# Firecrawl MCP Server
A Model Context Protocol (MCP) server that brings [Firecrawl](https://github.com/firecrawl/firecrawl) to MCP-compatible AI agents — search, scrape, and interact with the live web for clean, agent-ready context.
> Big thanks to [@vrknetha](https://github.com/vrknetha), [@knacklabs](https://www.knacklabs.ai) for the initial implementation!
## Features
- Search the web and get full page content
- Scrape any URL into clean, structured data
- Interact with pages — click, navigate, and operate
- Deep research with autonomous agent
- Automatic retries and rate limiting
- Cloud and self-hosted support
- SSE support
> Play around with [our MCP Server on MCP.so's playground](https://mcp.so/playground?server=firecrawl-mcp-server) or on [Klavis AI](https://www.klavis.ai/mcp-servers).
## Installation
### Hosted MCP (keyless free tier)
Connect to the remote hosted server with no setup:
```
https://mcp.firecrawl.dev/v2/mcp
```
On the keyless free tier, `scrape`, `search`, and `interact` work without an API key (rate-limited). Other tools such as `crawl`, `map`, `agent`, and `extract` still need a key.
Prefer an API key or OAuth whenever the human can sign up. It unlocks the full tool set and higher limits. With a key, use:
```
https://mcp.firecrawl.dev/{FIRECRAWL_API_KEY}/v2/mcp
```
See the [MCP server docs](https://docs.firecrawl.dev/mcp-server) and the [agent onboarding guide](https://www.firecrawl.dev/agent-onboarding/SKILL.md) for setup details.
### Running with npx
```bash
env FIRECRAWL_API_KEY=fc-YOUR_API_KEY npx -y firecrawl-mcp
```
### Manual Installation
```bash
npm install -g firecrawl-mcp
```
### Running on Cursor
Configuring Cursor 🖥️
Note: Requires Cursor version 0.45.6+
For the most up-to-date configuration instructions, please refer to the official Cursor documentation on configuring MCP servers:
[Cursor MCP Server Configuration Guide](https://docs.cursor.com/context/model-context-protocol#configuring-mcp-servers)
To configure Firecrawl MCP in Cursor **v0.48.6**
1. Open Cursor Settings
2. Go to Features > MCP Servers
3. Click "+ Add new global MCP server"
4. Enter the following code:
```json
{
"mcpServers": {
"firecrawl-mcp": {
"command": "npx",
"args": ["-y", "firecrawl-mcp"],
"env": {
"FIRECRAWL_API_KEY": "YOUR-API-KEY"
}
}
}
}
```
To configure Firecrawl MCP in Cursor **v0.45.6**
1. Open Cursor Settings
2. Go to Features > MCP Servers
3. Click "+ Add New MCP Server"
4. Enter the following:
- Name: "firecrawl-mcp" (or your preferred name)
- Type: "command"
- Command: `env FIRECRAWL_API_KEY=your-api-key npx -y firecrawl-mcp`
> If you are using Windows and are running into issues, try `cmd /c "set FIRECRAWL_API_KEY=your-api-key && npx -y firecrawl-mcp"`
Replace `your-api-key` with your Firecrawl API key. If you don't have one yet, you can create an account and get it from https://www.firecrawl.dev/app/api-keys
After adding, refresh the MCP server list to see the new tools. The Composer Agent will automatically use Firecrawl MCP when appropriate, but you can explicitly request it by describing your web scraping needs. Access the Composer via Command+L (Mac), select "Agent" next to the submit button, and enter your query.
### Running on Windsurf
Add this to your `./codeium/windsurf/model_config.json`:
```json
{
"mcpServers": {
"mcp-server-firecrawl": {
"command": "npx",
"args": ["-y", "firecrawl-mcp"],
"env": {
"FIRECRAWL_API_KEY": "YOUR_API_KEY"
}
}
}
}
```
### Running with Streamable HTTP Local Mode
To run the server using Streamable HTTP locally instead of the default stdio transport:
```bash
env HTTP_STREAMABLE_SERVER=true FIRECRAWL_API_KEY=fc-YOUR_API_KEY npx -y firecrawl-mcp
```
Use the url: http://localhost:3000/mcp
### Installing via Smithery (Legacy)
To install Firecrawl for Claude Desktop automatically via [Smithery](https://smithery.ai/server/@mendableai/mcp-server-firecrawl):
```bash
npx -y @smithery/cli install @mendableai/mcp-server-firecrawl --client claude
```
### Running on VS Code
For one-click installation, click one of the install buttons below...
[](https://insiders.vscode.dev/redirect/mcp/install?name=firecrawl&inputs=%5B%7B%22type%22%3A%22promptString%22%2C%22id%22%3A%22apiKey%22%2C%22description%22%3A%22Firecrawl%20API%20Key%22%2C%22password%22%3Atrue%7D%5D&config=%7B%22command%22%3A%22npx%22%2C%22args%22%3A%5B%22-y%22%2C%22firecrawl-mcp%22%5D%2C%22env%22%3A%7B%22FIRECRAWL_API_KEY%22%3A%22%24%7Binput%3AapiKey%7D%22%7D%7D) [](https://insiders.vscode.dev/redirect/mcp/install?name=firecrawl&inputs=%5B%7B%22type%22%3A%22promptString%22%2C%22id%22%3A%22apiKey%22%2C%22description%22%3A%22Firecrawl%20API%20Key%22%2C%22password%22%3Atrue%7D%5D&config=%7B%22command%22%3A%22npx%22%2C%22args%22%3A%5B%22-y%22%2C%22firecrawl-mcp%22%5D%2C%22env%22%3A%7B%22FIRECRAWL_API_KEY%22%3A%22%24%7Binput%3AapiKey%7D%22%7D%7D&quality=insiders)
For manual installation, add the following JSON block to your User Settings (JSON) file in VS Code. You can do this by pressing `Ctrl + Shift + P` and typing `Preferences: Open User Settings (JSON)`.
```json
{
"mcp": {
"inputs": [
{
"type": "promptString",
"id": "apiKey",
"description": "Firecrawl API Key",
"password": true
}
],
"servers": {
"firecrawl": {
"command": "npx",
"args": ["-y", "firecrawl-mcp"],
"env": {
"FIRECRAWL_API_KEY": "${input:apiKey}"
}
}
}
}
}
```
Optionally, you can add it to a file called `.vscode/mcp.json` in your workspace. This will allow you to share the configuration with others:
```json
{
"inputs": [
{
"type": "promptString",
"id": "apiKey",
"description": "Firecrawl API Key",
"password": true
}
],
"servers": {
"firecrawl": {
"command": "npx",
"args": ["-y", "firecrawl-mcp"],
"env": {
"FIRECRAWL_API_KEY": "${input:apiKey}"
}
}
}
}
```
## Configuration
### Environment Variables
#### Required for Cloud API
- `FIRECRAWL_API_KEY`: Your Firecrawl API key
- Required when using cloud API (default)
- Optional when using self-hosted instance with `FIRECRAWL_API_URL`
- `FIRECRAWL_API_URL` (Optional): Custom API endpoint for self-hosted instances
- Example: `https://firecrawl.your-domain.com`
- If not provided, the cloud API will be used (requires API key)
#### MCP OAuth (Bearer access tokens)
Hosted Firecrawl can issue OAuth **access tokens** (`fco_…`) via the authorization server on [firecrawl.dev](https://firecrawl.dev). This MCP server forwards whichever credential it resolves to the Firecrawl API as `Authorization: Bearer …`.
- **HTTP stream transports** (`CLOUD_SERVICE=true`, `HTTP_STREAMABLE_SERVER=true`, or `SSE_LOCAL=true`): Clients should send `Authorization: Bearer ` on MCP requests. An OAuth bearer token takes precedence over `x-firecrawl-api-key` / `x-api-key` when both are present.
- **stdio:** Use `FIRECRAWL_OAUTH_TOKEN` for a static access token, or keep using `FIRECRAWL_API_KEY` for an API key.
Use **access** tokens (`fco_…`) only. Refresh tokens (`fcr_…`) must be exchanged at the token endpoint, not passed to the scrape/search API.
### Configuration Examples
For cloud API usage:
```bash
export FIRECRAWL_API_KEY=your-api-key
```
For self-hosted instance:
```bash
# Required for self-hosted
export FIRECRAWL_API_URL=https://firecrawl.your-domain.com
# Optional authentication for self-hosted
export FIRECRAWL_API_KEY=your-api-key # If your instance requires auth
```
### Usage with Claude Desktop
Add this to your `claude_desktop_config.json`:
```json
{
"mcpServers": {
"mcp-server-firecrawl": {
"command": "npx",
"args": ["-y", "firecrawl-mcp"],
"env": {
"FIRECRAWL_API_KEY": "YOUR_API_KEY_HERE"
}
}
}
}
```
## How to Choose a Tool
Use this guide to select the right tool for your task:
- **If you know the exact URL you want:** use **scrape** (with JSON format for structured data)
- **If you have multiple known URLs:** call **scrape** for each URL. If you specifically need one bulk API operation, use the Firecrawl API batch endpoint outside MCP.
- **If you need to discover URLs on a site:** use **map**
- **If you want to search the web for info:** use **search**
- **If you need complex research across multiple unknown sources:** use **agent**
- **If you want to analyze a whole site or section:** use **crawl** (with limits!)
- **If you need interactive browser automation** (click, type, navigate): use **interact** with a URL for a fresh page, or **scrape** + **interact** when you already scraped the page or need tighter scrape control
### Quick Reference Table
| Tool | Best for | Returns |
| ------------ | ---------------------------------------------- | ------------------------------ |
| scrape | Single page content | JSON (preferred) or markdown |
| interact | Interact with a URL or scraped page | Execution result + scrapeId for URL mode |
| map | Discovering URLs on a site | URL[] |
| crawl | Multi-page extraction (with limits) | final crawl status/data after internal polling |
| parse | Files and hosted upload refs | markdown, JSON, or document output |
| extract | Structured extraction from URLs | JSON structured data |
| search | Web search for info | results[] |
| agent | Complex multi-source research | JSON (structured data) |
| monitor | Recurring page checks | monitor/check metadata and diffs |
| research | Paper and GitHub repository research | research results and repo matches |
### Format Selection Guide
When using `scrape`, choose the right format:
- **JSON format (recommended for most cases):** Use when you need specific data from a page. Define a schema based on what you need to extract. This keeps responses small and avoids context window overflow.
- **Markdown format (use sparingly):** Only when you genuinely need the full page content, such as reading an entire article for summarization or analyzing page structure.
## Available Tools
### 1. Scrape Tool (`firecrawl_scrape`)
Scrape content from a single URL with advanced options.
**Best for:**
- Single page content extraction, when you know exactly which page contains the information.
**Not recommended for:**
- Extracting content from multiple pages (use repeated scrape calls for known URLs, or map + scrape to discover URLs first, or crawl for full page content)
- When you're unsure which page contains the information (use search)
**Common mistakes:**
- Passing a list of URLs to one scrape call. Call scrape once per URL in MCP. If you specifically need one bulk API operation, use the Firecrawl API batch endpoint outside MCP.
- Using markdown format by default (use JSON format to extract only what you need).
**Choosing the right format:**
- **JSON format (preferred):** For most use cases, use JSON format with a schema to extract only the specific data needed. This keeps responses focused and prevents context window overflow.
- **Markdown format:** Only when the task genuinely requires full page content (e.g., summarizing an entire article, analyzing page structure).
**Prompt Example:**
> "Get the product details from https://example.com/product."
**Usage Example (JSON format - preferred):**
```json
{
"name": "firecrawl_scrape",
"arguments": {
"url": "https://example.com/product",
"formats": [
{
"type": "json",
"prompt": "Extract the product information",
"schema": {
"type": "object",
"properties": {
"name": { "type": "string" },
"price": { "type": "number" },
"description": { "type": "string" }
},
"required": ["name", "price"]
}
}
]
}
}
```
**Usage Example (markdown format - when full content needed):**
```json
{
"name": "firecrawl_scrape",
"arguments": {
"url": "https://example.com/article",
"formats": ["markdown"],
"onlyMainContent": true
}
}
```
**Usage Example (branding format - extract brand identity):**
```json
{
"name": "firecrawl_scrape",
"arguments": {
"url": "https://example.com",
"formats": ["branding"]
}
}
```
**Branding format:** Extracts comprehensive brand identity (colors, fonts, typography, spacing, logo, UI components) for design analysis or style replication.
**Privacy:** Set `redactPII: true` to return content with personally identifiable information redacted.
**Returns:**
- JSON structured data, markdown, branding profile, or other formats as specified.
### 2. Map Tool (`firecrawl_map`)
Map a website to discover all indexed URLs on the site.
**Best for:**
- Discovering URLs on a website before deciding what to scrape
- Finding specific sections of a website
**Not recommended for:**
- When you already know which specific URL you need (use scrape)
- When you need the content of the pages (use scrape after mapping)
**Common mistakes:**
- Using crawl to discover URLs instead of map
**Prompt Example:**
> "List all URLs on example.com."
**Usage Example:**
```json
{
"name": "firecrawl_map",
"arguments": {
"url": "https://example.com"
}
}
```
**Returns:**
- Array of URLs found on the site
### 3. Search Tool (`firecrawl_search`)
Search the web and optionally extract content from search results.
**Best for:**
- Finding specific information across multiple websites, when you don't know which website has the information.
- When you need the most relevant content for a query
**Not recommended for:**
- When you already know which website to scrape (use scrape)
- When you need comprehensive coverage of a single website (use map or crawl)
**Common mistakes:**
- Using crawl or map for open-ended questions (use search instead)
**Usage Example:**
```json
{
"name": "firecrawl_search",
"arguments": {
"query": "latest AI research papers 2023",
"limit": 5,
"lang": "en",
"country": "us",
"scrapeOptions": {
"formats": ["markdown"],
"onlyMainContent": true,
"redactPII": true
}
}
}
```
**Returns:**
- Array of search results (with optional scraped content), plus an `id` field. Pass that `id` to `firecrawl_search_feedback` after you've used the results to refund 1 credit (search costs 2) and improve search quality.
**Prompt Example:**
> "Find the latest research papers on AI published in 2023."
### 3b. Search Feedback Tool (`firecrawl_search_feedback`)
Sends structured feedback on a previous `firecrawl_search` result. The first feedback per search id refunds 1 credit and improves Firecrawl's search quality. Idempotent per search id.
**Call this after every search you actually use** (or that didn't help). Bad/partial feedback with `missingContent` is just as valuable as good feedback.
**Opt out:** set `FIRECRAWL_NO_SEARCH_FEEDBACK=1` (or `FIRECRAWL_DISABLE_SEARCH_FEEDBACK=1`) in the environment when starting the MCP server. The `firecrawl_search_feedback` tool will not be registered, so agents can't call it. Team admins can also disable feedback server-side; in that case the tool is registered but always returns `feedbackErrorCode: "TEAM_OPTED_OUT"`.
**Most important field:** `missingContent`. It's an array of specific pieces of content the agent expected to find but did not. One entry per missing topic — these aggregate across teams and tell us what to index next.
**Daily refund cap (per team, per UTC day, default 100 credits).** Once a team's `creditsRefundedToday` reaches `dailyRefundCap`, further submissions still record feedback but no longer refund credits. The response sets `dailyCapReached: true`. Agents should stop calling this tool for the rest of the UTC day when they see that flag.
**Usage Example:**
```json
{
"name": "firecrawl_search_feedback",
"arguments": {
"searchId": "0193f6c5-1234-7890-abcd-1234567890ab",
"rating": "good",
"valuableSources": [
{
"url": "https://docs.firecrawl.dev/features/search",
"reason": "Most up-to-date description of /search."
}
],
"missingContent": [
{
"topic": "Pricing for the search endpoint",
"description": "No pricing tier table for /search specifically."
},
{ "topic": "Per-team rate limits" }
],
"querySuggestions": "Boost docs.firecrawl.dev for queries that mention 'firecrawl'"
}
}
```
**Returns:**
- `{ success, feedbackId, creditsRefunded, alreadySubmitted? }` JSON.
### 3c. Generic Feedback Tool (`firecrawl_feedback`)
Sends structured feedback for a completed v2 endpoint job through `/v2/feedback`.
Use this for endpoint-level feedback on `scrape`, `parse`, `map`, or `search`
jobs. For search-result quality specifically, prefer
`firecrawl_search_feedback` because it includes search-specific guidance.
Keep feedback concise: use issue codes, tags, short notes, URLs, page numbers,
and small metadata objects. Do not include raw scrape/parse outputs.
**Opt out:** set `FIRECRAWL_NO_ENDPOINT_FEEDBACK=1` (or `FIRECRAWL_DISABLE_ENDPOINT_FEEDBACK=1`) in the environment when starting the MCP server. The `firecrawl_feedback` tool will not be registered, so agents cannot call it.
**Usage Example:**
```json
{
"name": "firecrawl_feedback",
"arguments": {
"endpoint": "scrape",
"jobId": "0193f6c5-1234-7890-abcd-1234567890ab",
"rating": "partial",
"issues": ["missing_markdown"],
"tags": ["docs"],
"note": "The pricing table was missing from the markdown output.",
"url": "https://example.com/pricing",
"pageNumbers": [1],
"metadata": {
"format": "markdown"
}
}
}
```
**Returns:**
- `{ success, feedbackId, creditsRefunded, creditsRefundedToday?, dailyRefundCap?, dailyCapReached?, alreadySubmitted?, warning? }` JSON.
### 4. Crawl Tool (`firecrawl_crawl`)
Starts a crawl job, polls until it reaches a terminal state, and returns the final crawl status/data.
**Best for:**
- Extracting content from multiple related pages, when you need comprehensive coverage.
**Not recommended for:**
- Extracting content from a single page (use scrape)
- When token limits are a concern (use map + scrape for tighter control)
- When you need fast results (crawling can be slow)
**Warning:** Crawl responses can be very large and may exceed token limits. Limit the crawl depth and number of pages, or use map + scrape for tighter control.
**Common mistakes:**
- Setting limit or maxDiscoveryDepth too high (causes token overflow)
- Using crawl for a single page (use scrape instead)
**Prompt Example:**
> "Get all blog posts from the first two levels of example.com/blog."
**Usage Example:**
```json
{
"name": "firecrawl_crawl",
"arguments": {
"url": "https://example.com/blog/*",
"maxDiscoveryDepth": 2,
"limit": 100,
"allowExternalLinks": false,
"deduplicateSimilarURLs": true
}
}
```
**Returns:**
- Final crawl status and data after internal polling, including `id`, `status`, `completed`, `total`, `creditsUsed`, `expiresAt`, `next`, and `data`. Use the returned `id` with `firecrawl_check_crawl_status` if you need to re-check the job later.
### 5. Check Crawl Status (`firecrawl_check_crawl_status`)
Check the status and results of an existing crawl job by ID.
```json
{
"name": "firecrawl_check_crawl_status",
"arguments": {
"id": "550e8400-e29b-41d4-a716-446655440000"
}
}
```
**Returns:**
- Response includes the status of the crawl job:
### 6. Parse Tool (`firecrawl_parse`)
Parse local files or hosted upload references with Firecrawl's `/v2/parse` endpoint.
**Best for:** PDFs, Word documents, spreadsheets, HTML files, and other documents that need markdown or structured JSON output. Hosted MCP supports a two-step upload-ref flow; local direct file reads require a self-hosted `FIRECRAWL_API_URL`.
**Not recommended for:** Remote URLs (use scrape), multiple files in one call (call parse once per file), or browser-only actions such as screenshots and clicks.
**Hosted MCP flow:** Hosted MCP cannot read the caller's filesystem directly. Call `firecrawl_parse` with `filePath` to receive a short-lived upload command and `nextToolCall`, upload the file locally, then call `firecrawl_parse` again with the returned `uploadRef`. Minting the hosted upload URL requires Firecrawl auth or keyless eligibility. In local `npx firecrawl-mcp` mode, direct file parsing currently requires `FIRECRAWL_API_URL` pointing to a self-hosted Firecrawl API; a plain cloud API-key-only local server cannot read and upload files through this tool.
**Usage Example:**
```json
{
"name": "firecrawl_parse",
"arguments": {
"filePath": "/absolute/path/to/document.pdf",
"formats": ["markdown"],
"parsers": ["pdf"],
"zeroDataRetention": true
}
}
```
**Returns:** Parsed document content or hosted upload instructions with a `nextToolCall`.
### 7. Extract Tool (`firecrawl_extract`)
Extract structured information from web pages using LLM capabilities. Supports both cloud AI and self-hosted LLM extraction.
**Best for:**
- Extracting specific structured data like prices, names, details.
**Not recommended for:**
- When you need the full content of a page (use scrape)
- When you're not looking for specific structured data
**Arguments:**
- `urls`: Array of URLs to extract information from
- `prompt`: Custom prompt for the LLM extraction
- `systemPrompt`: System prompt to guide the LLM
- `schema`: JSON schema for structured data extraction
- `allowExternalLinks`: Allow extraction from external links
- `enableWebSearch`: Enable web search for additional context
- `includeSubdomains`: Include subdomains in extraction
When using a self-hosted instance, the extraction will use your configured LLM. For cloud API, it uses Firecrawl's managed LLM service.
**Prompt Example:**
> "Extract the product name, price, and description from these product pages."
**Usage Example:**
```json
{
"name": "firecrawl_extract",
"arguments": {
"urls": ["https://example.com/page1", "https://example.com/page2"],
"prompt": "Extract product information including name, price, and description",
"systemPrompt": "You are a helpful assistant that extracts product information",
"schema": {
"type": "object",
"properties": {
"name": { "type": "string" },
"price": { "type": "number" },
"description": { "type": "string" }
},
"required": ["name", "price"]
},
"allowExternalLinks": false,
"enableWebSearch": false,
"includeSubdomains": false
}
}
```
**Returns:**
- Extracted structured data as defined by your schema
```json
{
"content": [
{
"type": "text",
"text": {
"name": "Example Product",
"price": 99.99,
"description": "This is an example product description"
}
}
],
"isError": false
}
```
### 8. Agent Tool (`firecrawl_agent`)
Autonomous web research agent. This is a separate AI agent layer that independently browses the internet, searches for information, navigates through pages, and extracts structured data based on your query.
**How it works:**
The agent performs web searches, follows links, reads pages, and gathers data autonomously. This runs **asynchronously** - it returns a job ID immediately, and you poll `firecrawl_agent_status` to check when complete and retrieve results.
**Async workflow:**
1. Call `firecrawl_agent` with your prompt/schema → returns job ID
2. Do other work while the agent researches (can take minutes for complex queries)
3. Poll `firecrawl_agent_status` with the job ID to check progress
4. When status is "completed", the response includes the extracted data
**Best for:**
- Complex research tasks where you don't know the exact URLs
- Multi-source data gathering
- Finding information scattered across the web
- Tasks where you can do other work while waiting for results
**Not recommended for:**
- Simple single-page scraping where you know the URL (use scrape with JSON format - faster and cheaper)
**Arguments:**
- `prompt`: Natural language description of the data you want (required, max 10,000 characters)
- `urls`: Optional array of URLs to focus the agent on specific pages
- `schema`: Optional JSON schema for structured output
**Prompt Example:**
> "Find the founders of Firecrawl and their backgrounds"
**Usage Example (start agent, then poll for results):**
```json
{
"name": "firecrawl_agent",
"arguments": {
"prompt": "Find the top 5 AI startups founded in 2024 and their funding amounts",
"schema": {
"type": "object",
"properties": {
"startups": {
"type": "array",
"items": {
"type": "object",
"properties": {
"name": { "type": "string" },
"funding": { "type": "string" },
"founded": { "type": "string" }
}
}
}
}
}
}
}
```
Then poll with `firecrawl_agent_status` using the returned job ID.
**Usage Example (with URLs - agent focuses on specific pages):**
```json
{
"name": "firecrawl_agent",
"arguments": {
"urls": ["https://docs.firecrawl.dev", "https://firecrawl.dev/pricing"],
"prompt": "Compare the features and pricing information from these pages"
}
}
```
**Returns:**
- Job ID for status checking. Use `firecrawl_agent_status` to poll for results.
### 9. Check Agent Status (`firecrawl_agent_status`)
Check the status of an agent job and retrieve results when complete. Use this to poll for results after starting an agent.
**Polling pattern:** Agent research can take minutes for complex queries. Poll this endpoint periodically (e.g., every 10-30 seconds) until status is "completed" or "failed".
```json
{
"name": "firecrawl_agent_status",
"arguments": {
"id": "550e8400-e29b-41d4-a716-446655440000"
}
}
```
**Possible statuses:**
- `processing`: Agent is still researching - check back later
- `completed`: Research finished - response includes the extracted data
- `failed`: An error occurred
### 10. Interact Tool (`firecrawl_interact`)
Interact with a fresh URL or with a page that was already opened by `firecrawl_scrape`.
**Best for:** Clicking, typing, navigating, and extracting state from dynamic pages without restoring the deprecated browser tools.
**Usage options:**
- Pass `url` to scrape and open a page for interaction in one MCP call.
- Pass `scrapeId` to continue interacting with an existing scraped page.
- Pass exactly one of `url` or `scrapeId`, plus either `prompt` or `code`.
**Usage Example:**
```json
{
"name": "firecrawl_interact",
"arguments": {
"url": "https://example.com",
"prompt": "Click the pricing link and summarize the visible plans"
}
}
```
**Returns:** Interaction result and, for URL mode, the derived `scrapeId` for follow-up or cleanup.
### 11. Stop Interact Tool (`firecrawl_interact_stop`)
Stop an interact session for a scraped page when you are done interacting.
```json
{
"name": "firecrawl_interact_stop",
"arguments": {
"scrapeId": "scrape-id-here"
}
}
```
### 12. Research Tools (`firecrawl_research_*`)
Search and inspect papers and GitHub repositories through the research MCP tools.
**Available research tools:**
- `firecrawl_research_search_papers`: search research papers.
- `firecrawl_research_inspect_paper`: inspect one paper.
- `firecrawl_research_related_papers`: find related papers.
- `firecrawl_research_read_paper`: read paper content.
- `firecrawl_research_search_github`: search GitHub repositories.
**Best for:** Literature review, paper lookup, and repository discovery workflows where the agent needs a focused research surface instead of general web scraping.
### 13. Monitor Tools (`firecrawl_monitor_*`)
Create and manage recurring page monitors. Monitors run scheduled scrapes or crawls, diff each result against the last retained snapshot, and can notify by webhook or email.
**Best for:**
- Watching one page or a few pages over time
- Alerting on meaningful changes using a plain-English goal
- Tracking check history and page-level diffs
**Recommended create pattern:**
Use `page` or `pages` plus `goal`. The MCP server builds the monitor request with a 30-minute schedule and the API enables meaningful-change judging automatically.
Meaningful-change judging runs automatically when `goal` is set. Page webhooks expose `isMeaningful` and `judgment` on `monitor.page` events.
Write goals as concise 2-3 sentence monitor instructions. Say what should trigger an alert, preserve any scope the user gave, and include intent-specific exclusions only when obvious from the request. Generic noise such as whitespace, formatting-only changes, request IDs, tracking params, generic metadata, and unrelated page chrome is already handled by the judge, so do not repeat it in every goal. If the user is vague, keep the goal broad; if they ask for broad monitoring or "any change", preserve that. If the user says they do not care about something, include that explicitly.
```json
{
"name": "firecrawl_monitor_create",
"arguments": {
"page": "https://example.com/pricing",
"goal": "Alert when pricing, packaging, or launch messaging changes."
}
}
```
**Multiple pages with webhooks:**
```json
{
"name": "firecrawl_monitor_create",
"arguments": {
"pages": ["https://example.com/pricing", "https://example.com/changelog"],
"goal": "Alert when pricing, packaging, or launch messaging changes.",
"webhookUrl": "https://example.com/webhooks/firecrawl"
}
}
```
**Advanced create requests:**
Pass `body` when you need crawl targets, JSON change tracking, custom retention, or explicit `judgeEnabled` control.
```json
{
"name": "firecrawl_monitor_create",
"arguments": {
"body": {
"name": "Docs monitor",
"schedule": { "text": "hourly", "timezone": "UTC" },
"goal": "Alert when docs pages add, remove, or materially change API behavior.",
"targets": [{ "type": "crawl", "url": "https://example.com/docs" }]
}
}
}
```
**Other monitor tools:**
- `firecrawl_monitor_list`: list monitors.
- `firecrawl_monitor_get`: get one monitor.
- `firecrawl_monitor_update`: update fields including `goal`, `judgeEnabled`, `webhook`, and `notification`.
- `firecrawl_monitor_run`: trigger a check now.
- `firecrawl_monitor_delete`: delete a monitor (destructive; only call when the user intends to remove it).
- `firecrawl_monitor_checks`: list checks, optionally filtered by status.
- `firecrawl_monitor_check`: get page-level results, including `diff`, `snapshot`, `judgment.meaningful`, and `judgment.meaningfulChanges`.
## Logging System
The server includes comprehensive logging:
- Operation status and progress
- Performance metrics
- Rate limit tracking
- Error conditions
Example log messages:
```
[INFO] Firecrawl MCP Server initialized successfully
[INFO] Starting scrape for URL: https://example.com
[ERROR] Rate limit exceeded
```
## Error Handling
The server provides robust error handling:
- API rate-limit errors surfaced to the MCP client
- Detailed error messages
- Network resilience
Example error response:
```json
{
"content": [
{
"type": "text",
"text": "Error: Rate limit exceeded"
}
],
"isError": true
}
```
## Development
```bash
# Install dependencies
npm install
# Build
npm run build
# Run tests
npm test
```
### Contributing
1. Fork the repository
2. Create your feature branch
3. Run tests: `npm test`
4. Submit a pull request
### Thanks to contributors
Thanks to [@vrknetha](https://github.com/vrknetha), [@cawstudios](https://caw.tech) for the initial implementation!
Thanks to MCP.so and Klavis AI for hosting and [@gstarwd](https://github.com/gstarwd), [@xiangkaiz](https://github.com/xiangkaiz) and [@zihaolin96](https://github.com/zihaolin96) for integrating our server.
## License
MIT License - see LICENSE file for details