Kaggle-MCP: Kaggle API Integration for Claude AI
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Kaggle-MCP connects Claude AI to the Kaggle API through the Model Context Protocol (MCP), enabling competition, dataset, and kernel operations through the AI interface.
Features
- Authentication: Securely authenticate with your Kaggle credentials
- Competitions: Browse, search, and download data from Kaggle competitions
- Datasets: Find, explore, and download datasets from Kaggle
- Kernels: Search for and analyze Kaggle notebooks/kernels
- Models: Access pre-trained models available on Kaggle
Quick Installation
The following commands install the base version of Kaggle-MCP.
macOS / Linux
# Install with a single command
curl -LsSf https://raw.githubusercontent.com/54yyyu/kaggle-mcp/main/install.sh | sh
Windows
# Download and run the installer
powershell -c "Invoke-WebRequest -Uri https://raw.githubusercontent.com/54yyyu/kaggle-mcp/main/install.ps1 -OutFile install.ps1; .\install.ps1"
Manual Installation
# Install with pip
pip install git+https://github.com/54yyyu/kaggle-mcp.git
# Or better, install with uv
uv pip install git+https://github.com/54yyyu/kaggle-mcp.git
Configuration
After installation, run the setup utility to configure Claude Desktop:
kaggle-mcp-setup
This will locate and update your Claude Desktop configuration file, which is typically found at:
- macOS:
~/Library/Application Support/Claude/claude_desktop_config.json - Windows:
%APPDATA%\Claude\claude_desktop_config.json - Linux:
~/.config/Claude/claude_desktop_config.json
Manual Configuration
Alternatively, you can manually add the following to your Claude Desktop configuration:
{
"mcpServers": {
"kaggle": {
"command": "kaggle-mcp"
}
}
}
Kaggle API Credentials
To use Kaggle-MCP, you need to set up your Kaggle API credentials:
- Go to your Kaggle account settings
- In the API section, click "Create New API Token"
- This will download a
kaggle.jsonfile with your credentials - Move this file to
~/.kaggle/kaggle.json(create the directory if needed) - Set the correct permissions:
chmod 600 ~/.kaggle/kaggle.json
Alternatively, you can authenticate directly through Claude using the authenticate() tool with your username and API key.
Available Tools
For a comprehensive list of available tools and their detailed usage, please refer to the documentation at stevenyuyy.us/kaggle-mcp.
Examples
Ask Claude:
- "Authenticate with Kaggle using my username 'username' and key 'apikey'"
- "List active Kaggle competitions"
- "Show me the top 10 competitors on the Titanic leaderboard"
- "Find datasets about climate change"
- "Download the Boston housing dataset"
- "Search for kernels about sentiment analysis"
Use Cases
- Competition Research: Quickly access competition details, data, and leaderboards
- Dataset Discovery: Find and download datasets for analysis projects
- Learning Resources: Locate relevant kernels and notebooks for specific topics
- Model Discovery: Find pre-trained models for various machine learning tasks
Requirements
- Python 3.8 or newer
- Claude Desktop or API access
- Kaggle account with API credentials
- MCP Python SDK 1.6.0+
License
This project is licensed under the MIT License - see the LICENSE file for details.
Metadata
Release files for iflow-mcp_kaggle-mcp 0.1.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| iflow_mcp_kaggle_mcp-0.1.2.tar.gz | 16.0 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| iflow_mcp_kaggle_mcp-0.1.2-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 37.7 kB
Release files / iflow_mcp_kaggle_mcp-0.1.2.tar.gz
| Download URL | iflow_mcp_kaggle_mcp-0.1.2.tar.gz |
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Release files / iflow_mcp_kaggle_mcp-0.1.2-py3-none-any.whl
| Download URL | iflow_mcp_kaggle_mcp-0.1.2-py3-none-any.whl |
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| Tags | Python 3 |
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