Crawl4AI MCP Server
About
用于提供给本地开发者的 LLM的高效互联网搜索&内容获取的MCP Server, 节省你的token
Details
- Author
- weidwonder
- GitHub stars
- 146
- Downloads
- 588
- Categories
- Other
Jump to
- Multi‑engine search (DuckDuckGo and Google)
- LLM‑optimized web content extraction with noise filtering
- Automatic identification and retention of key content
- Multiple output formats including markdown with citations
- High‑performance asynchronous design based on FastMCP
Setting up with Highlight
This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:
- Download and install Highlight from highlightai.com/download
- Navigate to the plugins tab and select "Add Custom Plugin"
-
Configure the plugin with the settings below
Plugin Name
Crawl4AI MCP ServerCommand (node, npx, python, etc.)Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
- Enable "Start Automatically" if you want the plugin to start when Highlight launches
From the repository
Install via cloning the repository, creating a Python 3.9+ virtual environment, installing dependencies (pip install -r requirements.txt) and the Playwright browser (playwright install), or via Smithery for Claude Desktop. The server exposes two tools: search (with parameters query, num_results, engine) and read_url (with parameters url and format). To use Google search, configure config.json with an API key and CSE ID.
Claude Desktop / Cursor
Paste into your MCP client config file to install this server.
{
"mcpServers": {
"crawl4ai mcp server": {
"crawl4ai-mcp-server": {
"command": "python",
"args": [
"-m",
"venv",
"crawl4ai_env"
]
}
}
}
}
McpServers
{
"crawl4ai-mcp-server": {
"command": "python",
"args": [
"-m",
"venv",
"crawl4ai_env"
]
}
}
Crawl4AI MCP Server
这是一个基于MCP (Model Context Protocol)的智能信息获取服务器,为AI助手系统提供强大的搜索能力和面向LLM优化的网页内容理解功能。通过多引擎搜索和智能内容提取,帮助AI系统高效获取和理解互联网信息,将网页内容转换为最适合LLM处理的格式。
特性
- 🔍 强大的多引擎搜索能力,支持DuckDuckGo和Google
- 📚 面向LLM优化的网页内容提取,智能过滤非核心内容
- 🎯 专注信息价值,自动识别和保留关键内容
- 📝 多种输出格式,支持引用溯源
- 🚀 基于FastMCP的高性能异步设计
安装
方式1: 大部分的安装场景
1. 确保您的系统满足以下要求:
- Python >= 3.9
- 建议使用专门的虚拟环境
2. 克隆仓库:
git clone https://github.com/yourusername/crawl4ai-mcp-server.git
cd crawl4ai-mcp-server
3. 创建并激活虚拟环境:
```bash
python -m venv crawl4ai_env
source crawl4ai_env/bin/activate # Linux/Mac
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