Library Docs MCP Server

@vikramdse

Repository

Basic information

About Library Docs MCP Server

Library docs MCP server

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

Library Docs MCP Server config

Add this server to your MCP-compatible client using the configuration below.

{
  "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 tools

Tool list not available yet

This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

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.

Frequently asked questions

What libraries does it support?

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

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.

Where does the documentation data come from?

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

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.

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.

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