Kaggle-MCP
Enables access to Kaggle's API for browsing and searching competitions, finding and downloading datasets, accessing kernels/notebooks, and discovering pre-trained models. Supports authentication and interaction with Kaggle leaderboards.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Kaggle-MCPshow me the top 10 datasets about climate change"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
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
Related MCP server: SketchupMCP
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 | shWindows
# 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.gitConfiguration
After installation, run the setup utility to configure Claude Desktop:
kaggle-mcp-setupThis will locate and update your Claude Desktop configuration file, which is typically found at:
macOS:
~/Library/Application Support/Claude/claude_desktop_config.jsonWindows:
%APPDATA%\Claude\claude_desktop_config.jsonLinux:
~/.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 credentialsMove 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.
This server cannot be deployed
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