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Library Docs MCP Server

@vikramdse

リポジトリ

基本情報

カテゴリ

メモリとナレッジ

トランスポート

stdio

作者

vikramdse

Library Docs MCP Server について

Library docs MCP server

#docs-mcp-server#library-docs#mcp-server

Library Docs 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": {
    "docs-mcp-server": {
      "command": "C:\\Users\\Vikram\\.local\\bin\\uv.exe",
      "args": [
        "run",
        "--with",
        "mcp[cli]",
        "mcp",
        "run",
        "F:\\My Projects\\AI\\docs-mcp-server\\server.py"
      ]
    }
  }
}

Library Docs 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 Library Docs MCP Server?

It is an MCP server that allows you to search and fetch documentation for popular libraries like Langchain, Llama-Index, MCP, and OpenAI using the Serper API. It is designed for developers using LLMs that have knowledge cut-off dates and need up‑to‑date library documentation.

How to use Library Docs MCP Server?

To use it with Claude Desktop, configure the claude_desktop_config.json file with the command and arguments pointing to the server script via uv. The README provides an example configuration for Windows.

Key features of Library Docs MCP Server

  • Search library documentation using natural language queries.
  • Supports Langchain, Llama-Index, MCP, and OpenAI (extensible by code modification).
  • Uses the Serper API for site‑specific searches.
  • Parses and returns documentation with BeautifulSoup.
  • Provides updated documentation useful for LLMs with knowledge cut‑off dates.

Use cases of Library Docs MCP Server

  • Fetching real‑time documentation from official sources for LLM‑assisted development.
  • Providing up‑to‑date information when using libraries with recent changes.
  • Improving response accuracy for LLMs that lack current library knowledge.

よくある質問

1

What libraries does it support?

It currently supports Langchain, Llama-Index, MCP, and OpenAI. You can update the code to add other libraries.

2

What are the runtime dependencies?

It requires the Serper API, BeautifulSoup, and is run via `uv` (a Python package manager). No other dependencies are explicitly listed.

3

Where does the documentation data come from?

Documentation is fetched in real time from official sources using the Serper API for site‑specific searches.

4

How is it authenticated?

The server uses the Serper API, which requires a valid API key. The README does not specify how to set the key, but it is assumed to be configured in the environment or code.

5

What transport or protocol does it use?

It follows the Model Context Protocol (MCP) standard. The README references Claude Desktop integration via the `mcpServers` configuration.

コメント

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