mcp-kaggle-tool

mcp-kaggle-tool

MCP server for Kaggle API integration that allows creating, running, and managing Kaggle notebooks programmatically.

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mcp-kaggle-tool

MCP server for Kaggle API integration - create, run, and manage Kaggle notebooks programmatically.

🚀 Features

  • ✅ Authentication check for Kaggle API
  • 📝 Create and manage Kaggle notebooks
  • 🏃 Run notebooks with GPU support
  • 📊 Search datasets and competitions
  • 💾 Download notebook outputs
  • 🔍 Monitor execution status

📋 Prerequisites

  1. Kaggle Account: You need a Kaggle account
  2. Kaggle API Token:
    • Go to https://www.kaggle.com/account
    • Click "Create New API Token"
    • Save the downloaded kaggle.json to ~/.kaggle/
  3. Kaggle CLI: Install the Kaggle CLI:
    pip install kaggle
    

🛠️ Installation

From npm (when published)

npm install -g mcp-kaggle-tool

From source

git clone https://github.com/yourusername/mcp-kaggle-tool.git
cd mcp-kaggle-tool
npm install
npm run build

🔧 Configuration

For Claude Desktop

Add to your Claude Desktop configuration (~/Library/Application Support/Claude/claude_desktop_config.json on macOS):

{
  "mcpServers": {
    "kaggle": {
      "command": "npx",
      "args": ["mcp-kaggle-tool"]
    }
  }
}

Or if running from source:

{
  "mcpServers": {
    "kaggle": {
      "command": "node",
      "args": ["/path/to/mcp-kaggle-tool/dist/index.js"]
    }
  }
}

📚 Available Tools

Authentication

  • kaggle_auth_check - Verify Kaggle API credentials are configured

Notebooks

  • kaggle_list_notebooks - List your Kaggle notebooks
  • kaggle_create_notebook - Create a new notebook with code
  • kaggle_run_notebook - Execute a notebook
  • kaggle_get_notebook_status - Check execution status
  • kaggle_download_notebook_output - Download notebook outputs

Data & Competitions

  • kaggle_search_datasets - Search for datasets
  • kaggle_list_competitions - List active competitions

💡 Usage Examples

Check Authentication

Use kaggle_auth_check to verify your credentials are set up

Create and Run a Notebook

1. Create a notebook with kaggle_create_notebook:
   - title: "My ARC Experiment"
   - code: "print('Hello from Kaggle!')"
   - enableGpu: true

2. Monitor with kaggle_get_notebook_status
3. Download results with kaggle_download_notebook_output

Search ARC Dataset

Use kaggle_search_datasets with search: "abstraction reasoning corpus"

🚧 Development

# Install dependencies
npm install

# Build TypeScript
npm run build

# Run in development
npm run dev

# Run tests
npm test

# Lint code
npm run lint

📝 License

MIT License - see LICENSE file for details.

🤝 Contributing

Contributions welcome! Please open an issue or submit a PR.

🐛 Known Issues

  • Kaggle API sometimes returns HTML instead of JSON for certain commands
  • Notebook execution status may take time to update
  • GPU availability depends on Kaggle quota

🔗 Resources

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