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MCP Server for Up-to-Date Library Documentation

@AmirUpSkill

代码仓库

基本信息

分类

记忆与知识

传输方式

stdio

作者

AmirUpSkill

关于 MCP Server for Up-to-Date Library Documentation

暂无概览

#mcp-server#documentation#python

MCP Server for Up-to-Date Library Documentation 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "Mcp-Server": {
      "command": "uv",
      "args": [
        "init",
        "mcp-server"
      ]
    }
  }
}

MCP Server for Up-to-Date Library Documentation 工具

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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 MCP Server for Up-to-Date Library Documentation?

This project implements an MCP server that provides large language models (LLMs) with real-time access to the latest documentation for specified Python libraries (Langchain, LlamaIndex, OpenAI) before they generate code suggestions. It addresses the problem of LLMs using outdated training data for rapidly evolving libraries.

How to use MCP Server for Up-to-Date Library Documentation?

Install Python 3.11+ and the uv package manager. Obtain a Serper API key from serper.dev and store it in a .env file as SERPER_API_KEY. Run the server with uv run main.py. Then integrate with an MCP client like Claude Desktop (via JSON configuration) or Claude Code (via claude mcp add).

Key features of MCP Server for Up-to-Date Library Documentation

  • Implements the Model Context Protocol for seamless client integration.
  • Exposes a get_docs tool for searching official documentation.
  • Uses Serper API for site‑specific searches (Langchain, LlamaIndex, OpenAI).
  • Fetches and parses documentation content with httpx and BeautifulSoup.
  • Built with Python 3.11+, asyncio, FastMCP, and managed via uv.

Use cases of MCP Server for Up-to-Date Library Documentation

  • A developer asks Claude to write code using Langchain and gets suggestions based on the latest API docs.
  • An LLM‑powered IDE retrieves up‑to‑date LlamaIndex documentation before generating data pipeline code.
  • An AI coding assistant fetches current OpenAI SDK examples to answer a user’s question correctly.

常见问题

1

Which libraries are supported?

The server searches official documentation for Langchain (`python.langchain.com/docs`), LlamaIndex (`docs.llamaindex.ai/en/stable`), and OpenAI (`platform.openai.com/docs`).

2

What are the runtime requirements?

Python 3.11+, the `uv` package manager, and a Serper API key are required. Node.js/npx is needed only for the optional MCP Inspector debugging tool.

3

How does the server fetch documentation?

It constructs a site‑specific Google search via the Serper API, then uses `httpx` and `BeautifulSoup` to extract text content from the top result pages.

4

How is the server configured?

Create a `.env` file with `SERPER_API_KEY=your_key`. The server runs locally over stdio and connects to MCP clients via configuration (Claude Desktop or Claude Code).

5

Can I test the server without a full client?

Yes. Run the MCP Inspector with `npx @model-context-protocol/inspector "uv run main.py"`, open `http://localhost:5173`, and test the `get_docs` tool with sample queries.

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