crawl4ai-mcp
@wyattowalsh
About crawl4ai-mcp
MCP (Model Context Protocol) server wrapping Crawl4AI library as functions using Python
Config
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"crawl4ai-mcp": {
"command": "docker",
"args": [
"build",
"-t",
"mcp-crawl4ai",
"."
]
}
}
}Tools
No tools detected
We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.
Overview
What is crawl4ai-mcp?
crawl4ai-mcp is a Model Context Protocol (MCP) server that provides AI systems with access to the live web. Built on FastMCP v3 and Crawl4AI, it exposes 4 tools, 2 resources, and 3 prompts through a standardized MCP interface, backed by a lifespan-managed headless Chromium browser.
How to use crawl4ai-mcp?
Install via pip install mcp-crawl4ai or uv add mcp-crawl4ai, then run mcp-crawl4ai for stdio transport (default) or mcp-crawl4ai --transport http --port 8000 for HTTP. For Claude Desktop, add to MCP settings with the command mcp-crawl4ai and args ["--transport", "stdio"].
Key features of crawl4ai-mcp
- Full MCP compliance via FastMCP v3 with tool annotations
- 4 focused tools for scrape, crawl, session lifecycle, and artifacts
- 3 prompts for common LLM workflows (summarize, extract schema, compare)
- 2 resources exposing server configuration and version info
- Headless Chromium managed as a lifespan singleton
- Multiple transports: stdio (default) and Streamable HTTP
- LLM-optimized output in markdown, cleaned HTML, raw HTML, or plain text
- Auto browser setup and detection of missing Playwright browsers
Use cases of crawl4ai-mcp
- AI agents that need to scrape or crawl web pages for real-time information
- Summarizing a page with a specified focus using the
summarize_pageprompt - Building a CSS extraction schema for structured data from a URL
- Comparing two web pages and producing a structured comparison
- Deep traversal of a website using recursive BFS/DFS from a single seed
FAQ from crawl4ai-mcp
What is the difference between crawl4ai-mcp and using Crawl4AI directly?
crawl4ai-mcp wraps Crawl4AI in an MCP server with only 2 runtime dependencies (fastmcp and crawl4ai), providing a standardized interface for AI tools and LLM clients. It adds session management, resource endpoints, and prompt templates.
What are the runtime dependencies of crawl4ai-mcp?
The server requires Python 3.13+ and has exactly two runtime dependencies: fastmcp and crawl4ai. Playwright browsers are needed for headless Chromium but are installed automatically or via mcp-crawl4ai --setup.
Does crawl4ai-mcp require a browser to be installed?
Yes, it uses headless Chromium. The server auto-detects missing Playwright browsers and attempts to install them on first startup, or you can run mcp-crawl4ai --setup manually. The Docker image includes browsers pre-installed.
What transports does crawl4ai-mcp support?
Stdio (default) for desktop clients like Claude Desktop and Cursor, and HTTP (Streamable) for remote access. HTTP binds to 127.0.0.1:8000 by default; use --host and a reverse proxy for external exposure.
Are there any known limits in crawl4ai-mcp?
The scrape tool accepts up to 20 URLs in a bounded list. The crawl tool supports both list traversal (bounded) and deep traversal (recursive BFS/DFS) from a single seed. There are configurable limits exposed via the config://server resource.
Frequently asked questions
What is the difference between crawl4ai-mcp and using Crawl4AI directly?
crawl4ai-mcp wraps Crawl4AI in an MCP server with only 2 runtime dependencies (`fastmcp` and `crawl4ai`), providing a standardized interface for AI tools and LLM clients. It adds session management, resource endpoints, and prompt templates.
What are the runtime dependencies of crawl4ai-mcp?
The server requires Python 3.13+ and has exactly two runtime dependencies: `fastmcp` and `crawl4ai`. Playwright browsers are needed for headless Chromium but are installed automatically or via `mcp-crawl4ai --setup`.
Does crawl4ai-mcp require a browser to be installed?
Yes, it uses headless Chromium. The server auto-detects missing Playwright browsers and attempts to install them on first startup, or you can run `mcp-crawl4ai --setup` manually. The Docker image includes browsers pre-installed.
What transports does crawl4ai-mcp support?
Stdio (default) for desktop clients like Claude Desktop and Cursor, and HTTP (Streamable) for remote access. HTTP binds to `127.0.0.1:8000` by default; use `--host` and a reverse proxy for external exposure.
Are there any known limits in crawl4ai-mcp?
The `scrape` tool accepts up to 20 URLs in a bounded list. The `crawl` tool supports both list traversal (bounded) and deep traversal (recursive BFS/DFS) from a single seed. There are configurable limits exposed via the `config://server` resource.
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