Documentation Retrieval MCP Server (DOCRET)
by Sreedeep-SS
This project implements a Model Context Protocol (MCP) server that enables AI assistants to access up-to-date documentation for various Python libraries. It allows AI applications to dynamically fetch and provide relevant information from official documentation sources.
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What is Documentation Retrieval MCP Server (DOCRET)?
The Documentation Retrieval MCP Server (DOCRET) is a server that provides AI assistants with access to the latest official documentation for Python libraries like LangChain, LlamaIndex, and OpenAI. It uses the Model Context Protocol (MCP) to enable secure, two-way connections between data sources and AI-powered tools.
How to use Documentation Retrieval MCP Server (DOCRET)?
To use the server, first install the dependencies and set up the environment variables. Then, run the main.py script to start the server. You can then use the get_docs function to search for documentation on a specific topic within a library. Finally, integrate the server with AI assistants by configuring them to interact with the server's API.
Key features of Documentation Retrieval MCP Server (DOCRET)
Dynamic Documentation Retrieval
Asynchronous Web Searches using SERPER API
HTML Parsing with BeautifulSoup
Extensible Design for adding new libraries
Use cases of Documentation Retrieval MCP Server (DOCRET)
Providing AI assistants with up-to-date documentation
Enabling AI applications to dynamically fetch relevant information
Integrating with custom-built AI models
Building secure connections between data sources and AI tools
FAQ from Documentation Retrieval MCP Server (DOCRET)
What is an MCP Server?
What is an MCP Server?
The Model Context Protocol is an open standard that enables developers to build secure, two-way connections between their data sources and AI-powered tools.
What libraries are currently supported?
What libraries are currently supported?
The server currently supports LangChain, LlamaIndex, and OpenAI.
How can I add support for more libraries?
How can I add support for more libraries?
Update the docs_urls dictionary in main.py with the library name and its documentation URL.
What API key is required?
What API key is required?
The SERPER API key is required for searching documentation.
How do I run the server?
How do I run the server?
After installing dependencies and setting up environment variables, run python main.py.