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Crawl4ai MCP Server

@wyattowalsh

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基本情報

カテゴリ

その他

ライセンス

MIT

トランスポート

stdio

作者

wyattowalsh

Crawl4ai MCP Server について

MCP (Model Context Protocol) server wrapping Crawl4AI library as functions using Python

#python#agent#crawler#scraper#mcp#crawling#python3#scrape#uv#uvx#agentic-workflow#agentic-ai#crawl4ai#model-context-protocol#mcp-servers#mcp-server#model-context-protocol-servers

Crawl4ai MCP Server の設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

{
  "mcpServers": {
    "crawl4ai-mcp": {
      "command": "docker",
      "args": [
        "build",
        "-t",
        "mcp-crawl4ai",
        "."
      ]
    }
  }
}

Crawl4ai MCP Server のツール

ツール一覧はまだありません

この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。

ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

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_page prompt
  • 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

よくある質問

1

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.

2

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`.

3

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.

4

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.

5

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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