
  |-------|-------------|---------|
  | url | TikTok post URL | https://www.tiktok.com/@user/video/123456 |
  | post_id | Unique post identifier | 7234567890123456789 |
  | description | Post caption/description | Check out this amazing content! #viral |
  | digg_count | Number of likes | 15400 |
  | share_count | Number of shares | 892 |
  | comment_count | Number of comments | 1250 |
  | play_count | Number of views | 125000 |
  | profile_username | Creator's username | @creativity_master |
  | profile_followers | Creator's follower count | 50000 |
  | hashtags | Post hashtags | #viral #trending #fyp |
  | create_time | Post creation timestamp | 2025-01-15T10:30:00Z |
  | video_url | Direct video URL | https://video.tiktok.com/tos/... |

  🚀 Setup Instructions

  Step 1: Prerequisites

  n8n instance (self-hosted or cloud)
  Bright Data account with TikTok scraping dataset access
  Google account with Sheets access
  Basic understanding of n8n workflows

  Step 2: Import Workflow

  Copy the provided JSON workflow code
  In n8n: Go to Workflows → + Add workflow → Import from JSON
  Paste the JSON code and click Import
  The workflow will appear in your n8n interface

  Step 3: Configure Bright Data

  In n8n: Navigate to Credentials → + Add credential → Bright Data API
  Enter your Bright Data API credentials
  Test the connection to ensure it's working
  Update the workflow nodes with your dataset ID: gd_lu702nij2f790tmv9h
  Replace BRIGHT_DATA_API_KEY with your actual API key

  Step 4: Configure Google Sheets

  Create a new Google Sheet or use an existing one
  Copy the Sheet ID from the URL
  In n8n: Credentials → + Add credential → Google Sheets OAuth2 API
  Complete OAuth setup and test connection
  Update the Google Sheets node with your Sheet ID
  Ensure the sheet has a tab named "Tiktok by keyword"

  Step 5: Test the Workflow

  Activate the workflow using the toggle switch
  Access the form trigger URL to submit a test keyword
  Monitor the workflow execution in n8n
  Verify data appears in your Google Sheet
  Check that all fields are populated correctly

  ⚙️ Configuration Details

  Bright Data API Settings
  Dataset ID:** gd_lu702nij2f790tmv9h
  Discovery Type:** discover_new
  Search Method:** keyword
  Results per Input:** 2 posts per keyword
  Include Errors:** true

  Workflow Parameters
  Wait Time:** 1 minute between status checks
  Status Check:** Monitors until scraping is complete
  Data Format:** JSON response from Bright Data
  Error Handling:** Automatic retry on incomplete scraping

  📋 Usage Guide

  Running the Workflow

  Access the form trigger URL provided by n8n
  Enter your desired keyword (e.g., "viral dance", "cooking tips")
  Submit the form to start the scraping process
  Wait for the workflow to complete (typically 2-5 minutes)
  Check your Google Sheet for the extracted data

  Best Practices

  Use specific, relevant keywords for better results
  Monitor your Bright Data usage to stay within limits
  Regularly backup your Google Sheets data
  Test with simple keywords before complex searches
  Review extracted data for accuracy and completeness

  🔧 Troubleshooting

  Common Issues

  🚨 Scraping Not Starting
  Verify Bright Data API credentials are correct
  Check dataset ID matches your account
  Ensure sufficient credits in Bright Data account

  🚨 No Data in Google Sheets
  Confirm Google Sheets credentials are authenticated
  Verify sheet ID is correct
  Check that the "Tiktok by keyword" tab exists

  🚨 Workflow Timeout
  Increase wait time if scraping takes longer
  Check Bright Data dashboard for scraping status
  Verify keyword produces available results

  📈 Use Cases

  Content Research
  Research trending content and hashtags in your niche to inform your content strategy.

  Competitor Analysis
  Monitor competitor posts and engagement metrics to understand market trends.

  Influencer Discovery
  Find influencers and creators in specific topics or industries.

  Market Intelligence
  Gather data on trending topics, hashtags, and user engagement patterns.

  🔒 Security Notes

  Keep your Bright Data API credentials secure
  Use appropriate Google Sheets sharing permissions
  Monitor API usage to prevent unexpected charges
  Regularly rotate API keys for better security
  Comply with TikTok's terms of service and data usage policies

  🎉 Ready to Use!

  Your TikTok scraper is now configured and ready to extract valuable data. Start with simple keywords and gradually expand your research as you become familiar with the workflow.

  Need Help? Visit the n8n community forum or check the Bright Data documentation for additional support and advanced configuration options.

  For any questions or support, please contact: Email or
  fill out this form

nodes_used:
  ["n8n-nodes-base.googleSheets","n8n-nodes-base.httpRequest","n8n-nodes-base.wait","n8n-nodes-base.formTrigger","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","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.stickyNote"]

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metadata_json:
  {"categories":["Social Media Monitoring","Data Processing","Marketing Analytics"],"complexity":"medium","use_cases":["Monitor brand mentions","Track competitor content","Collect trend data","Gather user-generated content"],"estimated_setup_minutes":15,"required_services":["Bright Data","Google Sheets","TikTok"],"key_features":["Keyword-based search","Automated scraping","Data export to spreadsheets","Webhook integration"],"target_audience":["marketers","social media managers","analysts"]}


name: 🛠️ Change Binary MimeType/Extension
author_name: Lucas Peyrin
author_username: lucaspeyrin
categories: []
created_at: 2025-06-23T13:02:42.840Z
updated_at: 2025-06-23T13:02:42.840Z
url: https://n8n.io/workflows/5155
scraped_at: 2026-05-02 08:04:51
metadata_generated_at: 2026-05-02 08:36:19
description:
  How it works

  This workflow changes the file name, and therefore the extension and MIME type, of any binary file passed to it. This is perfect for converting file formats on the fly, like turning a Telegram voice message (.oga) into an MP3 for an AI transcription service.

  Set New File Name: The SET OUTPUT FILE NAME node is where you define the desired output file name and extension (e.g., audio.mp3). It also dynamically captures the property name of the incoming binary (e.g., data).
  Extract Binary Data: The workflow temporarily converts the binary file into a Base64 text string to make it accessible in the next step.
  Rebuild Binary with New Name: A Code node takes the Base64 data and reconstructs it as a binary file, but this time, it assigns the new file name you specified. n8n automatically sets the MIME type based on the new file extension.

  Set up steps

  Setup time: &lt; 1 minute

  This workflow is designed to be used as a sub-workflow.

  In your main workflow, add an Execute Sub-Workflow node where you need to change a file's type.
  In the Workflow parameter, select this "Change Binary MimeType/Extension" workflow.
  Open this workflow and go to the SET OUTPUT FILE NAME node.
  Modify the output_file_name value to your desired file name (e.g., voice_message.mp3 or document.pdf).
  Save this workflow. Now, any binary file you send to it from your main workflow will be returned with the new fileName and mimeType.

nodes_used:
  ["n8n-nodes-base.extractFromFile","n8n-nodes-base.set","n8n-nodes-base.code","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.executeWorkflowTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

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metadata_json:
  {"categories":["Data Processing"],"complexity":"simple","use_cases":["Normalize file extensions","Rename binary files","Troubleshoot MIME types"],"estimated_setup_minutes":5,"required_services":[],"key_features":["Allows dynamic MIMEType setting","Changes file extension","Resets binary filename","Works for binary data files"],"target_audience":["developers","file managers"]}


name: Transform Books into 100+ Social Media Posts with DeepSeek AI and Google Drive
author_name: Abdellah Homrani
author_username: adamcrafts
categories: []
created_at: 2025-06-23T13:46:17.215Z
updated_at: 2025-06-23T13:46:17.215Z
url: https://n8n.io/workflows/5156
scraped_at: 2026-05-02 08:04:50
metadata_generated_at: 2026-05-02 08:36:21
description:
  📚🤖✨ Your Automated Content Factory: Turn Any Book into 100+ Social Media Ideas Instantly Never run out of content again by automatically generating a massive library of social media posts from a single document.

  🚀 Overview

  This automation is a game-changer for content creators, marketers, and authors. It transforms any book or long document into a treasure trove of over 100 ready-to-use, short-form content ideas for platforms like TikTok, Instagram Reels, and YouTube Shorts. Drop a file, and get a batch of viral-ready posts back.

  😩 The Problem

  You have amazing, valuable content locked away in books, e-books, or long reports. Turning that content into a steady stream of engaging social media posts is a painful, manual grind. You spend countless hours rereading chapters, trying to pinpoint interesting facts, brainstorming catchy hooks, and writing dozens of unique posts. It's a creative bottleneck that drains your time and energy, making it impossible to post consistently and scale your reach.

  ✨ The Solution

  This workflow acts as your personal AI content team, working 24/7. Simply drop a book file (like a PDF or TXT) into a designated Google Drive folder. The automation instantly gets to work:
  It reads and understands the entire book, breaking it down chapter by chapter.
  An advanced AI agent then analyzes the core ideas, emotional hooks, and surprising facts within the text.
  It generates 5-10 unique, viral content ideas for each chapter, complete with an irresistible hook, the core message, and a call-to-action to drive engagement.
  Finally, it neatly saves all of these brilliant ideas into a new document in another Google Drive folder, ready for you to use. It's a complete, hands-off content repurposing machine.

  ⚙️ Simple Setup

  This workflow is a pre-built blueprint, designed to be up and running in minutes!

  Upload:** Simply upload the provided JSON file into your n8n instance.
  Detailed Setup:** Follow all the instructions of the Detailed Setup.
  Activate:** Turn the workflow on, and it's ready to go! Let your new automated employee get to work.

  🌐 Explore more workflows
  ❤️ Buy more workflows at: adamcrafts
  🦾 Custom workflows at: adamcrafts@cloudysoftwares.com
  adamaicrafts@gmail.com

nodes_used:
  ["@n8n/n8n-nodes-langchain.vectorStoreQdrant","@n8n/n8n-nodes-langchain.textSplitterRecursiveCharacterTextSplitter","@n8n/n8n-nodes-langchain.documentDefaultDataLoader","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.memoryBufferWindow","n8n-nodes-base.code","n8n-nodes-base.googleDrive","n8n-nodes-base.httpRequest","@n8n/n8n-nodes-langchain.chainRetrievalQa","@n8n/n8n-nodes-langchain.retrieverVectorStore","@n8n/n8n-nodes-langchain.vectorStoreQdrant","@n8n/n8n-nodes-langchain.vectorStoreQdrant","@n8n/n8n-nodes-langchain.embeddingsCohere","@n8n/n8n-nodes-langchain.informationExtractor","n8n-nodes-base.splitOut","n8n-nodes-base.googleDrive","n8n-nodes-base.googleDriveTrigger","n8n-nodes-base.code","@n8n/n8n-nodes-langchain.lmChatDeepSeek","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.outputParserStructured","n8n-nodes-base.stickyNote"]

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metadata_json:
  {"categories":["Marketing","Content Creation","AI/ML"],"complexity":"medium","use_cases":["Generate social media posts from books","Automate content creation","Extract post ideas from documents","Batch create short-form content"],"estimated_setup_minutes":20,"required_services":["Google Drive","Qdrant","DeepSeek AI"],"key_features":["Documents to social media content pipeline","RAG-style content retrieval","AI-powered text generation","High-volume post output"],"target_audience":["Content creators","Social media managers","Marketers"]}


name: Automate Daily AI News with Perplexity Sonar Pro (via Telegram)
author_name: Automate With Marc
author_username: marconi
categories: []
created_at: 2025-06-23T15:09:33.217Z
updated_at: 2025-06-23T15:09:33.217Z
url: https://n8n.io/workflows/5157
scraped_at: 2026-05-02 08:04:48
metadata_generated_at: 2026-05-02 08:36:20
description:
  This workflow contains community nodes that are only compatible with the self-hosted version of n8n. 

  🧠 Perplexity-Powered Daily AI News Digest (via Telegram)


  This ready-to-deploy n8n workflow automates the entire process of collecting, filtering, formatting, and distributing daily AI industry news summaries directly to your Telegram group or channel.

  Powered by Perplexity and OpenAI, it fetches only high-signal AI updates from trusted sources (e.g. OpenAI, DeepMind, HuggingFace, MIT Tech Review), filters out duplicates based on a Google Sheet archive, and delivers beautifully formatted news directly to your team — every morning at 10AM.

  For more such build and step-by-step tutorials, check out:
  https://www.youtube.com/@Automatewithmarc

  🚀 Key Features:
  Perplexity AI Integration: Automatically fetches the most relevant AI developments from the last 24 hours.

  AI Formatter Agent: Cleans the raw feed, removes duplicates, adds summaries, and ensures human-friendly formatting.

  Google Sheets Log: Tracks previously reported news items to avoid repetition.

  Telegram Delivery: Sends a polished daily digest straight to your chat, ready for immediate team consumption.

  Customizable Scheduling: Preconfigured for daily use, but can be modified to fit your team's preferred cadence.

  💼 Ideal For:
  Anyone who wants to stay ahead of fast-moving AI trends with zero manual effort

  🛠️ Tech Stack:
  Perplexity AI

  OpenAI (GPT-4 or equivalent)

  Google Sheets

  Telegram API

  ✅ Setup Notes:
  You’ll need to connect your own OpenAI, Perplexity, Google Sheets, and Telegram credentials.

  Replace the Google Sheet ID and Telegram channel settings with your own.

nodes_used:
  ["n8n-nodes-base.scheduleTrigger","n8n-nodes-base.googleSheetsTool","n8n-nodes-base.googleSheets","n8n-nodes-base.perplexity","@n8n/n8n-nodes-langchain.openAi","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.telegram"]

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metadata_json:
  {"categories":["AI/ML","Communication","Data Processing"],"complexity":"medium","use_cases":["generate daily AI news digests","send curated industry updates to Telegram","automate information gathering and distribution"],"estimated_setup_minutes":15,"required_services":["Perplexity","OpenAI","Telegram"],"key_features":["cross-platform news aggregation","AI-generated content summarization","scheduled automated delivery","community-components activation for self-hosted mode"],"target_audience":["tech journalists","AI practitioners","industry analysts"]}


name: Generate Realistic Sound Effects with CassetteAI and Save to Google Drive
author_name: Davide Boizza
author_username: n3witalia
categories: []
created_at: 2025-06-23T15:12:57.125Z
updated_at: 2025-06-23T15:12:57.125Z
url: https://n8n.io/workflows/5158
scraped_at: 2026-05-02 08:04:49
metadata_generated_at: 2026-05-02 08:36:20
description:
  The Sound Effects Generator is an automated workflow that allows users to create realistic sound effects using AI and save them directly to Google Drive. It generates high-quality sound effects (up to 30 seconds long) based on user prompts.

  How It Works:

  User Input via Web Form
     A form is presented to the user asking for:

     A prompt describing the sound (e.g. "waves crashing", "laser blast").
     A duration in seconds (up to 30 seconds).

  API Request to Generate Audio
     The input is sent to CassetteAI via a POST request using API with proper authentication.

  Status Polling
     The workflow waits for 10 seconds and then checks the status of the request.

  Conditional Flow

     If the audio generation is complete (COMPLETED), it proceeds to fetch the audio file URL.
     If not, it waits and retries.

  Download & Save

     The audio file is downloaded from the URL.
     It is automatically uploaded to a specific folder in the user’s Google Drive, with a timestamped filename.

  Key Advantages

  Fast & Efficient**: Generates up to 30 seconds of audio in just 1 second of processing time.
  No Coding Required**: Entire flow can be triggered via a simple form interface.
  Automated Storage**: Files are automatically saved to a preconfigured Google Drive folder.
  Scalable**: Can be reused for multiple projects by simply changing the input prompts.
  Secure**: Uses secure API key-based authentication for interaction with Fal.run and Google Drive.
  Customizable**: Easy to adapt or extend—for example, sending download links via email or Telegram.

  How It Works  
  Form Submission: The workflow starts with a form where users input a prompt and the desired duration (max 30 seconds) for the sound effect.  
  Audio Creation: The submitted data is sent to the CassetteAI Sound Effects Generator API via an HTTP request, which initiates the sound effect generation process.  
  Status Check: The workflow periodically checks the status of the request. If the status is "COMPLETED," it proceeds to fetch the audio file.  
  Audio Retrieval: The generated audio file is downloaded from the provided URL and uploaded to a specified Google Drive folder, with a timestamped filename for organization.  

  Set Up Steps  
  API Key Configuration:  
     Create an account on fal.ai and obtain an API key.  
     In the "Create audio" node, set the "Header Auth" with:  
       Name: Authorization  
       Value: Key YOURAPIKEY (replace YOURAPIKEY with your actual API key).  

  Google Drive Integration:  
     Ensure the Google Drive node is configured with the correct OAuth2 credentials and folder ID.  
     Adjust the folder ID in the "Upload Audio" node if a different destination is preferred.  

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

nodes_used:
  ["n8n-nodes-base.httpRequest","n8n-nodes-base.stickyNote","n8n-nodes-base.if","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.formTrigger","n8n-nodes-base.wait","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.googleDrive","n8n-nodes-base.httpRequest"]

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metadata_json:
  {"categories":["AI/ML","Audio Processing"],"complexity":"medium","use_cases":["generate custom sound effects","create audio assets","save media to cloud storage","build interactive sound experiences"],"estimated_setup_minutes":30,"required_services":["CassetteAI","Google Drive"],"key_features":["AI-powered sound generation","custom prompt input","configurable audio duration","direct cloud storage integration","automated asset creation"],"target_audience":["audio designers","content creators","media developers"]}


name: AI content creation and auto WordPress publishing with Pexels API image workflow
author_name: Mateusz Kosiorek
author_username: mkosiorek
categories: []
created_at: 2025-06-23T15:48:04.145Z
updated_at: 2025-06-23T15:48:04.145Z
url: https://n8n.io/workflows/5159
scraped_at: 2026-05-02 08:04:48
metadata_generated_at: 2026-05-02 08:36:19
description:
  AI powered content creation and WordPress publishing workflow

  Summary

  This workflow automates the entire process of blog content creation, from idea generation and article writing using Google Gemini, to sourcing images from Pexels and publishing directly to your WordPress site. It uses Google Sheets as a central hub for managing content ideas and tracking their status, all orchestrated through interactive n8n forms.

  Key features

  AI driven content:** Leverages Google Gemini for generating:
      Full blog articles based on prompts.
      Relevant keywords for image searching.
      New blog topic ideas.
  Automated image sourcing:** Searches Pexels for suitable images based on AI generated keywords and downloads them.
  WordPress integration:**
      Creates new posts with AI generated title and content.
      Uploads sourced images to the WordPress media library.
      Sets the uploaded image as the featured image for the post.
  Google Sheets management:**
      Fetches content ideas (prompts) marked as "not generated".
      Updates the sheet after a post is generated with the post ID, title, and generation date.
      Adds newly AI generated blog topic ideas to the sheet.
  Interactive forms:**
      Main trigger form to choose between generating content or adding new ideas.
      Forms to input topics for idea generation.
      Confirmation forms at the end of processes.
  Structured output parsing:** Ensures AI responses for topic generation are correctly formatted as JSON.

  How it works

  The workflow is initiated via an n8n Form Trigger: Select Action, allowing the user to choose one of two main paths:

  1. Generate content path:
      Fetch idea: The Fetch unprocessed ideas (Google Sheets) node retrieves a row from your sheet where the "Generated" column is "no".
      Set prompt: The Set prompt node prepares the topic from the sheet for the AI.
      Generate article: The Generate article AI (Langchain Agent with Google Gemini) node takes the prompt and writes a full article.
      Generate image keyword: The Generate image keyword AI (Langchain Agent with Google Gemini) node creates a concise search term based on the article topic.
      Search image: The Search Pexels image (HTTP Request) node uses the generated keyword to find a relevant image via the Pexels API.
      Create WordPress post: The Create WordPress post node publishes the AI generated article and initial image metadata to your WordPress site.
      Download and upload image: The Download Pexels image (HTTP Request) node fetches the actual image file, and the Upload image (HTTP Request) node uploads it to your WordPress media library.
      Set featured image: The Set featured image (HTTP Request) node links the uploaded image as the featured image for the newly created post.
      Update sheet: The Update Google Sheet node marks the idea as "yes" in your Google Sheet and adds the WordPress post ID and title.
      Confirmation: A Form: End post generation node displays a completion message.

  2. Add ideas path:
      Input topic: The Form: Enter topic for ideas node prompts the user to enter a general subject.
      Generate topics: The Generate blog topics AI (Langchain Agent with Google Gemini and Structured Output Parser) node generates five SEO friendly blog topic ideas based on the user's input, formatted as JSON.
      Process topics: The Split topics node separates the generated list of topics into individual items.
      Add to sheet: For each topic, the Add ideas to sheet (Google Sheets) node appends it as a new row, marked with "Generated: no".
      Loop or end: The Form: Add more topics? node asks the user if they want to generate more ideas or end the process.
          If "NEXT", it loops back to the Form: Enter topic for ideas.
          If "END", a Form: End idea generation node displays a completion message with the list of added topics.

  Nodes used

  Form Trigger
  If
  Google Sheets
  Set
  Langchain Agent (with Google Gemini Chat Model)
  Structured Output Parser (Langchain)
  HTTP Request (for Pexels API and WordPress Media/Post updates)
  WordPress
  Split Out
  Form (for user interaction and completion messages)
  Sticky Note (for instructions within the workflow)

  Setup instructions

  Credentials:
      Google Sheets: Configure your Google Sheets OAuth2 credentials in the Fetch unprocessed ideas, Update Google Sheet, and Add ideas to sheet nodes.
      WordPress: Configure your WordPress API credentials in the Create WordPress post, Upload image, and Set featured image nodes.
      Google Gemini: Configure your Google Gemini (PaLM) API key in the Gemini model for article, Gemini model for image keyword, and Gemini model for topics nodes.
  API keys and URLs:
      Pexels: In the Search Pexels image node, replace &lt;YOUR_PEXELS_API_KEY&gt; in the Authorization header with your actual Pexels API key.
      WordPress URL: In the Upload image and Set featured image nodes, replace &lt;YOUR_WORDPRESS_URL&gt; in the URL field with your WordPress site's domain (e.g., yourblog.com).
  Google Sheet configuration:
      Ensure your Google Sheet (specified by Document ID in Google Sheets nodes) has a sheet named Sheet1 (or update the Sheet Name parameter).
      The sheet should have at least the following columns: Prompt (for the blog idea/topic), Generated (to track status, e.g., "no" or "yes"), row_number (automatically populated by n8n when reading), Date, Title (for the final WordPress post title), Post ID.
  Activate the workflow. The Form Trigger: Select Action will provide a webhook URL to initiate the process.

  Customization ideas

  Modify the AI prompts in the Langchain Agent nodes for different tones, styles, or content structures.
  Change the Google Gemini models used for different cost/performance balances.
  Integrate other image sources instead of or in addition to Pexels.
  Add steps for social media sharing after a post is published.
  Extend the Google Sheet to track more metrics like word count or target keywords.
  Implement more sophisticated error handling.

  Use cases

  Automating blog content generation for personal or company blogs.
  Streamlining content marketing efforts.
  Quickly populating new websites with initial content.
  Assisting SEO agencies in creating draft content for clients.
  Helping solo bloggers maintain a consistent publishing schedule.

nodes_used:
  ["n8n-nodes-base.googleSheets","n8n-nodes-base.set","n8n-nodes-base.wordpress","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.googleSheets","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.formTrigger","n8n-nodes-base.if","n8n-nodes-base.googleSheets","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.form","n8n-nodes-base.form","n8n-nodes-base.if","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","@n8n/n8n-nodes-langchain.outputParserStructured","n8n-nodes-base.splitOut","n8n-nodes-base.form","n8n-nodes-base.form","n8n-nodes-base.stickyNote","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","Marketing","Content Creation"],"complexity":"medium","use_cases":["automate blog content creation","generate article outlines","source stock images","publish content to WordPress"],"estimated_setup_minutes":30,"required_services":["Google Gemini","WordPress","Pexels API","Google Sheets"],"key_features":["AI-driven article writing","automated image sourcing","content status tracking","direct WordPress publishing","user via n8n forms"],"target_audience":["content creators","bloggers","marketing managers"]}


name: 🤖 Build Resilient AI Workflows with Automatic GPT and Gemini Failover Chain
author_name: Lucas Peyrin
author_username: lucaspeyrin
categories: []
created_at: 2025-06-23T16:33:43.301Z
updated_at: 2025-06-23T16:33:43.301Z
url: https://n8n.io/workflows/5160
scraped_at: 2026-05-02 08:04:49
metadata_generated_at: 2026-05-02 08:36:20
description:
  This workflow contains community nodes that are only compatible with the self-hosted version of n8n.

  How it works

  This workflow demonstrates how to create a resilient AI Agent that automatically falls back to a different language model if the primary one fails. This is useful for handling API errors, rate limits, or model outages without interrupting your process.

  State Initialization: The Agent Variables node initializes a fail_count to 0. This counter tracks how many models have been attempted.
  Dynamic Model Selection: The Fallback Models (a LangChain Code node) acts as a router. It receives a list of all connected AI models and, based on the current fail_count, selects which one to use for this attempt (0 for the first model, 1 for the second, etc.).
  Agent Execution: The AI Agent node attempts to run your prompt using the model selected by the router.
  The Fallback Loop:
      On Success: The workflow completes successfully.
      On Error: If the AI Agent node fails, its "On Error" output is triggered. This path loops back to the Agent Variables node, which increments the fail_count by 1. The process then repeats, causing the Fallback Models router to select the next model in the list.
  Final Failure: If all connected models are tried and fail, the workflow will stop with an error.

  Set up steps

  Setup time: ~3-5 minutes

  Configure Credentials: Ensure you have the necessary credentials (e.g., for OpenAI, Google AI) configured in your n8n instance.
  Define Your Model Chain:
      Add the AI model nodes you want to use to the canvas (e.g., OpenAI, Google Gemini, Anthropic).
      Connect them to the Fallback Models node.
      Important: The order in which you connect the models determines the fallback order. The model nodes first created/connected will be tried first.
  Set Your Prompt: Open the AI Agent node and enter the prompt you want to execute.
  Test: Run the workflow. To test the fallback logic, you can temporarily disable the First Model node or configure it with invalid credentials to force an error.

nodes_used:
  ["@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.code","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.manualTrigger","n8n-nodes-base.stickyNote"]

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metadata_json:
  {"categories":["AI/ML","DevOps"],"complexity":"medium","use_cases":["deploy resilient AI agents","handle ML model outages","automate fallback chains","build redundant chatbots"],"estimated_setup_minutes":45,"required_services":["Anthropic","Google Cloud Platform","n8n Self-Hosted"],"key_features":["automatic model failover","error rate tracking","dual API integration","self-hosted node dependencies","resilient chatbot architecture"],"target_audience":["AI engineers","DevOps specialists","ML architects"]}


name: Enrich LinkedIn Profiles with Ghost Genius and Google Sheets (No Account Needed)
author_name: Matthieu
author_username: yaznow
categories: []
created_at: 2025-06-23T17:03:19.850Z
updated_at: 2025-06-23T17:03:19.850Z
url: https://n8n.io/workflows/5161
scraped_at: 2026-05-02 08:04:49
metadata_generated_at: 2026-05-02 08:36:21
description:
  LinkedIn Profile Enrichment Automation

  Who is this for?
  This template is perfect for sales teams, recruiters, marketing professionals, and business development specialists who need to gather comprehensive LinkedIn profile data at scale. Ideal for lead generation teams building prospect databases, recruiters sourcing candidate information, sales professionals researching prospects, and marketing teams creating targeted outreach campaigns.

  What problem does this workflow solve?
  Manually collecting detailed information from LinkedIn profiles is incredibly time-consuming and prone to inconsistency. Visiting each profile individually to extract names, job titles, experience, education, skills, and contact details can take hours for even small prospect lists. This automation eliminates the tedious manual data entry while ensuring consistent, comprehensive profile enrichment.

  What this workflow does
  This workflow automatically enriches a list of LinkedIn profile URLs by extracting comprehensive professional data including:
  Personal details** (first name, last name, headline, location)
  Professional status** (hiring status, open to work indicators)
  Network metrics** (connections, followers count)
  Work experience** (up to 5 most recent positions with company details, dates, and roles)
  Education background** (up to 3 educational institutions with degrees and dates)
  Skills and languages** (complete skill sets and language proficiencies)
  Professional summary** (profile description and bio)

  The enriched data is automatically organized and updated in your Google Sheets database with structured formatting for easy analysis and outreach.

  Setup
  Create a Ghost Genius API account and obtain your API key for cookieless LinkedIn profile scraping
  Configure HTTP Request credentials with Header Auth using your Ghost Genius API key
  Set up your Google Sheets database using the provided template with columns:
     URL, Firstname, Lastname, Tagline, Location
     Connections, Followers, Hiring?, Open to work?
     Summary, Languages, Skills
     Experience 1-5, Education 1-3
  Configure Google Sheets OAuth2 credentials following n8n's authentication setup guide
  Add LinkedIn profile URLs to the first column of your Google Sheet to begin enrichment
  Test the workflow with a small batch before processing larger lists

  How to customize this workflow
  Adjust batch processing settings** to handle larger volumes by modifying the batch size and interval timing
  Add data validation rules** to filter out incomplete or invalid profiles before processing
  Integrate with CRM systems** like HubSpot or Salesforce to automatically sync enriched data
  Set up automated scheduling** to regularly re-enrich profiles and capture profile updates
  Add email notifications** to alert when enrichment batches are completed or encounter errors
  Customize data mapping** to include additional profile fields or reorganize the output structure
  Add duplicate detection** to prevent re-processing the same profiles multiple times

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

workflow_json_compressed:
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metadata_json:
  {"categories":["Sales & Marketing","Data Enrichment","Lead Generation"],"complexity":"medium","use_cases":["Gather prospect LinkedIn data","Build lead databases","Source candidate information","Create outreach campaigns"],"estimated_setup_minutes":5,"required_services":["Spark-seer AI"],"key_features":["Enricn LinkedIn profiles","Aggregate data into spreadsheets","Handle high volumes of prospects"],"target_audience":["Sales professionals","Recruiters","Marketing teams"]}


name: AI-Powered LinkedIn Content Engine (n8n + OpenAI + Perplexity + Replicate)
author_name: Mariano Kostelec
author_username: marianokostelec
categories: []
created_at: 2025-06-23T17:12:12.431Z
updated_at: 2025-06-23T17:12:12.431Z
url: https://n8n.io/workflows/5162
scraped_at: 2026-05-02 08:04:49
metadata_generated_at: 2026-05-02 08:36:20
description:
  A fully automated content engine that researches, writes, scores, and visualizes LinkedIn posts — built with n8n, OpenAI, Perplexity, and Replicate.

  What it does:
  ✅ Researches any topic using real-time data
  ✅ Writes a personalized post in your voice
  ✅ Refines tone and structure
  ✅ Generates abstract, high-quality visual assets
  ✅ Scores the output and saves it to Google Sheets

  How it works:
  Triggered when you change a row status in Google Sheets
  Uses Perplexity to research
  GPT-4o (OpenAI) to create and polish content
  Replicate (FLUX Pro) to generate images
  Scores the post using heuristics
  Appends everything back to your sheet

nodes_used:
  ["@n8n/n8n-nodes-langchain.openAi","@n8n/n8n-nodes-langchain.openAi","n8n-nodes-base.code","@n8n/n8n-nodes-langchain.openAi","n8n-nodes-base.httpRequest","n8n-nodes-base.googleSheets","n8n-nodes-base.perplexity","n8n-nodes-base.code","n8n-nodes-base.webhook"]

workflow_json_compressed:
  [encoded data, 10260 characters]

metadata_json:
  {"categories":["Marketing","Content Creation","AI/ML","Social Media","Communication"],"complexity":"medium","use_cases":["automate LinkedIn posts","research trending topics","generate AI visuals","create scored content","optimize social media"],"estimated_setup_minutes":45,"required_services":["OpenAI","Perplexity","Replicate","Google Sheets"],"key_features":["Real-time topic research","Voice-matching writing","Tone refinement","AI visual generation","Content scoring system"],"target_audience":["social media managers","content creators","brand marketers"]}


name: AI-Powered Stock Analysis Assistant with Telegram, Claude & GPT-4O Vision
author_name: Femi Ad
author_username: hgray
categories: []
created_at: 2025-06-23T17:45:06.815Z
updated_at: 2025-06-23T17:45:06.815Z
url: https://n8n.io/workflows/5163
scraped_at: 2026-05-02 08:04:48
metadata_generated_at: 2026-05-02 08:36:19
description:
  "Ade Technical Analyst" is a dual-workflow AI system combining conversational intelligence with visual chart analysis through Telegram. The system features 11 primary nodes for conversation management and 8 secondary nodes for chart generation and analysis.

  Core Components:

  Telegram Integration: Message handling with dynamic typing indicators

  AI Personality: "Ade" - a financial analyst with 50+ years NYSE/LSE experience using Claude 3.5 Sonnet

  Chart Generation: TradingView integration via Chart-IMG API with MACD and volume indicators

  Visual Analysis: GPT-4O vision for technical pattern recognition

  Memory System: Session-based conversation context retention

  Target Users
  Individual traders seeking professional-grade analysis without subscription costs

  Financial advisors wanting 24/7 AI-powered client support

  Investment educators needing interactive learning tools

  Fintech companies requiring white-label analysis solutions

  Setup Requirements
  Critical Security Fix Needed:

  Remove hardcoded API key from Chart-IMG node immediately

  Store all credentials securely in n8n credential manager

  Required APIs:

  OpenRouter (Claude 3.5 Sonnet)

  OpenAI (GPT-4O vision)

  Chart-IMG API

  Telegram Bot Token

  Technical Prerequisites:

  n8n version 1.7+ with Langchain nodes

  Webhook configuration for Telegram

  Dual-workflow setup with proper ID referencing

  Workflow Requirements
  Security Compliance:

  Never hardcode API keys in workflow JSON files

  Use n8n credential manager for all sensitive data

  Implement proper session isolation for user data

  Include mandatory financial disclaimers

  Performance Specifications:

  Model temperature: 0.8 for balanced responses

  Token limit: 500 for optimized performance

  Dark theme charts with professional indicators

  Session-based memory management

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

nodes_used:
  ["@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.telegram","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.lmChatOpenRouter","n8n-nodes-base.set","n8n-nodes-base.telegram","n8n-nodes-base.merge","n8n-nodes-base.set","n8n-nodes-base.telegramTrigger","@n8n/n8n-nodes-langchain.memoryBufferWindow","n8n-nodes-base.stickyNote","n8n-nodes-base.executeWorkflowTrigger","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.openAi","n8n-nodes-base.httpRequest","n8n-nodes-base.telegram","n8n-nodes-base.set","n8n-nodes-base.httpRequest"]

workflow_json_compressed:
  [encoded data, 9308 characters]

metadata_json:
  {"categories":["AI/ML","Finance"],"complexity":"medium","use_cases":["Stock market analysis","Trade signal generation","Financial chatbot","Chart interpretation"],"estimated_setup_minutes":120,"required_services":["Telegram API","Claude API","OpenRouter","TradingView API","GPT-4 Vision API (via OpenRouter)"],"key_features":["Visual chart analysis","AI persona customization","Dynamic typing indicators","Conversational memory","Trading signal generation"],"target_audience":["Financial analysts","Traders","DevOps engineers"]}


name: LinkedIn Engagement Automator with GPT-4o/Claude, Human Review & Multilingual Comments
author_name: Stefan
author_username: stefan
categories: []
created_at: 2025-06-23T18:42:44.964Z
updated_at: 2025-06-23T18:42:44.964Z
url: https://n8n.io/workflows/5164
scraped_at: 2026-05-02 08:04:49
metadata_generated_at: 2026-05-02 08:36:20
description:
  Automate LinkedIn engagement without sounding like a bot.
  This workflow:
  🌍 Detects language & tone (German / English)
  👍 Chooses the right reaction (like / celebrate / support …)
  🗣 Generates a personalised comment in your voice and mentions the author
  📲 Optional Telegram review – approve ✅ or regenerate ❌ before posting
  💸 Runs on cost-efficient GPT-4o mini or Claude 3.5 Haiku
  ☁️ Publishes comment + reaction via the Unipile API
  Setup (≈ 15-30 min)
  Unipile – connect LinkedIn → copy account_id, dsn, then create an Access-Token (X-API-KEY).
  Telegram (optional) – create a bot, add a credential named YOUR TELEGRAM ACCOUNT.
  OpenAI / Anthropic – add your API key and keep one LLM node (delete the other).
  Open the “Defining guardrails” node and replace the credential placeholders.
  (Optional) Tweak role, comment_length and openers_example_1-3 for your brand voice.
  Security: no live keys included – all secrets are placeholders.
  Best for: solopreneurs, marketing teams, personal-branding consultants.

nodes_used:
  ["@n8n/n8n-nodes-langchain.outputParserStructured","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.toolThink","@n8n/n8n-nodes-langchain.lmChatAnthropic","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.outputParserStructured","@n8n/n8n-nodes-langchain.outputParserStructured","n8n-nodes-base.if","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.httpRequest","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.set","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.informationExtractor","n8n-nodes-base.filter","n8n-nodes-base.telegram","n8n-nodes-base.telegramTrigger"]

workflow_json_compressed:
  [encoded data, 7084 characters]

metadata_json:
  {"categories":["Social Media","AI/ML"],"complexity":"medium","use_cases":["Automate LinkedIn engagement","Generate personalized responses","Moderate AI-generated comments"],"estimated_setup_minutes":30,"required_services":["LinkedIn","Unipile API","Telegram","Anthropic Claude API","OpenAI GPT API"],"key_features":["Presets for diverse reactions","Multi-language support","Human-in-the-loop approval","Tailored comment generation"],"target_audience":["Marketing teams","Social Media Managers","Community managers"]}


name: Manage Google Calendar Events with Natural Language Using Gemini 1.5 Flash
author_name: Sakar Dahal
author_username: sakar-dahal
categories: []
created_at: 2025-06-23T18:42:59.617Z
updated_at: 2025-06-23T18:42:59.617Z
url: https://n8n.io/workflows/5165
scraped_at: 2026-05-02 08:04:50
metadata_generated_at: 2026-05-02 08:36:21
description:
  This is the AI agent which will set the event in the Google Calendar and get the events from the calendar based on the prompt provided to AI agent based on Gemini.

nodes_used:
  ["n8n-nodes-base.googleCalendarTool","n8n-nodes-base.googleCalendarTool","@n8n/n8n-nodes-langchain.memoryBufferWindow","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.chatTrigger","n8n-nodes-base.stickyNote","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"],"complexity":"medium","use_cases":["Set calendar events","Extract event details","Process natural language prompts"],"estimated_setup_minutes":15,"required_services":["Google Calendar","Google Gemini"],"key_features":["Natural language parsing","AI-driven event scheduling","Calendar management"],"target_audience":["developers","power users"]}


name: Sync Leads from Webflow to Pipedrive CRM Using n8n
author_name: PixelMakers
author_username: pixelmakers
categories: []
created_at: 2025-06-23T19:40:33.279Z
updated_at: 2025-06-23T19:40:33.279Z
url: https://n8n.io/workflows/5166
scraped_at: 2026-05-02 08:04:49
metadata_generated_at: 2026-05-02 08:36:21
description:
  This n8n template automates the process of capturing leads from Webflow form submissions and syncing them with your Pipedrive CRM. It ensures that each submission is accurately associated with the correct organization and contact in Pipedrive, streamlining lead management and minimizing duplicates.

  Use cases include:
  Sales teams that want to automate CRM data entry, marketing teams capturing qualified leads from landing pages, or any business looking to improve their Webflow-to-CRM integration workflow.

  Good to know
  The workflow assumes that Webflow form submissions include the lead’s email address.

  The domain is extracted from the email to match or create the organization in Pipedrive.

  This template does not handle lead scoring or enrichment, but can be extended for such use-cases.

  How it works

  Extract website from email
  The email is split to extract the domain (e.g., jane@company.com → company.com), which is used to search for existing organizations.

  Check if the organization exists
  The Pipedrive API is queried using the domain. If the organization exists, we proceed. If not, a new organization is created.

  Check if the person exists
  -- If the person already exists in Pipedrive, a note is added to their activities to log the form submission.
  -- If the person does not exist, a new person is created, a note is added to the person, and a new lead is created.

  (Optional) Add your own actions
  You can extend this workflow to trigger Slack notifications, email follow-ups, or internal dashboards.

  How to use
  Start with the manual trigger node, or replace it with a webhook to connect directly to Webflow form submissions in real-time.

  Requirements
  Webflow form integration (via webhook or other method)
  Pipedrive account and API key

  Customising this workflow
  You can add enrichment services to auto-fill job titles or LinkedIn profiles. Perfect for growing sales pipelines without manual CRM input.

nodes_used:
  ["n8n-nodes-base.webflowTrigger","n8n-nodes-base.pipedrive","n8n-nodes-base.if","n8n-nodes-base.pipedrive","n8n-nodes-base.pipedrive","n8n-nodes-base.pipedrive","n8n-nodes-base.pipedrive","n8n-nodes-base.pipedrive","n8n-nodes-base.if","n8n-nodes-base.pipedrive","n8n-nodes-base.stickyNote","n8n-nodes-base.code","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

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metadata_json:
  {"categories":["Marketing","CRM & Sales"],"complexity":"medium","use_cases":["automate CRM data entry","sync webflow form submissions to Pipedrive","manage lead contacts and organizations"],"estimated_setup_minutes":15,"required_services":["Webflow","Pipedrive"],"key_features":["bimodal platform integration","automatic organization matching","contact creation and linking","duplicate prevention"],"target_audience":["sales teams","marketing teams","business owners"]}


name: Competitor LinkedIn Monitor with Airtop
author_name: Airtop
author_username: cesar-at-airtop
categories: []
created_at: 2025-06-23T20:47:45.167Z
updated_at: 2025-06-23T20:47:45.167Z
url: https://n8n.io/workflows/5167
scraped_at: 2026-05-02 08:04:49
metadata_generated_at: 2026-05-02 08:36:21
description:
  Automating LinkedIn Competitive Monitoring

  Use Case

  Automatically track and summarize LinkedIn posts from key executives at competitor companies. This agent provides structured insights into hiring trends, product announcements, strategic shifts, and thought leadership, helping teams stay informed and responsive without manual monitoring.

  What This Automation Does

  This automation monitors and summarizes LinkedIn posts from competitor profiles and shares the results on Slack. It uses the following input parameters:

  Airtop Profile**: A browser profile authenticated to LinkedIn. Create one
  Google Sheet**: A document listing LinkedIn profile URLs of competitors, copy this one.
  Slack Channel**: The destination for sharing summarized post insights.

  How It Works

  Trigger: The workflow is scheduled to run weekly at a specific time.
  Data Collection: Retrieves the list of competitor LinkedIn URLs from a Google Sheet.
  Browser Automation: Uses Airtop to navigate to each LinkedIn profile and analyze up to 5 recent posts.
  Summarization: Summarizes number of recent posts, main topics, and engagement levels using Airtop’s AI.
  Slack Notification: Posts a formatted summary to a predefined Slack channel.

  Setup Requirements

  Airtop API Key — free to generate.
  An Airtop Profile authenticated to LinkedIn.
  Google Sheet with competitor post URLs, copy this one.
  Slack Bot credentials with access to the target channel.

  Next Steps

  Expand Coverage**: Add more competitor profiles to the Google Sheet to scale monitoring.
  Integrate with CRM**: Feed summarized insights into your CRM for competitor tracking.
  Enhance Analysis**: Include post-level engagement metrics over time for trend analysis.

  Read more about competitve analysis using Linkedin

nodes_used:
  ["n8n-nodes-base.scheduleTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.googleSheets","n8n-nodes-base.slack","n8n-nodes-base.airtop","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
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metadata_json:
  {"categories":["Marketing","Data Processing"],"complexity":"medium","use_cases":["track competitor LinkedIn posts","summarize executive content","monitor hiring trends","detect product announcements","analyze strategic shifts"],"estimated_setup_minutes":15,"required_services":["LinkedIn","Sigma","Slack"],"key_features":["automated competitive intelligence","AI-powered post summarization","executive profile monitoring","structured insight generation"],"target_audience":["marketers","strategists","ops engineers"]}


name: Auto-Generate Facebook Posts from Video Insights using Dumpling AI + GPT-4o
author_name: Yang
author_username: yang
categories: []
created_at: 2025-06-23T21:34:13.431Z
updated_at: 2025-06-23T21:34:13.431Z
url: https://n8n.io/workflows/5168
scraped_at: 2026-05-02 08:04:49
metadata_generated_at: 2026-05-02 08:36:21
description:
  What this workflow does

  This workflow automatically turns new technical video uploads into short,  
  engaging Facebook post drafts—complete with a suggested image—and saves the  
  results to Google Sheets for quick review or publishing.

  It’s designed to help you repurpose tutorial or demo videos into ready-to-use  
  social content without any manual writing or design effort.

  What problem is this workflow solving?

  Manually writing Facebook posts for every new tutorial or product video takes  
  time, especially when you want them to be engaging and consistent. This workflow  
  solves that by using AI to watch for new videos, extract meaningful insights,  
  and write posts and create visuals automatically—saving hours of work.

  Who is this for?

  This workflow is ideal for:
  Content creators uploading tutorial videos  
  Marketing teams working with how-to or product videos  
  Agencies and automation pros building scalable social workflows for clients

  How it works

  Trigger: Starts when a new video is uploaded to a specific Google Drive folder.  
  Download & Convert: Downloads the video and converts it to base64.  
  Extract Insights: Dumpling AI analyzes the video and extracts structured insights  
     such as topic, tools mentioned, and key steps.  
  Generate Post: GPT-4o creates a short, friendly Facebook post using those insights,  
     along with an image prompt.  
  Create Visual: Dumpling AI generates an image using the prompt.  
  Save to Sheet: The Facebook post and image URL are saved to a Google Sheet.

  Setup

  Create a Google Sheet to store the posts and images.  
  Connect your Google Drive, Google Sheets, Dumpling AI, and OpenAI  
     credentials in n8n.  
  Update the workflow with:  
     Your Google Drive folder ID  
     Your target Google Sheet ID  
  (Optional) Edit the prompt used in the GPT node if you want a different tone,  
     style, or structure for the post.

  How to customize the workflow

  Change the platform**: Replace “Facebook” in the prompt with LinkedIn, Instagram,  
    or another platform.  
  Use a different image tool**: You can swap Dumpling AI for any other image  
    generation API (e.g. DALL·E, Midjourney via webhook).  
  Add auto-publishing**: Add a Facebook or social media module to publish the  
    generated post directly instead of just saving to Google Sheets.  
  Tag videos by content type**: Use AI to classify videos into categories and  
    store them in separate tabs or sheets.

nodes_used:
  ["n8n-nodes-base.googleDriveTrigger","n8n-nodes-base.googleDrive","n8n-nodes-base.extractFromFile","n8n-nodes-base.httpRequest","@n8n/n8n-nodes-langchain.openAi","n8n-nodes-base.httpRequest","n8n-nodes-base.googleSheets","n8n-nodes-base.stickyNote"]

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metadata_json:
  {"categories":["Content Creation","Social Media","Data Automation"],"complexity":"medium","use_cases":["automate social media posting","repurpose video content","generate Facebook posts","create video summaries","extract insights from videos"],"estimated_setup_minutes":25,"required_services":["Dumpling AI","OpenAI","Google Sheets","Google Drive"],"key_features":["video-to-social-content automation","AI-driven image generation","metadata extraction","draft saving to spreadsheets","webhook-based triggers"],"target_audience":["content creators","video creators","social media managers"]}


name: Extract Product Info from Website Screenshots with Dumpling AI + Sheets
author_name: Yang
author_username: yang
categories: []
created_at: 2025-06-23T21:45:00.341Z
updated_at: 2025-06-23T21:45:00.341Z
url: https://n8n.io/workflows/5169
scraped_at: 2026-05-02 08:04:49
metadata_generated_at: 2026-05-02 08:36:21
description:
  What this workflow does

  This workflow extracts product details—like name, price, discount, and rating—  
  from website screenshots using Dumpling AI. It starts when a new product page  
  URL is added to a Google Sheet, captures a screenshot of that page, extracts  
  visible product info from the image, and writes the results back into the sheet.

  What problem is this workflow solving?

  Many product pages block traditional scraping tools or use unstructured layouts.  
  This workflow bypasses HTML limitations by using visual AI extraction, making  
  it reliable even when content is embedded in images or hard to parse with code.

  Who is this for?

  This is ideal for eCommerce researchers, pricing analysts, marketers, or anyone  
  building a product database from websites without needing to code or maintain  
  complex scrapers.

  Setup

  Create a Google Sheet with a column named "Site" (or update the trigger).  
  Add your product page URLs in this column—one per row.  
  Connect your Google Sheets and Dumpling AI credentials in n8n.  
  Ensure your Dumpling AI account has API access for screenshots and extraction.

  How to customize the workflow

  Prompt adjustment**:  
    In the “Extract Text from Screenshot” node, you can modify the prompt to  
    extract other information like brand name, delivery time, or availability.

  Add more fields**:  
    After the extraction, edit the “Format Extracted Data” node to map additional  
    fields from the response to your Google Sheet columns.

  Change output destination**:  
    You can easily replace the Google Sheets module with Airtable, Notion, or  
    another app if preferred.

  &gt; ⚠️ This works best when the product data is clearly visible in the screenshot.  
  &gt; It won’t extract info that’s hidden behind popups or loaded via user interaction.

nodes_used:
  ["n8n-nodes-base.googleSheetsTrigger","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.extractFromFile","n8n-nodes-base.set","n8n-nodes-base.googleSheets","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
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metadata_json:
  {"categories":["E-commerce","Data Extraction"],"complexity":"medium","use_cases":["extract product details from images","automate data collection from websites","update spreadsheets with AI insight"],"estimated_setup_minutes":15,"required_services":["Dumpling AI","Google Sheets"],"key_features":["converts screenshots to structured product data","handles 动态 schema product pages","syncs results to spreadsheet automatically"],"target_audience":["data analysts","e-commerce managers","automation engineers"]}


name: 🎓 Learn JSON Basics with an Interactive Step-by-Step Tutorial for Beginners
author_name: Lucas Peyrin
author_username: lucaspeyrin
categories: []
created_at: 2025-06-23T22:42:11.749Z
updated_at: 2025-06-23T22:42:11.749Z
url: https://n8n.io/workflows/5170
scraped_at: 2026-05-02 08:04:48
metadata_generated_at: 2026-05-02 08:24:25
description:
  How it works

  This workflow is an interactive, hands-on tutorial designed to teach you the absolute basics of JSON (JavaScript Object Notation) and, more importantly, how to use it within n8n. It's perfect for beginners who are new to automation and data structures.

  The tutorial is structured as a series of simple steps. Each node introduces a new, fundamental concept of JSON:

  Key/Value Pairs: The basic building block of all JSON.
  Data Types: It then walks you through the most common data types one by one:
      String (text)
      Number (integers and decimals)
      Boolean (true or false)
      Null (representing "nothing")
      Array (an ordered list of items)
      Object (a collection of key/value pairs)
  Using JSON with Expressions: The most important step! It shows you how to dynamically pull data from a previous node into a new one using n8n's expressions ({{ }}).
  Final Exam: A final node puts everything together, building a complete JSON object by referencing data from all the previous steps.

  Each node has a detailed sticky note explaining the concept in simple terms.

  Set up steps

  Setup time: 0 minutes!

  This is a tutorial workflow, so there is no setup required.

  Simply click the "Execute Workflow" button to run it.
  Follow the instructions in the main sticky note: click on each node in order, from top to bottom.
  For each node, observe the output in the right-hand panel and read the sticky note next to it to understand what you're seeing.

  By the end, you'll have a solid understanding of what JSON is and how to work with it in your own n8n workflows.

nodes_used:
  ["n8n-nodes-base.manualTrigger","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.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.set","n8n-nodes-base.stickyNote","n8n-nodes-base.set","n8n-nodes-base.stickyNote","n8n-nodes-base.set","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":["Education","Data Processing"],"complexity":"simple","use_cases":["new to automation","new to JSON","new coding"],"estimated_setup_minutes":40,"required_services":["manual input"],"key_features":["interactive learning","concept by concept"],"target_audience":["beginners","students"]}


name: 🎓 Learn API Fundamentals with an Interactive Hands-On Tutorial Workflow
author_name: Lucas Peyrin
author_username: lucaspeyrin
categories: []
created_at: 2025-06-23T23:27:47.342Z
updated_at: 2025-06-23T23:27:47.342Z
url: https://n8n.io/workflows/5171
scraped_at: 2026-05-02 08:04:49
metadata_generated_at: 2026-05-02 08:24:25
description:
  How it works

  This template is an interactive, hands-on tutorial designed to demystify what an API is and how it works, right inside your n8n canvas.

  It uses a simple restaurant analogy to explain the core concepts:
  You* are the "Client" (an *HTTP Request** node).
  The Kitchen is the "Server" (a Webhook node).
  The API is the Menu and the Waiter—the set of rules for how you can ask for things and get a response.

  The workflow is a series of self-contained lessons. Each lesson pairs an HTTP Request node (the customer placing an order) with a Webhook node (the kitchen receiving and responding to the order) to demonstrate a key concept:

  The Basics: Making a simple GET request to a URL.
  Customizing: Using Query Parameters to filter or modify your request.
  Sending Data: Using the POST method and a Body to send information to the server.
  Identification: Using Headers and simple Authentication to prove who you are.
  Handling Delays: Understanding how Timeouts prevent your workflow from getting stuck.

  Set up steps

  Setup time: &lt; 1 minute

  This workflow is a self-contained tutorial and requires no external services or credentials. You may want to check the Base URL.

  Click "Execute Workflow" to run the entire tutorial.
  Follow the flow from top to bottom, exploring each "Lesson".
  For each lesson, click on the HTTP Request node and its corresponding Webhook node to see how they are configured and what they do.
  Read the sticky notes next to each lesson—they contain the core explanations!

  That's it! Explore and have fun learning the fundamentals of APIs in an interactive way.

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

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metadata_json:
  {"categories":["Education","AI/ML","Developer Tools"],"complexity":"medium","use_cases":["learning API concepts","teaching HTTP requests","interactive education"],"estimated_setup_minutes":5,"required_services":[],"key_features":["educational nodes","analogy-based learning","interactive tutorials"],"target_audience":["students","developers","teachers"]}


name: Monitor SSL certificate expiry dates with Google Sheets & Slack alerts
author_name: CustomJS
author_username: customjs
categories: []
created_at: 2025-06-23T23:48:58.339Z
updated_at: 2025-06-23T23:48:58.339Z
url: https://n8n.io/workflows/5172
scraped_at: 2026-05-02 08:04:51
metadata_generated_at: 2026-05-02 08:36:21
description:
  This n8n workflow illustrates how to monitor and track SSL certificate expiration dates for any domain using the SSL Checker node from customJS. It automatically updates a Google Sheet with the number of days left until expiry and sends a Slack notification when certificates are about to expire.  

  What this workflow does

  Input** a list of domains from Google Sheets.  
  Check** each domain’s SSL certificate details, including expiration date and days left.  
  Update** the Google Sheet with the latest SSL expiry information.  
  Notify** via Slack if any certificate is expiring soon (e.g., less than 8 days).  

  Requirements

  CustomJS API key** for SSL checking.  
  Google Sheets API credentials** for reading/updating domain data.  
  Slack API credentials** (optional, for notifications).  

  Workflow Steps

  Schedule Trigger  
     ⏰ Starts the workflow automatically (weekly by default, configurable).  

  Google Sheets (Read Rows)  
     📄 Retrieves the list of domains from your Google Sheet.  

  CustomJS - Check SSL  
     🔐 Fetches SSL certificate details for each domain.  
     Returns JSON output with fields such as expires and daysLeft.  

  Google Sheets (Update Rows)  
     📝 Updates the sheet with the current number of days left until certificate expiry.  

  Check Days Left Threshold (formerly "If" node)  
     ⚠️ Evaluates whether the certificate expires within the threshold (e.g., &lt; 8 days).  

  Slack Node  
     💬 Sends a notification message if a certificate is close to expiration.  

     Example Slack alert message:  

        ⏰ Reminder: SSL certificate of www.example.com 
     will expire in 7 days.
  SSL Checker node JSON output

  {
    "output": {
      "domain": "example.com",
      "valid": true,
      "expires": "2025-12-31T23:59:59.000Z",
      "issuer": "Let's Encrypt",
      "daysLeft": 5
    }
  }

nodes_used:
  ["n8n-nodes-base.googleSheets","n8n-nodes-base.slack","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.if","@custom-js/n8n-nodes-pdf-toolkit-v2.pdfToolkit","n8n-nodes-base.googleSheets"]

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metadata_json:
  {"categories":["Security","Data Processing"],"complexity":"medium","use_cases":["Monitor SSL certificate expiry","Automate security alerts","Track domain certificates"],"estimated_setup_minutes":20,"required_services":["Google Sheets API","Slack API","SSL Checker API","PDF Toolkit"],"key_features":["Scheduled domain checks","Conditional email/Slack alerts","Spreadsheet data management","Custom JavaScript logic"],"target_audience":["DevOps Engineers","System Administrators","Security Teams"]}


name: 🗲 Serve Custom Websites (HTML Webpages) with Webhooks
author_name: Lucas Peyrin
author_username: lucaspeyrin
categories: []
created_at: 2025-06-23T23:51:48.249Z
updated_at: 2025-06-23T23:51:48.249Z
url: https://n8n.io/workflows/5173
scraped_at: 2026-05-02 08:04:49
metadata_generated_at: 2026-05-02 08:36:20
description:
  How it works

  This workflow demonstrates how to use n8n to serve a complete, styled HTML webpage. It acts as a mini web server, responding to browser requests with your custom HTML content.

  Webhook Trigger: The workflow starts with a Webhook node configured to listen for GET requests on a specific path. When you visit this node's Production URL in a browser, it triggers the workflow.
  Respond with HTML: The Respond to Webhook node is configured to send a response back to the browser.
      Content-Type Header: It sets a crucial response header, Content-Type: text/html, which tells the browser to render the response as a webpage, not just plain text.
      HTML Body: The entire HTML, CSS, and JavaScript for the webpage is pasted directly into the Body field of this node.

  When activated, visiting the webhook URL will instantly display the custom webpage.

  Set up steps

  Setup time: &lt; 1 minute

  This workflow is ready to use out-of-the-box.

  Activate the workflow.
  Open the Your WebPage (Webhook) node and copy its Production URL.
  Paste the URL into your browser to see the live tutorial page.
  To use your own HTML, simply open the Site (Respond to Webhook) node and replace the content in the Body field with your own code.

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

workflow_json_compressed:
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metadata_json:
  {"categories":["Web Development","Data Processing","API Management"],"complexity":"medium","use_cases":["serve custom HTML pages","dynamically deliver website content","build simple web servers","host static webpages"],"estimated_setup_minutes":10,"required_services":["webhook","respond to webhook","http"],"key_features":["triggers on get requests","returns styled html content","configurable url path","mini web server simulation"],"target_audience":["developers","web administrators"]}


name: 🗲 Creating a Secure Webhook - MUST HAVE
author_name: Lucas Peyrin
author_username: lucaspeyrin
categories: []
created_at: 2025-06-24T00:39:28.426Z
updated_at: 2025-06-24T00:39:28.426Z
url: https://n8n.io/workflows/5174
scraped_at: 2026-05-02 08:04:50
metadata_generated_at: 2026-05-02 08:36:19
description:
  How it works

  This workflow demonstrates a fundamental pattern for securing a webhook by requiring an API key. It acts as a gatekeeper, checking for a valid key in the request header before allowing the request to proceed.

  Incoming Request: The Secured Webhook node receives an incoming POST request. It expects an API key to be sent in the x-api-key header.
  API Key Verification:
      The Check API Key node takes the key from the incoming request's header.
      It then makes an internal HTTP request to a second webhook (Get API Key) which acts as a mock database.
      This second webhook retrieves a list of registered API keys (from the Registered API Keys node) and filters it to find a match for the key that was provided.
  Conditional Response:
      If a match is found, the API Key Identified node routes the execution to the "success" path, returning a 200 OK response with the identified user's ID.
      If no match is found, it routes to the "unauthorized" path, returning a 401 Unauthorized error.

  This pattern separates the public-facing endpoint from the data source, which is a good security practice.

  Set up steps

  Setup time: ~2 minutes

  This workflow is designed to be a self-contained example.

  Set up Credentials: This workflow uses "Header Auth" for its internal communication. Go to Credentials and create a new Header Auth credential. You can use any name and value (e.g., Name: X-N8N-Auth, Value: my-secret-password). Select this credential in all four webhook/HTTP Request nodes.
  Add Your API Keys: Open the Registered API Keys node. This is your mock database. Edit the array to include the user_id and api_key pairs you want to authorize.
  Activate the workflow.
  Test it: Use the Test Secure Webhook node to send a request.
      Try it with a valid key from your list to see the success response.
      Change the x-api-key header to an invalid key to see the 401 Unauthorized error.

  For Production: Replace the mock database part of this workflow (the Get API Key webhook and Registered API Keys node) with a real database node like Supabase, Postgres, or Baserow to look up keys.

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

workflow_json_compressed:
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metadata_json:
  {"categories":["DevOps","API Security"],"complexity":"simple","use_cases":["secure webhooks","api key validation","request filtering"],"estimated_setup_minutes":5,"required_services":[],"key_features":["header validation","node pattern for security","webhook protection"],"target_audience":["devops engineers","api developers"]}


name: 🛠️ Microsoft To Do Tool MCP Server 💪 all 15 operations
author_name: David Ashby
author_username: cfomodz
categories: []
created_at: 2025-06-24T03:18:06.681Z
updated_at: 2025-06-24T03:18:06.681Z
url: https://n8n.io/workflows/5177
scraped_at: 2026-05-02 08:04:51
metadata_generated_at: 2026-05-02 08:36:21
description:
  Need help? Want access to this workflow + many more paid workflows + live Q&A sessions with a top verified n8n creator?

  Join the community

  Complete MCP server exposing all Microsoft To Do Tool operations to AI agents. Zero configuration needed - all 15 operations pre-built.

  ⚡ Quick Setup

  Import this workflow into your n8n instance
  Activate the workflow to start your MCP server
  Copy the webhook URL from the MCP trigger node
  Connect AI agents using the MCP URL

  🔧 How it Works

  • MCP Trigger: Serves as your server endpoint for AI agent requests
  • Tool Nodes: Pre-configured for every Microsoft To Do Tool operation
  • AI Expressions: Automatically populate parameters via $fromAI() placeholders
  • Native Integration: Uses official n8n Microsoft To Do Tool tool with full error handling

  📋 Available Operations (15 total)

  Every possible Microsoft To Do Tool operation is included:

  🔧 Linkedresource (5 operations)

  • Create a linked resource
  • Delete a linked resource
  • Get a linked resource
  • Get many linked resources
  • Update a linked resource

  📝 List (5 operations)

  • Create a list
  • Delete a list
  • Get a list
  • Get many lists
  • Update a list

  🔧 Task (5 operations)

  • Create a task
  • Delete a task
  • Get a task
  • Get many tasks
  • Update a task

  🤖 AI Integration

  Parameter Handling: AI agents automatically provide values for:
  • Resource IDs and identifiers
  • Search queries and filters
  • Content and data payloads
  • Configuration options

  Response Format: Native Microsoft To Do Tool API responses with full data structure

  Error Handling: Built-in n8n error management and retry logic

  💡 Usage Examples

  Connect this MCP server to any AI agent or workflow:

  • Claude Desktop: Add MCP server URL to configuration
  • Custom AI Apps: Use MCP URL as tool endpoint
  • Other n8n Workflows: Call MCP tools from any workflow
  • API Integration: Direct HTTP calls to MCP endpoints

  ✨ Benefits

  • Complete Coverage: Every Microsoft To Do Tool operation available
  • Zero Setup: No parameter mapping or configuration needed
  • AI-Ready: Built-in $fromAI() expressions for all parameters
  • Production Ready: Native n8n error handling and logging
  • Extensible: Easily modify or add custom logic

  &gt; 🆓 Free for community use! Ready to deploy in under 2 minutes.

nodes_used:
  ["n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.mcpTrigger","n8n-nodes-base.microsoftToDoTool","n8n-nodes-base.microsoftToDoTool","n8n-nodes-base.microsoftToDoTool","n8n-nodes-base.microsoftToDoTool","n8n-nodes-base.microsoftToDoTool","n8n-nodes-base.stickyNote","n8n-nodes-base.microsoftToDoTool","n8n-nodes-base.microsoftToDoTool","n8n-nodes-base.microsoftToDoTool","n8n-nodes-base.microsoftToDoTool","n8n-nodes-base.microsoftToDoTool","n8n-nodes-base.stickyNote","n8n-nodes-base.microsoftToDoTool","n8n-nodes-base.microsoftToDoTool","n8n-nodes-base.microsoftToDoTool","n8n-nodes-base.microsoftToDoTool","n8n-nodes-base.microsoftToDoTool","n8n-nodes-base.stickyNote"]

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metadata_json:
  {"categories":["AI/ML","DevOps"],"complexity":"medium","use_cases":["enable AI agents","access Microsoft To Do","manage tasks programmatically"],"estimated_setup_minutes":5,"required_services":["Microsoft To Do"],"key_features":["15 pre-built operations","zero configuration","MCP server integration"],"target_audience":["developers","AI engineers"]}


name: 🛠️ Microsoft SharePoint Tool MCP Server 💪 all 11 operations
author_name: David Ashby
author_username: cfomodz
categories: []
created_at: 2025-06-24T03:52:04.362Z
updated_at: 2025-06-24T03:52:04.362Z
url: https://n8n.io/workflows/5178
scraped_at: 2026-05-02 08:04:50
metadata_generated_at: 2026-05-02 08:36:21
description:
  Need help? Want access to this workflow + many more paid workflows + live Q&A sessions with a top verified n8n creator?

  Join the community

  Complete MCP server exposing all Microsoft SharePoint Tool operations to AI agents. Zero configuration needed - all 11 operations pre-built.

  ⚡ Quick Setup

  Import this workflow into your n8n instance
  Activate the workflow to start your MCP server
  Copy the webhook URL from the MCP trigger node
  Connect AI agents using the MCP URL

  🔧 How it Works

  • MCP Trigger: Serves as your server endpoint for AI agent requests
  • Tool Nodes: Pre-configured for every Microsoft SharePoint Tool operation
  • AI Expressions: Automatically populate parameters via $fromAI() placeholders
  • Native Integration: Uses official n8n Microsoft SharePoint Tool tool with full error handling

  📋 Available Operations (11 total)

  Every possible Microsoft SharePoint Tool operation is included:

  📄 File (3 operations)

  • Download file
  • Update file
  • Upload file

  🔧 Item (6 operations)

  • Create item in a list
  • Create or update item (upsert)
  • Delete an item
  • Get an item
  • Get many items
  • Update item in a list

  📝 List (2 operations)

  • Get list
  • Get many lists

  🤖 AI Integration

  Parameter Handling: AI agents automatically provide values for:
  • Resource IDs and identifiers
  • Search queries and filters
  • Content and data payloads
  • Configuration options

  Response Format: Native Microsoft SharePoint Tool API responses with full data structure

  Error Handling: Built-in n8n error management and retry logic

  💡 Usage Examples

  Connect this MCP server to any AI agent or workflow:

  • Claude Desktop: Add MCP server URL to configuration
  • Custom AI Apps: Use MCP URL as tool endpoint
  • Other n8n Workflows: Call MCP tools from any workflow
  • API Integration: Direct HTTP calls to MCP endpoints

  ✨ Benefits

  • Complete Coverage: Every Microsoft SharePoint Tool operation available
  • Zero Setup: No parameter mapping or configuration needed
  • AI-Ready: Built-in $fromAI() expressions for all parameters
  • Production Ready: Native n8n error handling and logging
  • Extensible: Easily modify or add custom logic

  &gt; 🆓 Free for community use! Ready to deploy in under 2 minutes.

nodes_used:
  ["n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.mcpTrigger","n8n-nodes-base.microsoftSharePointTool","n8n-nodes-base.microsoftSharePointTool","n8n-nodes-base.microsoftSharePointTool","n8n-nodes-base.stickyNote","n8n-nodes-base.microsoftSharePointTool","n8n-nodes-base.microsoftSharePointTool","n8n-nodes-base.microsoftSharePointTool","n8n-nodes-base.microsoftSharePointTool","n8n-nodes-base.microsoftSharePointTool","n8n-nodes-base.microsoftSharePointTool","n8n-nodes-base.stickyNote","n8n-nodes-base.microsoftSharePointTool","n8n-nodes-base.microsoftSharePointTool","n8n-nodes-base.stickyNote"]

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metadata_json:
  {"categories":["Data Processing","DevOps"],"complexity":"medium","use_cases":["integrate SharePoint with AI agents","automate file operations via MCP","configure Microsoft SharePoint tools"],"estimated_setup_minutes":5,"required_services":["Microsoft SharePoint","n8n MCP server"],"key_features":["exposes all 11 SharePoint operations","zero configuration required","ready for AI agent integration"],"target_audience":["developers","IT administrators"]}


name: 🛠️ Microsoft OneDrive Tool MCP Server 💪 all 14 operations
author_name: David Ashby
author_username: cfomodz
categories: []
created_at: 2025-06-24T04:04:16.104Z
updated_at: 2025-06-24T04:04:16.104Z
url: https://n8n.io/workflows/5179
scraped_at: 2026-05-02 08:04:50
metadata_generated_at: 2026-05-02 08:36:21
description:
  Need help? Want access to this workflow + many more paid workflows + live Q&A sessions with a top verified n8n creator?

  Join the community

  Complete MCP server exposing all Microsoft OneDrive Tool operations to AI agents. Zero configuration needed - all 14 operations pre-built.

  ⚡ Quick Setup

  Import this workflow into your n8n instance
  Activate the workflow to start your MCP server
  Copy the webhook URL from the MCP trigger node
  Connect AI agents using the MCP URL

  🔧 How it Works

  • MCP Trigger: Serves as your server endpoint for AI agent requests
  • Tool Nodes: Pre-configured for every Microsoft OneDrive Tool operation
  • AI Expressions: Automatically populate parameters via $fromAI() placeholders
  • Native Integration: Uses official n8n Microsoft OneDrive Tool tool with full error handling

  📋 Available Operations (14 total)

  Every possible Microsoft OneDrive Tool operation is included:

  📄 File (8 operations)

  • Copy a file
  • Delete a file
  • Download a file
  • Get a file
  • Rename a file
  • Search a file
  • Share a file
  • Upload a file

  📁 Folder (6 operations)

  • Create a folder
  • Delete a folder
  • Get items in a folder
  • Rename a folder
  • Search a folder
  • Share a folder

  🤖 AI Integration

  Parameter Handling: AI agents automatically provide values for:
  • Resource IDs and identifiers
  • Search queries and filters
  • Content and data payloads
  • Configuration options

  Response Format: Native Microsoft OneDrive Tool API responses with full data structure

  Error Handling: Built-in n8n error management and retry logic

  💡 Usage Examples

  Connect this MCP server to any AI agent or workflow:

  • Claude Desktop: Add MCP server URL to configuration
  • Custom AI Apps: Use MCP URL as tool endpoint
  • Other n8n Workflows: Call MCP tools from any workflow
  • API Integration: Direct HTTP calls to MCP endpoints

  ✨ Benefits

  • Complete Coverage: Every Microsoft OneDrive Tool operation available
  • Zero Setup: No parameter mapping or configuration needed
  • AI-Ready: Built-in $fromAI() expressions for all parameters
  • Production Ready: Native n8n error handling and logging
  • Extensible: Easily modify or add custom logic

  &gt; 🆓 Free for community use! Ready to deploy in under 2 minutes.

nodes_used:
  ["n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.mcpTrigger","n8n-nodes-base.microsoftOneDriveTool","n8n-nodes-base.microsoftOneDriveTool","n8n-nodes-base.microsoftOneDriveTool","n8n-nodes-base.microsoftOneDriveTool","n8n-nodes-base.microsoftOneDriveTool","n8n-nodes-base.microsoftOneDriveTool","n8n-nodes-base.microsoftOneDriveTool","n8n-nodes-base.microsoftOneDriveTool","n8n-nodes-base.stickyNote","n8n-nodes-base.microsoftOneDriveTool","n8n-nodes-base.microsoftOneDriveTool","n8n-nodes-base.microsoftOneDriveTool","n8n-nodes-base.microsoftOneDriveTool","n8n-nodes-base.microsoftOneDriveTool","n8n-nodes-base.microsoftOneDriveTool","n8n-nodes-base.stickyNote"]

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metadata_json:
  {"categories":["AI/ML","Data Processing","DevOps"],"complexity":"medium","use_cases":["Exposure of Microsoft OneDrive operations to AI agents","Seamless integration of OneDrive with MCP servers","Zero-configuration access to OneDrive tools","AI agent tool calling"],"estimated_setup_minutes":30,"required_services":["microsoft onedrive"],"key_features":["prebuilt operations","mcp protocol support","automated access"],"target_audience":["ai developers","integrators","devops engineers"]}


name: 🛠️ Microsoft Graph Security Tool MCP Server 💪 all 5 operations
author_name: David Ashby
author_username: cfomodz
categories: []
created_at: 2025-06-24T04:07:11.669Z
updated_at: 2025-06-24T04:07:11.669Z
url: https://n8n.io/workflows/5180
scraped_at: 2026-05-02 08:04:51
metadata_generated_at: 2026-05-02 08:36:21
description:
  Need help? Want access to this workflow + many more paid workflows + live Q&A sessions with a top verified n8n creator?

  Join the community

  Complete MCP server exposing all Microsoft Graph Security Tool operations to AI agents. Zero configuration needed - all 5 operations pre-built.

  ⚡ Quick Setup

  Import this workflow into your n8n instance
  Activate the workflow to start your MCP server
  Copy the webhook URL from the MCP trigger node
  Connect AI agents using the MCP URL

  🔧 How it Works

  • MCP Trigger: Serves as your server endpoint for AI agent requests
  • Tool Nodes: Pre-configured for every Microsoft Graph Security Tool operation
  • AI Expressions: Automatically populate parameters via $fromAI() placeholders
  • Native Integration: Uses official n8n Microsoft Graph Security Tool tool with full error handling

  📋 Available Operations (5 total)

  Every possible Microsoft Graph Security Tool operation is included:

  🔧 Securescore (2 operations)

  • Get a secure score
  • Get many secure scores

  🔧 Securescorecontrolprofile (3 operations)

  • Get a secure score control profile
  • Get many secure score control profiles
  • Update a secure score control profile

  🤖 AI Integration

  Parameter Handling: AI agents automatically provide values for:
  • Resource IDs and identifiers
  • Search queries and filters
  • Content and data payloads
  • Configuration options

  Response Format: Native Microsoft Graph Security Tool API responses with full data structure

  Error Handling: Built-in n8n error management and retry logic

  💡 Usage Examples

  Connect this MCP server to any AI agent or workflow:

  • Claude Desktop: Add MCP server URL to configuration
  • Custom AI Apps: Use MCP URL as tool endpoint
  • Other n8n Workflows: Call MCP tools from any workflow
  • API Integration: Direct HTTP calls to MCP endpoints

  ✨ Benefits

  • Complete Coverage: Every Microsoft Graph Security Tool operation available
  • Zero Setup: No parameter mapping or configuration needed
  • AI-Ready: Built-in $fromAI() expressions for all parameters
  • Production Ready: Native n8n error handling and logging
  • Extensible: Easily modify or add custom logic

  &gt; 🆓 Free for community use! Ready to deploy in under 2 minutes.

nodes_used:
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metadata_json:
  {"categories":["DevOps","Security","AI/ML"],"complexity":"complex","use_cases":["Secure Microsoft Graph integration","AI agent tool access","Security operations automation","MCP server configuration","Azure security management"],"estimated_setup_minutes":5,"required_services":["Microsoft Graph","Microsoft 365","Azure Active Directory"],"key_features":["All 5 Security Tool operations","Zero configuration required","Pre-built MCP server access","AI agent integration ready","Webhook-triggered execution"],"target_audience":["DevOps engineers","Security administrators","AI developers"]}


name: 🛠️ Microsoft Entra ID Tool MCP Server 💪 all 12 operations
author_name: David Ashby
author_username: cfomodz
categories: []
created_at: 2025-06-24T04:11:48.396Z
updated_at: 2025-06-24T04:11:48.396Z
url: https://n8n.io/workflows/5181
scraped_at: 2026-05-02 08:04:51
metadata_generated_at: 2026-05-02 08:36:21
description:
  Need help? Want access to this workflow + many more paid workflows + live Q&A sessions with a top verified n8n creator?

  Join the community

  Complete MCP server exposing all Microsoft Entra ID Tool operations to AI agents. Zero configuration needed - all 12 operations pre-built.

  ⚡ Quick Setup

  Import this workflow into your n8n instance
  Activate the workflow to start your MCP server
  Copy the webhook URL from the MCP trigger node
  Connect AI agents using the MCP URL

  🔧 How it Works

  • MCP Trigger: Serves as your server endpoint for AI agent requests
  • Tool Nodes: Pre-configured for every Microsoft Entra ID Tool operation
  • AI Expressions: Automatically populate parameters via $fromAI() placeholders
  • Native Integration: Uses official n8n Microsoft Entra ID Tool tool with full error handling

  📋 Available Operations (12 total)

  Every possible Microsoft Entra ID Tool operation is included:

  🔧 Group (5 operations)

  • Create group
  • Delete group
  • Get group
  • Get many groups
  • Update group

  👤 User (7 operations)

  • Add user to group
  • Create user
  • Delete user
  • Get user
  • Get many users
  • Remove user from group
  • Update user

  🤖 AI Integration

  Parameter Handling: AI agents automatically provide values for:
  • Resource IDs and identifiers
  • Search queries and filters
  • Content and data payloads
  • Configuration options

  Response Format: Native Microsoft Entra ID Tool API responses with full data structure

  Error Handling: Built-in n8n error management and retry logic

  💡 Usage Examples

  Connect this MCP server to any AI agent or workflow:

  • Claude Desktop: Add MCP server URL to configuration
  • Custom AI Apps: Use MCP URL as tool endpoint
  • Other n8n Workflows: Call MCP tools from any workflow
  • API Integration: Direct HTTP calls to MCP endpoints

  ✨ Benefits

  • Complete Coverage: Every Microsoft Entra ID Tool operation available
  • Zero Setup: No parameter mapping or configuration needed
  • AI-Ready: Built-in $fromAI() expressions for all parameters
  • Production Ready: Native n8n error handling and logging
  • Extensible: Easily modify or add custom logic

  &gt; 🆓 Free for community use! Ready to deploy in under 2 minutes.

nodes_used:
  ["n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.mcpTrigger","n8n-nodes-base.microsoftEntraTool","n8n-nodes-base.microsoftEntraTool","n8n-nodes-base.microsoftEntraTool","n8n-nodes-base.microsoftEntraTool","n8n-nodes-base.microsoftEntraTool","n8n-nodes-base.stickyNote","n8n-nodes-base.microsoftEntraTool","n8n-nodes-base.microsoftEntraTool","n8n-nodes-base.microsoftEntraTool","n8n-nodes-base.microsoftEntraTool","n8n-nodes-base.microsoftEntraTool","n8n-nodes-base.microsoftEntraTool","n8n-nodes-base.microsoftEntraTool","n8n-nodes-base.stickyNote"]

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metadata_json:
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name: 🛠️ Microsoft Dynamics CRM Tool MCP Server 💪 all 5 operations
author_name: David Ashby
author_username: cfomodz
categories: []
created_at: 2025-06-24T04:15:10.009Z
updated_at: 2025-06-24T04:15:10.009Z
url: https://n8n.io/workflows/5182
scraped_at: 2026-05-02 08:04:51
metadata_generated_at: 2026-05-02 08:36:21
description:
  Need help? Want access to this workflow + many more paid workflows + live Q&A sessions with a top verified n8n creator?

  Join the community

  Complete MCP server exposing all Microsoft Dynamics CRM Tool operations to AI agents. Zero configuration needed - all 5 operations pre-built.

  ⚡ Quick Setup

  Import this workflow into your n8n instance
  Activate the workflow to start your MCP server
  Copy the webhook URL from the MCP trigger node
  Connect AI agents using the MCP URL

  🔧 How it Works

  • MCP Trigger: Serves as your server endpoint for AI agent requests
  • Tool Nodes: Pre-configured for every Microsoft Dynamics CRM Tool operation
  • AI Expressions: Automatically populate parameters via $fromAI() placeholders
  • Native Integration: Uses official n8n Microsoft Dynamics CRM Tool tool with full error handling

  📋 Available Operations (5 total)

  Every possible Microsoft Dynamics CRM Tool operation is included:

  👤 Account (5 operations)

  • Create an account
  • Delete an account
  • Get an account
  • Get many accounts
  • Update an account

  🤖 AI Integration

  Parameter Handling: AI agents automatically provide values for:
  • Resource IDs and identifiers
  • Search queries and filters
  • Content and data payloads
  • Configuration options

  Response Format: Native Microsoft Dynamics CRM Tool API responses with full data structure

  Error Handling: Built-in n8n error management and retry logic

  💡 Usage Examples

  Connect this MCP server to any AI agent or workflow:

  • Claude Desktop: Add MCP server URL to configuration
  • Custom AI Apps: Use MCP URL as tool endpoint
  • Other n8n Workflows: Call MCP tools from any workflow
  • API Integration: Direct HTTP calls to MCP endpoints

  ✨ Benefits

  • Complete Coverage: Every Microsoft Dynamics CRM Tool operation available
  • Zero Setup: No parameter mapping or configuration needed
  • AI-Ready: Built-in $fromAI() expressions for all parameters
  • Production Ready: Native n8n error handling and logging
  • Extensible: Easily modify or add custom logic

  &gt; 🆓 Free for community use! Ready to deploy in under 2 minutes.

nodes_used:
  ["n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.mcpTrigger","n8n-nodes-base.microsoftDynamicsCrmTool","n8n-nodes-base.microsoftDynamicsCrmTool","n8n-nodes-base.microsoftDynamicsCrmTool","n8n-nodes-base.microsoftDynamicsCrmTool","n8n-nodes-base.microsoftDynamicsCrmTool","n8n-nodes-base.stickyNote"]

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metadata_json:
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name: 🛠️ Metabase Tool MCP Server 💪 all 10 operations
author_name: David Ashby
author_username: cfomodz
categories: []
created_at: 2025-06-24T04:18:32.872Z
updated_at: 2025-06-24T04:18:32.872Z
url: https://n8n.io/workflows/5183
scraped_at: 2026-05-02 08:04:51
metadata_generated_at: 2026-05-02 08:36:21
description:
  Need help? Want access to this workflow + many more paid workflows + live Q&A sessions with a top verified n8n creator?

  Join the community

  Complete MCP server exposing all Metabase Tool operations to AI agents. Zero configuration needed - all 10 operations pre-built.

  ⚡ Quick Setup

  Import this workflow into your n8n instance
  Activate the workflow to start your MCP server
  Copy the webhook URL from the MCP trigger node
  Connect AI agents using the MCP URL

  🔧 How it Works

  • MCP Trigger: Serves as your server endpoint for AI agent requests
  • Tool Nodes: Pre-configured for every Metabase Tool operation
  • AI Expressions: Automatically populate parameters via $fromAI() placeholders
  • Native Integration: Uses official n8n Metabase Tool tool with full error handling

  📋 Available Operations (10 total)

  Every possible Metabase Tool operation is included:

  🔧 Alerts (2 operations)

  • Get an alert
  • Get many alerts

  🔧 Databases (3 operations)

  • Add a databases
  • Get many databases
  • Get Fields a databases

  🔧 Metrics (2 operations)

  • Get a metric
  • Get many metrics

  🔧 Questions (3 operations)

  • Get a questions
  • Get many questions
  • Get the results from a question

  🤖 AI Integration

  Parameter Handling: AI agents automatically provide values for:
  • Resource IDs and identifiers
  • Search queries and filters
  • Content and data payloads
  • Configuration options

  Response Format: Native Metabase Tool API responses with full data structure

  Error Handling: Built-in n8n error management and retry logic

  💡 Usage Examples

  Connect this MCP server to any AI agent or workflow:

  • Claude Desktop: Add MCP server URL to configuration
  • Custom AI Apps: Use MCP URL as tool endpoint
  • Other n8n Workflows: Call MCP tools from any workflow
  • API Integration: Direct HTTP calls to MCP endpoints

  ✨ Benefits

  • Complete Coverage: Every Metabase Tool operation available
  • Zero Setup: No parameter mapping or configuration needed
  • AI-Ready: Built-in $fromAI() expressions for all parameters
  • Production Ready: Native n8n error handling and logging
  • Extensible: Easily modify or add custom logic

  &gt; 🆓 Free for community use! Ready to deploy in under 2 minutes.

nodes_used:
  ["n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.mcpTrigger","n8n-nodes-base.metabaseTool","n8n-nodes-base.metabaseTool","n8n-nodes-base.stickyNote","n8n-nodes-base.metabaseTool","n8n-nodes-base.metabaseTool","n8n-nodes-base.metabaseTool","n8n-nodes-base.stickyNote","n8n-nodes-base.metabaseTool","n8n-nodes-base.metabaseTool","n8n-nodes-base.stickyNote","n8n-nodes-base.metabaseTool","n8n-nodes-base.metabaseTool","n8n-nodes-base.metabaseTool","n8n-nodes-base.stickyNote"]

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metadata_json:
  {"categories":["AI/ML","Data Processing"],"complexity":"medium","use_cases":["Query databases with AI","Integrate Metabase tools","Enable AI agents data access","Build custom MCP servers","Automate BI tasks"],"estimated_setup_minutes":5,"required_services":["Metabase","MCP SDK"],"key_features":["All 10 Metabase operations","Zero configuration setup","MCP server integration","AI agent ready","Webhook trigger"],"target_audience":["developers","AI engineers","data analysts"]}


name: 🛠️ Mautic Tool MCP Server 💪 all 20 operations
author_name: David Ashby
author_username: cfomodz
categories: []
created_at: 2025-06-24T04:24:25.298Z
updated_at: 2025-06-24T04:24:25.298Z
url: https://n8n.io/workflows/5184
scraped_at: 2026-05-02 08:04:51
metadata_generated_at: 2026-05-02 08:36:21
description:
  Need help? Want access to this workflow + many more paid workflows + live Q&A sessions with a top verified n8n creator?

  Join the community

  Complete MCP server exposing all Mautic Tool operations to AI agents. Zero configuration needed - all 20 operations pre-built.

  ⚡ Quick Setup

  Import this workflow into your n8n instance
  Activate the workflow to start your MCP server
  Copy the webhook URL from the MCP trigger node
  Connect AI agents using the MCP URL

  🔧 How it Works

  • MCP Trigger: Serves as your server endpoint for AI agent requests
  • Tool Nodes: Pre-configured for every Mautic Tool operation
  • AI Expressions: Automatically populate parameters via $fromAI() placeholders
  • Native Integration: Uses official n8n Mautic Tool tool with full error handling

  📋 Available Operations (20 total)

  Every possible Mautic Tool operation is included:

  🔧 Campaigncontact (2 operations)

  • Add a campaign contact
  • Remove a campaign contact

  🔧 Company (5 operations)

  • Create a company
  • Delete a company
  • Get a company
  • Get many companies
  • Update a company

  🔧 Companycontact (2 operations)

  • Add a company contact
  • Remove a company contact

  📇 Contact (8 operations)

  • Create a contact
  • Delete a contact
  • Edit a contact's points
  • Add/remove contacts from/to the do not contact list
  • Get a contact
  • Get many contacts
  • Send email to a contact
  • Update a contact

  🔧 Contactsegment (2 operations)

  • Add a contact to a segment
  • Remove a contact from a segment

  🔧 Segmentemail (1 operations)

  • Send an email to a segment

  🤖 AI Integration

  Parameter Handling: AI agents automatically provide values for:
  • Resource IDs and identifiers
  • Search queries and filters
  • Content and data payloads
  • Configuration options

  Response Format: Native Mautic Tool API responses with full data structure

  Error Handling: Built-in n8n error management and retry logic

  💡 Usage Examples

  Connect this MCP server to any AI agent or workflow:

  • Claude Desktop: Add MCP server URL to configuration
  • Custom AI Apps: Use MCP URL as tool endpoint
  • Other n8n Workflows: Call MCP tools from any workflow
  • API Integration: Direct HTTP calls to MCP endpoints

  ✨ Benefits

  • Complete Coverage: Every Mautic Tool operation available
  • Zero Setup: No parameter mapping or configuration needed
  • AI-Ready: Built-in $fromAI() expressions for all parameters
  • Production Ready: Native n8n error handling and logging
  • Extensible: Easily modify or add custom logic

  &gt; 🆓 Free for community use! Ready to deploy in under 2 minutes.

nodes_used:
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metadata_json:
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name: 🛠️ Matrix Tool MCP Server 💪 all 11 operations
author_name: David Ashby
author_username: cfomodz
categories: []
created_at: 2025-06-24T04:27:37.150Z
updated_at: 2025-06-24T04:27:37.150Z
url: https://n8n.io/workflows/5185
scraped_at: 2026-05-02 08:04:51
metadata_generated_at: 2026-05-02 08:36:21
description:
  Need help? Want access to this workflow + many more paid workflows + live Q&A sessions with a top verified n8n creator?

  Join the community

  Complete MCP server exposing all Matrix Tool operations to AI agents. Zero configuration needed - all 11 operations pre-built.

  ⚡ Quick Setup

  Import this workflow into your n8n instance
  Activate the workflow to start your MCP server
  Copy the webhook URL from the MCP trigger node
  Connect AI agents using the MCP URL

  🔧 How it Works

  • MCP Trigger: Serves as your server endpoint for AI agent requests
  • Tool Nodes: Pre-configured for every Matrix Tool operation
  • AI Expressions: Automatically populate parameters via $fromAI() placeholders
  • Native Integration: Uses official n8n Matrix Tool tool with full error handling

  📋 Available Operations (11 total)

  Every possible Matrix Tool operation is included:

  👤 Account (1 operations)

  • Get the current user's account information

  📅 Event (1 operations)

  • Get an event by ID

  🔧 Media (1 operations)

  • Upload media to a chatroom

  💬 Message (2 operations)

  • Create a message
  • Get many messages

  🔧 Room (5 operations)

  • Create a room
  • Invite a room
  • Join a room
  • Kick a user from a room
  • Leave a room

  🔧 Roommember (1 operations)

  • Get many room members

  🤖 AI Integration

  Parameter Handling: AI agents automatically provide values for:
  • Resource IDs and identifiers
  • Search queries and filters
  • Content and data payloads
  • Configuration options

  Response Format: Native Matrix Tool API responses with full data structure

  Error Handling: Built-in n8n error management and retry logic

  💡 Usage Examples

  Connect this MCP server to any AI agent or workflow:

  • Claude Desktop: Add MCP server URL to configuration
  • Custom AI Apps: Use MCP URL as tool endpoint
  • Other n8n Workflows: Call MCP tools from any workflow
  • API Integration: Direct HTTP calls to MCP endpoints

  ✨ Benefits

  • Complete Coverage: Every Matrix Tool operation available
  • Zero Setup: No parameter mapping or configuration needed
  • AI-Ready: Built-in $fromAI() expressions for all parameters
  • Production Ready: Native n8n error handling and logging
  • Extensible: Easily modify or add custom logic

  &gt; 🆓 Free for community use! Ready to deploy in under 2 minutes.

nodes_used:
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metadata_json:
  {"categories":["AI/ML","Communication","Data Processing"],"complexity":"medium","use_cases":["expose Matrix operations to AI agents","integrate Matrix tools via MCP","configure AI tool access"],"estimated_setup_minutes":20,"required_services":["Matrix Tool"],"key_features":["pre-built MCP server","all 11 Matrix operations","zero configuration needed","AI agent integration"],"target_audience":["AI developers","integration engineers","admins"]}


