Documentation-MCP

# Documentation MCP Server 📚🔍 A Model Context Protocol (MCP) server that enables Claude to search and access documentation from popular libraries like LangChain, LlamaIndex, and OpenAI directly within conversations. ## What is MCP? 🤔 MCP (Model Context Protocol) is an open protocol that standardizes how applications provide context to Large Language Models. Think of it as a universal connector that lets AI assistants like Claude access external data sources and tools.   ## Features ✨ - **Documentation Search Tool**: Search through documentation of popular AI libraries - **Supported Libraries**: - [LangChain](https://python.langchain.com/docs) 🔗 - [LlamaIndex](https://docs.llamaindex.ai/en/stable) 🦙 - [OpenAI](https://platform.openai.com/docs) 🤖 - **Smart Extraction**: Intelligently parses HTML content to extract the most relevant information - **Configurable Results**: Limit the amount of text returned based on your needs ## How It Works 🛠️ 1. The server uses the Serper API to perform Google searches with site-specific queries 2. It fetches the content from the search results 3. BeautifulSoup extracts the most relevant text from main content areas 4. Claude can access this information through the `get_docs` tool ## System Requirements 🖥️ - Python 3.11 or higher - `uv` package manager - A Serper API key ## Setup Instructions 🚀 ### 1. Install uv Package Manager ```bash curl -LsSf https://astral.sh/uv/install.sh | sh ``` ### 2. Clone and Set Up the Project ```bash # Clone or download the project cd documentation # Create and activate virtual environment uv venv # On Windows: .venv\Scripts\activate # On macOS/Linux: source .venv/bin/activate # Install dependencies uv pip install -e . ``` ### 3. Configure the Serper API Key Create a `.env` file in the project directory with your Serper API key: ``` SERPER_API_KEY=your_serper_api_key_here ``` You can get a Serper API key by signing up at [serper.dev](https://serper.dev). ### 4. Configure Claude Desktop Edit your Claude Desktop configuration file at: - Windows: `/C:/Users/[Your Username]/AppData/Roaming/Claude/claude_desktop_config.json` - macOS: `~/Library/Application Support/Claude/claude_desktop_config.json` Add the following to the `mcpServers` section: ```json "documentation": { "command": "uv", "args": [ "--directory", "/ABSOLUTE/PATH/TO/YOUR/documentation", "run", "main.py" ] } ``` Replace `/ABSOLUTE/PATH/TO/YOUR/documentation` with the absolute path to your project directory. ### 5. Restart Claude Desktop Close and reopen Claude Desktop to apply the new configuration. ## Using the Documentation Tool 🧩 Once connected, you can ask Claude to use the documentation tool: > "Can you look up information about vector stores in LangChain documentation?" Claude will use the `get_docs` tool to search for relevant information and provide you with documentation excerpts. ## Tool Parameters 📋 The `get_docs` tool accepts the following parameters: - `query`: The search term (e.g., "vector stores", "embedding models") - `library`: Which library to search (langchain, llama-index, or openai) - `max_chars`: Maximum characters to return (default: 1000) ## Troubleshooting 🛠️ - **Claude can't find the server**: Verify the path in `/C:/Users/fcbsa/AppData/Roaming/Claude/claude_desktop_config.json` is correct - **Search returns no results**: Check your Serper API key and internet connection - **Timeout errors**: The server might be experiencing connectivity issues or rate limits ## License 📜 This project is provided as an educational example of MCP server implementation. ## Acknowledgements 🙏 - Built using the [MCP SDK](https://github.com/modelcontextprotocol) - Powered by [Serper API](https://serper.dev) for Google search integration - Uses [BeautifulSoup4](https://www.crummy.com/software/BeautifulSoup/) for HTML parsing - Inspired by the growing MCP community --- *This MCP server enhances Claude's capabilities by providing direct access to documentation resources. Explore, learn, and build better AI applications with contextual knowledge from the docs!*