MCP 服务器

mcp-kaggle-tool

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

README

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

Kaggle Account: You need a Kaggle account
Kaggle API Token:
- Go to https://www.kaggle.com/account
- Click "Create New API Token"
- Save the downloaded kaggle.json to ~/.kaggle/
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