What can you do with this server?

The MCP Server Firecrawl is an API-powered server providing multiple web data collection capabilities: * Web Scraping: Extract content from URLs with options for mobile emulation, ad blocking, content filtering, and structured data extraction in various formats (markdown, HTML, JSON). * Content Search: Perform intelligent searches with multi-language support, location-based results, and customizable result limits. * Site Crawling: Crawl websites with depth control, path filtering, rate limiting, and sitemap integration. * Site Mapping: Generate structural maps of websites with subdomain support and link analysis. * Data Extraction: Extract structured data from multiple URLs using schema validation, batch processing, and custom extraction prompts.

Which integrations are available for this server?

Supports using .env files to configure the Firecrawl API key for secure development environments. Supports outputting scraped content in Markdown format for better readability and structure. Provides TypeScript interfaces for the API, with examples written in TypeScript for better type safety and developer experience.

How do I use MCP Server Firecrawl?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@MCP Server Firecrawl scrape the latest blog posts from techcrunch.com and extract titles and summaries" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

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MCP Server Firecrawl

by Msparihar

Overview Schema Related Servers Score Discussions

TypeScript

Remote

Firecrawl MCP Server

A Model Context Protocol (MCP) server for web scraping, content searching, site crawling, and data extraction using the Firecrawl API.

Features

Web Scraping: Extract content from any webpage with customizable options
- Mobile device emulation
- Ad and popup blocking
- Content filtering
- Structured data extraction
- Multiple output formats
Content Search: Intelligent search capabilities
- Multi-language support
- Location-based results
- Customizable result limits
- Structured output formats
Site Crawling: Advanced web crawling functionality
- Depth control
- Path filtering
- Rate limiting
- Progress tracking
- Sitemap integration
Site Mapping: Generate site structure maps
- Subdomain support
- Search filtering
- Link analysis
- Visual hierarchy
Data Extraction: Extract structured data from multiple URLs
- Schema validation
- Batch processing
- Web search enrichment
- Custom extraction prompts

Related MCP server: MCP Firecrawl Server

Installation

# Global installation
npm install -g @modelcontextprotocol/mcp-server-firecrawl

# Local project installation
npm install @modelcontextprotocol/mcp-server-firecrawl

Quick Start

Get your Firecrawl API key from the developer portal

Set your API key:

Unix/Linux/macOS (bash/zsh):

export FIRECRAWL_API_KEY=your-api-key

Windows (Command Prompt):

set FIRECRAWL_API_KEY=your-api-key

Windows (PowerShell):

$env:FIRECRAWL_API_KEY = "your-api-key"

Alternative: Using .env file (recommended for development):

# Install dotenv
npm install dotenv

# Create .env file
echo "FIRECRAWL_API_KEY=your-api-key" > .env

Then in your code:

import dotenv from 'dotenv';
dotenv.config();

Run the server:
```
mcp-server-firecrawl
```

Integration

Claude Desktop App

Add to your MCP settings:

{
  "firecrawl": {
    "command": "mcp-server-firecrawl",
    "env": {
      "FIRECRAWL_API_KEY": "your-api-key"
    }
  }
}

Claude VSCode Extension

Add to your MCP configuration:

{
  "mcpServers": {
    "firecrawl": {
      "command": "mcp-server-firecrawl",
      "env": {
        "FIRECRAWL_API_KEY": "your-api-key"
      }
    }
  }
}

Usage Examples

Web Scraping

// Basic scraping
{
  name: "scrape_url",
  arguments: {
    url: "https://example.com",
    formats: ["markdown"],
    onlyMainContent: true
  }
}

// Advanced extraction
{
  name: "scrape_url",
  arguments: {
    url: "https://example.com/blog",
    jsonOptions: {
      prompt: "Extract article content",
      schema: {
        title: "string",
        content: "string"
      }
    },
    mobile: true,
    blockAds: true
  }
}

Site Crawling

// Basic crawling
{
  name: "crawl",
  arguments: {
    url: "https://example.com",
    maxDepth: 2,
    limit: 100
  }
}

// Advanced crawling
{
  name: "crawl",
  arguments: {
    url: "https://example.com",
    maxDepth: 3,
    includePaths: ["/blog", "/products"],
    excludePaths: ["/admin"],
    ignoreQueryParameters: true
  }
}

Site Mapping

// Generate site map
{
  name: "map",
  arguments: {
    url: "https://example.com",
    includeSubdomains: true,
    limit: 1000
  }
}

Data Extraction

// Extract structured data
{
  name: "extract",
  arguments: {
    urls: ["https://example.com/product1", "https://example.com/product2"],
    prompt: "Extract product details",
    schema: {
      name: "string",
      price: "number",
      description: "string"
    }
  }
}

Configuration

See configuration guide for detailed setup options.

API Documentation

See API documentation for detailed endpoint specifications.

Development

# Install dependencies
npm install

# Build
npm run build

# Run tests
npm test

# Start in development mode
npm run dev

Examples

Check the examples directory for more usage examples:

Basic scraping: scrape.ts
Crawling and mapping: crawl-and-map.ts

Error Handling

The server implements robust error handling:

Rate limiting with exponential backoff
Automatic retries
Detailed error messages
Debug logging

Security

API key protection
Request validation
Domain allowlisting
Rate limiting
Safe error messages

Contributing

See CONTRIBUTING.md for contribution guidelines.

License

MIT License - see LICENSE for details.

Available Tools

2 tools

extractC

Extracts structured data from URLs

ParametersJSON Schema

Name	Required	Description
`urls`	Yes	URLs to extract from
`prompt`	No	Extraction guidance prompt
`schema`	No	Data structure schema
`ignoreSitemap`	No	Ignore sitemap.xml during processing
`enableWebSearch`	No	Use web search for additional data
`includeSubdomains`	No	Include subdomains in processing

TDQS

C2.1/5.0

Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations exist, so the description must disclose behavior. It does not mention network requests, rate limits, authentication, error handling, or whether it is idempotent. Only states 'extracts', which is vague.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness2/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Very short at 7 words, but under-specified. Lacks structure such as sections or examples. Conciseness would be appropriate if complete, but here it is insufficient.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness1/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity (6 parameters, nested objects, sibling tools, no output schema), the description is extremely incomplete. No information on return format, usage patterns, or edge cases.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so baseline is 3. The description does not add any extra meaning beyond the schema's parameter descriptions. No elaboration on how parameters interact.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states the tool extracts structured data from URLs, but does not differentiate from sibling 'map'. The verb and resource are clear, but the scope is vague as 'structured data' is not defined.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines1/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool versus alternatives like 'map', no prerequisites or exclusions provided. The description is insufficient for an agent to decide usage context.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

mapC

Maps a website's structure

ParametersJSON Schema

Name	Required	Description
`url`	Yes	Base URL to map
`limit`	No	Maximum links to return
`search`	No	Search query for mapping
`timeout`	No	Request timeout
`sitemapOnly`	No	Only use sitemap.xml for mapping
`ignoreSitemap`	No	Ignore sitemap.xml during mapping
`includeSubdomains`	No	Include subdomains in mapping

TDQS

C2.4/5.0

Behavior1/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are present, so the description must disclose behavioral traits. It only says 'Maps a website's structure' with no details on whether it crawls, destructiveness, rate limits, or return format. This is insufficient.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness2/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, short sentence, which is efficient but under-specified for a tool with 7 parameters. It could include key details without sacrificing conciseness.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness1/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (7 parameters, no output schema, no annotations), the description lacks essential context such as return values, process details, or limitations. It is highly incomplete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% description coverage for all 7 parameters, so the baseline is 3. The description adds no additional meaning beyond the schema, making it adequate but not improved.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb ('Maps') and resource ('a website's structure'), making the core purpose clear. However, it does not differentiate from the sibling tool 'extract', which could lead to ambiguity.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives (e.g., 'extract'). The description lacks context for selection or prerequisites.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.

2 tool updatesv1.0.1Jul 4, 2026
- First observedextract
- First observedmap

Install Server

RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

TDQS

C2.7/5.0

Disambiguation5/5

The two tools have clearly distinct purposes: one extracts structured data from URLs, the other maps a website's structure. There is no overlap in functionality.

Naming Consistency5/5

Both tool names are single imperative verbs ('extract' and 'map'), following a consistent and concise naming pattern.

Tool Count3/5

With only 2 tools, the server is on the lower end of acceptable scope. It covers basic functionality but feels minimal for a web crawling service.

Completeness3/5

The server provides core data extraction and site mapping, but lacks advanced features like recursive crawling or search, which are notable gaps for the domain.

Maintenance

ActivityInactive

ResponsivenessNo issues

Resources

GitHub Repository

Need Help?

Reddit Discussion

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Looking for Admin?

If you are the server author, to access and configure the admin panel.

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Firecrawl MCP Server

Features

Installation

Quick Start

Integration

Claude Desktop App

Claude VSCode Extension

Usage Examples

Web Scraping

Site Crawling

Site Mapping

Data Extraction

Configuration

API Documentation

Development

Examples

Error Handling

Security

Contributing

License

Available Tools

TDQS

TDQS

Tool Schema Changelog

TDQS

Maintenance

Resources

Looking for Admin?

Related MCP Connectors

Related MCP Servers

WebSearch

MCP Firecrawl Server

Firecrawl MCP Server

Firecrawl MCP Server

Appeared in Searches

Latest Blog Posts

MCP directory API