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Library Docs MCP Server

Library Docs MCP Server

Public
vikramdse/docs-mcp-server

Enables real-time, natural language search and retrieval of up-to-date documentation for popular libraries like Langchain, Llama-Index, MCP, and OpenAI using the Serper API, enhancing LLM accuracy beyond knowledge cut-off limits.

python
0 tools
May 29, 2025
Updated Jun 4, 2025

Supercharge Your AI with Library Docs MCP Server

MCP Server

Unlock the full potential of Library Docs MCP Server through LangDB's AI Gateway. Get enterprise-grade security, analytics, and seamless integration with zero configuration.

Unified API Access
Complete Tracing
Instant Setup
Get Started Now

Free tier available • No credit card required

Instant Setup
99.9% Uptime
10,000+Monthly Requests

Library Docs MCP Server

This is an MCP (Model Context Protocol) server that allows you to search and fetch documentation for popular libraries like Langchain, Llama-Index, MCP, and OpenAI using the Serper API.

Features

  • Search library documentation using a natural language query.
  • Supports Langchain, Llama-Index, MCP, and OpenAI (Update the code to add other libraries).
  • Uses the Serper API to perform site-specific searches.
  • Parses and returns the documentation using BeautifulSoup.
  • Provides updated documentation – useful for LLM models with knowledge cut-off dates.

Why Use This Server with LLMs?

Many LLM models, including those used in Claude Desktop and similar platforms, have a knowledge cut-off date and may not have access to the latest library documentation. This MCP server solves that problem by:

  • Fetching real-time documentation from official sources.
  • Providing up-to-date information for development and troubleshooting.
  • Improving the accuracy and relevance of responses when working with new library updates.

Setting Up with Claude Desktop

To use this server with Claude Desktop, update the claude_desktop_config.json file with the following configuration:

{ "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" ] } } }
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