docs-mcp-server

docs-mcp-server

0
research_and_data

The MCP Docs Search Server is designed to facilitate seamless interaction between language models and AI library documentation. It provides dynamic querying capabilities that enhance the functionality of AI-powered tools by standardizing communication and reducing the need for bespoke integrations.

MCP Docs Search Server

A lightweight server for querying and retrieving documentation from AI libraries like LangChain, LlamaIndex, and OpenAI. Key features include web search integration using Serper API, clean content extraction via BeautifulSoup, and a structured get_docs tool for seamless LLM tooling. It acts as a bridge between language models and external documentation sources, standardizing communication and enabling dynamic querying.

Features

  • Web Search Integration: Uses Serper API to query Google.
  • Clean Content Extraction: Parses HTML for clean text.
  • Seamless LLM Tooling: Provides a get_docs tool for real-time queries.

Setup

  1. Clone the repository.
  2. Create and activate a virtual environment.
  3. Install dependencies.
  4. Set environment variables in a .env file.

Future Enhancements

  • Support more libraries.
  • Implement caching.
  • Introduce a scoring/ranking mechanism.