This project provides an MCP (Model Context Protocol) server for interacting with Kaggle from Claude Desktop (or any MCP-compatible client) 🚀 Setup 1. Clone the repository and install dependencies pip install -r requirements.txt 2. Configure Kaggle API credentials Go to your Kaggle account -> Settings Scroll to API section → click Create New API Token. This will download a file called kaggle.json. Place kaggle.json in the following location on your system: Linux/Mac: ~/.kaggle/kaggle.json Windows: C:\Users\ \.kaggle\kaggle.json 3. Configure Claude Desktop To connect Claude with this MCP server, create or update the file: Claude/claude_desktop_config.json with the following contents: { "mcpServers": { "Kaggle": { "command": " ", "args": [" "] } } } Replace with the path to your Python interpreter (e.g. python or C:/Python/python.exe). Replace with the path to this repo’s kaggle-server.py file. 📜 Usage Once configured: Start Claude Desktop. Start the Kaggle MCP server (Run kaggle-server.py as a Python File). You can now use MCP tools defined in kaggle-server.py, for example: get_competitions_list: Fetches the list of available Kaggle competitions and returns them in a JSON-friendly format. 🛠️ About the Code kaggle-server.py registers MCP tools using the @mcp.tool() decorator. The server communicates with Claude via MCP and exposes Kaggle API methods. Example tool: @mcp.tool() def get_competitions_list() -> list[dict]: """ Fetch the list of available Kaggle competitions. """ ✅ Requirements Python 3.10+ Kaggle API credentials (kaggle.json) Dependencies listed in requirements.txt 🔒 Security Notes Never commit your kaggle.json file. Ensure the .kaggle folder has restricted permissions.