MCP Cursor

Enhance your development workflow with AI-powered MCP tools and extensions for Cursor IDE.

Product

  • MCP Servers
  • Getting Started
  • Documentation
  • Open Source

Resources

  • MCP Specification
  • Cursor IDE
  • MCP GitHub
  • Contributing

Legal

  • Privacy Policy
  • Terms of Service
  • Cookie Policy
Made withfor the developer community
© 2025 MCP Cursor. All rights reserved.
MCP Logo
MCP Cursor
IntroductionMCPs
IntroductionMCPs
3D MCP Cursor Visualization
  1. Home
  2. Servers
  3. Firecrawl MCP
Firecrawl MCP Logo

Firecrawl MCP

Model Context Protocol Integration

Overview

Integrates with the Firecrawl API to enable website crawling, content translation, and structured data extraction for enhanced web data processing workflows.

Firecrawl

Integrates with the Firecrawl API to enable website crawling, content translation, and structured data extraction for enhanced web data processing workflows.

Installation Instructions


README: https://github.com/codyde/mcp-firecrawl-tool

MCP Firecrawl Server

This is a simple MCP server that provides tools to scrape websites and extract structured data using Firecrawl's APIs.

Setup

  1. Install dependencies:
npm install
  1. Create a .env file in the root directory with the following variables:
FIRECRAWL_API_TOKEN=your_token_here
SENTRY_DSN=your_sentry_dsn_here
  • FIRECRAWL_API_TOKEN (required): Your Firecrawl API token
  • SENTRY_DSN (optional): Sentry DSN for error tracking and performance monitoring
  1. Start the server:
npm start

Alternatively, you can set environment variables directly when running the server:

FIRECRAWL_API_TOKEN=your_token_here npm start

Features

  • Website Scraping: Extract content from websites in various formats
  • Structured Data Extraction: Extract specific data points based on custom schemas
  • Error Tracking: Integrated with Sentry for error tracking and performance monitoring

Usage

The server exposes two tools:

  1. scrape-website: Basic website scraping with multiple format options
  2. extract-data: Structured data extraction based on prompts and schemas

Tool: scrape-website

This tool scrapes a website and returns its content in the requested formats.

Parameters:

  • url (string, required): The URL of the website to scrape
  • formats (array of strings, optional): Array of desired output formats. Supported formats are:
    • "markdown" (default)
    • "html"
    • "text"

Example usage with MCP Inspector:

# Basic usage (defaults to markdown)
mcp-inspector --tool scrape-website --args '{
  "url": "https://example.com"
}'

# Multiple formats
mcp-inspector --tool scrape-website --args '{
  "url": "https://example.com",
  "formats": ["markdown", "html", "text"]
}'

Tool: extract-data

This tool extracts structured data from websites based on a provided prompt and schema.

Parameters:

  • urls (array of strings, required): Array of URLs to extract data from
  • prompt (string, required): The prompt describing what data to extract
  • schema (object, required): Schema definition for the data to extract

The schema definition should be an object where keys are field names and values are types. Supported types are:

  • "string": For text fields
  • "boolean": For true/false fields
  • "number": For numeric fields
  • Arrays: Specified as ["type"] where type is one of the above
  • Objects: Nested objects with their own type definitions

Example usage with MCP Inspector:

# Basic example extracting company information
mcp-inspector --tool extract-data --args '{
  "urls": ["https://example.com"],
  "prompt": "Extract the company mission, whether it supports SSO, and whether it is open source.",
  "schema": {
    "company_mission": "string",
    "supports_sso": "boolean",
    "is_open_source": "boolean"
  }
}'

# Complex example with nested data
mcp-inspector --tool extract-data --args '{
  "urls": ["https://example.com/products", "https://example.com/pricing"],
  "prompt": "Extract product information including name, price, and features.",
  "schema": {
    "products": [{
      "name": "string",
      "price": "number",
      "features": ["string"]
    }]
  }
}'

Both tools will return appropriate error messages if the scraping or extraction fails and automatically log errors to Sentry if configured.

Troubleshooting

If you encounter issues:

  1. Verify your Firecrawl API token is valid
  2. Check that the URLs you're trying to scrape are accessible
  3. For complex schemas, ensure they follow the supported format
  4. Review Sentry logs for detailed error information (if configured)

Featured MCPs

Github MCP - Model Context Protocol for Cursor IDE

Github

This server provides integration with Github's issue tracking system through MCP, allowing LLMs to interact with Github issues.

Sequential Thinking MCP - Model Context Protocol for Cursor IDE

Sequential Thinking

An MCP server implementation that provides a tool for dynamic and reflective problem-solving through a structured thinking process. Break down complex problems into manageable steps, revise and refine thoughts as understanding deepens, and branch into alternative paths of reasoning.

Puppeteer MCP - Model Context Protocol for Cursor IDE

Puppeteer

A Model Context Protocol server that provides browser automation capabilities using Puppeteer. This server enables LLMs to interact with web pages, take screenshots, execute JavaScript, and perform various browser-based operations in a real browser environment.