What dependencies does the server require?
It requires Python (managed via uv), the `mcp[cli]`, `httpx`, and `beautifulsoup4` packages, plus a Serper API key stored as the `SERPER_API_KEY` environment variable.
@RohitKrish46
基本信息
This is a lightweight, plug-and-play MCP server that empowers any LLM to dynamically search and retrieve up-to-date documentation from popular AI libraries such as LangChain, LlamaIndex, and OpenAI.
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"documnetation": {
"command": "uv",
"args": [
"--directory",
"your_reository_where_the_repo_exists",
"run",
"main.py"
]
}
}
}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。
A lightweight MCP server that searches and retrieves relevant documentation content from popular AI libraries like LangChain, LlamaIndex, and OpenAI using web search and content parsing. It acts as a bridge between LLMs and external documentation sources, enabling language models to query and fetch up-to-date documentation dynamically.
Clone the repository, create a virtual environment with uv, install dependencies (mcp[cli], httpx, beautifulsoup4), and set the SERPER_API_KEY environment variable. Integrate with Claude Desktop by adding the server configuration to claude_desktop_config.json, then use the get_docs tool with a query and library name. Debug in real time using npx @modelcontextprotocol/inspector uv run main.py.
get_docs tool for LLM agents.It requires Python (managed via uv), the `mcp[cli]`, `httpx`, and `beautifulsoup4` packages, plus a Serper API key stored as the `SERPER_API_KEY` environment variable.
LangChain, LlamaIndex, and OpenAI. More libraries can be added by updating the `docs_urls` dictionary.
It accepts a query string and a library name, searches for relevant documentation pages, fetches and parses clean text content, and returns the result to the LLM for further reasoning.
Yes. Use `npx @modelcontextprotocol/inspector uv run main.py` after installing Node.js 18+, then follow the port where the connection is set up.
Add the server configuration to `claude_desktop_config.json` under `mcpServers`, specifying the command `uv` with the directory and `run main.py`, then restart Claude Desktop.

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