Kaggle

A MCP server for Kaggle Apis

Components

Tools

The server implements one tool:

• add-note: Adds a new note to the server
  • Takes "name" and "content" as required string arguments
  • Updates server state and notifies clients of resource changes

Configuration

Ensure that you have downloaded your Kaggle credentials (kaggle.json) and placed it in the ~/.kaggle/ directory (this is the default location where the Kaggle API looks for your credentials)

Otherwise you can add the env KAGGLE_USERNAME and KAGGLE_KEY to the mcp config

Quickstart

Install

Claude Desktop

On MacOS: ~/Library/Application\ Support/Claude/claude_desktop_config.json On Windows: %APPDATA%/Claude/claude_desktop_config.json

Development/Unpublished Servers Configuration

``` "mcpServers": { "kaggle-mcp": { "command": "uv", "args": [ "--directory", "/Users/{username}/Work/kaggle-mcp", "run", "kaggle-mcp" ] } } ```

Published Servers Configuration

``` "mcpServers": { "kaggle-mcp": { "command": "uvx", "args": [ "kaggle-mcp" ] } } ```

Development

Building and Publishing

To prepare the package for distribution:

1. Sync dependencies and update lockfile:

uv sync

2. Build package distributions:

uv build

This will create source and wheel distributions in the dist/ directory.

3. Publish to PyPI:

uv publish

Note: You'll need to set PyPI credentials via environment variables or command flags:

• Token: --token or UV_PUBLISH_TOKEN
• Or username/password: --username/UV_PUBLISH_USERNAME and --password/UV_PUBLISH_PASSWORD

Debugging

Since MCP servers run over stdio, debugging can be challenging. For the best debugging experience, we strongly recommend using the MCP Inspector.

You can launch the MCP Inspector via npm with this command:

npx @modelcontextprotocol/inspector uv --directory /Users/{username}/Work/kaggle-mcp run kaggle-mcp

Upon launching, the Inspector will display a URL that you can access in your browser to begin debugging.