MCP.so
登录

Crawl4ai MCP Server

@wyattowalsh

基本信息

分类

其他

许可证

MIT

传输方式

stdio

作者

wyattowalsh

关于 Crawl4ai MCP Server

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

Crawl4ai MCP Server 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

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

Crawl4ai MCP Server 工具

工具列表暂未提供

当前收录暂时没有可展示的工具列表,不代表服务没有工具。请查阅项目文档了解支持的能力。

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

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

常见问题

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.

评论

其他 分类下的更多 MCP 服务器