MCP Docs Search Server

What is MCP Docs Search Server?

MCP Docs Search Server is a lightweight, plug-and-play server that enables Language Learning Models (LLMs) like Claude or GPT to dynamically search and retrieve up-to-date documentation from popular AI libraries such as LangChain, LlamaIndex, and OpenAI.

How to use MCP Docs Search Server?

To use the MCP Docs Search Server, clone the repository, set up a virtual environment, install the necessary dependencies, and configure your environment variables with your Serper API key. You can then integrate it with LLMs to query documentation in real-time.

Key features of MCP Docs Search Server?

• Web Search Integration using the Serper API to fetch relevant documentation.
• Clean Content Extraction to provide human-readable text from HTML.
• A structured get_docs tool for querying specific libraries in real-time.

Use cases of MCP Docs Search Server?

1. Enabling LLMs to access the latest documentation for AI libraries.
2. Assisting developers in finding relevant information quickly.
3. Enhancing the capabilities of LLMs by providing them with real-time data.

FAQ from MCP Docs Search Server?

• Can MCP Docs Search Server work with any LLM?

Yes! It is designed to work with various LLMs that can communicate using the Model Context Protocol (MCP).

• Is there a limit to the number of libraries supported?

No, additional libraries can be easily added by updating the configuration.

• How does the content extraction work?

It uses BeautifulSoup to parse HTML and extract clean, readable text.