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Kaggle Mcp

mcp-54yyyu-kaggle-mcp · by 54yyyu

Kaggle-MCP: Connect Claude AI to the Kaggle API through the Model Context Protocol (MCP), enabling competition, dataset, and kernel operations through the AI interface.

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Install

$ agentstack add mcp-54yyyu-kaggle-mcp

Open-source listing — not yet scanned by AgentStack. Follow the source repository for install instructions.

Security review

⚠ Flagged

1 finding(s); flagged for manual review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures
  • high Pipes remote content directly into a shell (remote code execution).

What it can access

  • Network access Used
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

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About

[](https://mseep.ai/app/54yyyu-kaggle-mcp)

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:

  1. Go to your Kaggle account settings
  2. In the API section, click "Create New API Token"
  3. This will download a kaggle.json file with your credentials
  4. Move this file to ~/.kaggle/kaggle.json (create the directory if needed)
  5. 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.

Source & license

This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

Reviews

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Versions

  • v0.1.0 Imported from the upstream source.