What is Kaggle

Kaggle is a platform for data science competitions, allowing users to collaborate, share datasets, and build models using machine learning techniques. The Kaggle MCP Server facilitates interaction with Kaggle competitions through AI assistants like Claude.

Use cases

Use cases for Kaggle include participating in data science competitions, collaborating on data projects, building predictive models, and exploring datasets for insights and trends.

How to use

To use the Kaggle MCP Server, you need to install Node.js, TypeScript, and the Kaggle CLI. Authenticate using either a kaggle.json file or by configuring your credentials in the Claude desktop configuration file.

Key features

Key features of the Kaggle MCP Server include seamless integration with Kaggle competitions, support for AI-assisted data analysis, and the ability to manage Kaggle datasets and submissions efficiently.

Where to use

Kaggle is widely used in fields such as data science, machine learning, artificial intelligence, and analytics, making it suitable for both academic research and industry applications.

Kaggle MCP Server

A Model Context Protocol (MCP) server for interacting with Kaggle competitions through Claude or other compatible AI assistants.

📖 Learn More

Want to understand the full potential of this server? Check out the detailed article:

AI-Powered Data Science Revolution: How Kaggle MCP Server Transforms AI Capabilities

Prerequisites

• Node.js 16 or higher
• TypeScript
• Kaggle CLI installed (pip install kaggle)
• Kaggle API credentials configured

Authentication Setup

There are two ways to authenticate with the Kaggle API:

Option 1: Using a kaggle.json file (Standard approach)

1. Install the Kaggle CLI:

pip install kaggle

2. Go to https://www.kaggle.com/account and click “Create New API Token”
3. This will download a kaggle.json file with your credentials
4. Create a .kaggle directory in your home folder (if it doesn’t exist)

# On Linux/Mac
mkdir -p ~/.kaggle

# On Windows (PowerShell)
New-Item -ItemType Directory -Force -Path "$HOME\.kaggle"

5. Move the downloaded kaggle.json file to the .kaggle directory:

# On Linux/Mac
mv ~/Downloads/kaggle.json ~/.kaggle/
chmod 600 ~/.kaggle/kaggle.json  # Set permissions

# On Windows (PowerShell)
Move-Item -Path "$HOME\Downloads\kaggle.json" -Destination "$HOME\.kaggle\kaggle.json"

Option 2: Using Claude for Desktop Configuration (Simpler)

You can directly add your Kaggle credentials to your claude_desktop_config.json file:

{
  "mcpServers": {
    "kaggle": {
      "command": "node",
      "args": [
        "/path/to/build/index.js"
      ],
      "env": {
        "KAGGLE_USERNAME": "your-kaggle-username",
        "KAGGLE_KEY": "your-kaggle-api-key"
      }
    }
  }
}

Replace your-kaggle-username and your-kaggle-api-key with your actual Kaggle credentials.

Installation

1. Clone this repository
2. Install dependencies:

npm install

3. Build the project:

npm run build

Usage

Running the server

npm start

Or directly:

node build/index.js

Connecting with Claude for Desktop

Add the following configuration to your claude_desktop_config.json file.

Example Queries

Once connected to Claude, you can ask questions like:

• “Show me the active Kaggle competitions”
• “Search for image classification competitions”
• “Download the files for the Titanic competition”
• “Submit my predictions.csv file to the housing-prices competition with the message ‘Random forest model’”
• “Show me my submissions for the digit-recognizer competition”

Troubleshooting

Authentication Issues

If you encounter authentication errors:

1. Verify your credentials are correctly set:

   • If using kaggle.json, check it’s in the correct location:
     • Linux/Mac: ~/.kaggle/kaggle.json
     • Windows: C:\Users\<USERNAME>\.kaggle\kaggle.json
   • If using environment variables, check the env section in your claude_desktop_config.json

2. For kaggle.json, check if the file has the correct permissions:

   • On Linux/Mac, run: chmod 600 ~/.kaggle/kaggle.json

3. Make sure your API token is still valid. If needed, generate a new one from your Kaggle account page.

Installation Issues

If the Kaggle CLI is not found:

1. Make sure you have installed it with: pip install kaggle
2. Verify that the Kaggle command is in your PATH by running: kaggle --version

Current Capabilities

The server currently provides the following operations for Kaggle competitions:

🔍 List Competitions

• List all active Kaggle competitions
• Search competitions by keyword
• Support for pagination to browse through results
• Display competition details including name, category, deadline, and prize

📥 Download Competition Files

• Download files for any competition
• Specify custom download path
• Force re-download of existing files
• Works with all public competition datasets

📤 Submit to Competitions

• Submit prediction files to competitions
• Add custom submission messages
• Get immediate feedback on submission status
• Requires prior acceptance of competition rules on Kaggle website

📋 List Submissions

• View submission history for a specific competition
• See submission status and scores
• Track multiple submissions over time

All Features Now Available

All the features previously listed as “Coming Soon” are now available in the feature-complete branch of this repository. This includes:

• Dataset Operations: Browse, search, download, and analyze datasets from Kaggle
• Notebook Integration: Work with Kaggle notebooks directly from your AI assistant
• User Management: Check profile information and competition standings
• Competition Analysis: Get detailed competition metrics and leaderboard insights

Check out the feature-complete branch for the most up-to-date and comprehensive implementation of the Kaggle MCP server.

License

MIT