🤖 Claude AI Documentation Assistant 📚

A powerful MCP server that supercharges Claude with documentation search capabilities

✨ Features

• 🔍 Smart Documentation Search - Search across multiple AI/ML library documentation

• 🧠 Claude Integration - Seamless connection with Claude's advanced reasoning capabilities

• 🌐 Intelligent Web Search - Leverages Serper API for targeted documentation lookup

• 💨 Fast Response Times - Optimized for quick retrieval and processing

• 🧩 Extendable Architecture - Easily add more documentation sources

Related MCP server: Volcengine Knowledge Base MCP

📋 Prerequisites

• 🐍 Python 3.8 or higher

• 🔑 Claude Pro subscription

• 🔐 Serper API key (Get one here)

• 💻 Claude Desktop application

🚀 Quick Start

1️⃣ Installation

# Clone the repository
git clone https://github.com/your-username/claude-docs-assistant.git
cd claude-docs-assistant

# Create a virtual environment (recommended)
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

# Install dependencies
pip install -r requirements.txt

2️⃣ Configuration

Create a .env file in the project root with your API keys:

SERPER_API_KEY=your_serper_api_key_here

3️⃣ Start the MCP Server

python main.py

You should see output indicating the server is running and waiting for Claude to connect.

4️⃣ Connect Claude Desktop App

1. 📱 Open the Claude Desktop App

2. ⚙️ Click on your profile icon and select "Settings"

3. 🧰 Navigate to the "Tools" section

4. ➕ Click "Add Tool"

5. 🔗 Select "Connect to a local tool"

6. 🖥️ Follow the prompts to connect to your running MCP server

7. ✅ Confirm the connection is successful

🎮 Using Your Claude Documentation Assistant

Once connected, you can start asking Claude questions that will trigger the documentation search. For example:

Could you explain how to use FAISS with LangChain? Please search the langchain documentation to help me.

Claude will automatically use your MCP server to:

1. 🔍 Search for relevant documentation

2. 📥 Retrieve the content

3. 🧠 Process and explain the information

🔧 Under the Hood

📄 Code Structure

claude-docs-assistant/
├── main.py           # MCP server implementation
├── requirements.txt  # Project dependencies
├── .env              # Environment variables (API keys)
└── README.md         # This documentation

🔌 Supported Libraries

The assistant currently supports searching documentation for:

• 🦜 LangChain: python.langchain.com/docs

• 🦙 LlamaIndex: docs.llamaindex.ai/en/stable

• 🧠 OpenAI: platform.openai.com/docs

🧩 How It Works

1. 📡 The MCP server exposes a get_docs tool to Claude

2. 🔍 When invoked, the tool searches for documentation using Serper API

3. 📚 Results are scraped for their content

4. 🔄 Content is returned to Claude for analysis and explanation

🛠️ Advanced Configuration

Adding New Documentation Sources

Extend the docs_urls dictionary in main.py:

docs_urls = {
    "langchain": "python.langchain.com/docs",
    "llama-index": "docs.llamaindex.ai/en/stable",
    "openai": "platform.openai.com/docs",
    "huggingface": "huggingface.co/docs",  # Add new documentation sources
    "tensorflow": "www.tensorflow.org/api_docs",
}

Customizing Search Behavior

Modify the search_web function to adjust the number of results:

payload = json.dumps({"q": query, "num": 5})  # Increase from default 2

🔍 Troubleshooting

Common Issues

• 🚫 "Connection refused" error: Ensure the MCP server is running before connecting Claude

• ⏱️ Timeout errors: Check your internet connection or increase the timeout value

• 🔒 API key issues: Verify your Serper API key is correct in the .env file

Debugging Tips

Add more detailed logging by modifying the main.py file:

import logging
logging.basicConfig(level=logging.DEBUG)

📈 Performance Optimization

• ⚡ For faster response times, consider caching frequently accessed documentation

• 🧠 Limit the amount of text returned to Claude to avoid token limitations

• 🌐 Use more specific queries to get more relevant documentation

🤝 Contributing

Contributions are welcome! Here's how you can help:

1. 🍴 Fork the repository

2. 🌿 Create a feature branch (git checkout -b feature/amazing-feature)

3. 💾 Commit your changes (git commit -m 'Add some amazing feature')

4. 📤 Push to the branch (git push origin feature/amazing-feature)

5. 🔍 Open a Pull Request

📜 License

This project is licensed under the MIT License - see the LICENSE file for details.

🙏 Acknowledgements

• Anthropic for creating Claude

• Serper.dev for their search API

• All the open-source libraries that make this project possible