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Kaggle MCP (Model Context Protocol) Server This repository contains an MCP (Model Context Protocol) server (server.py) built using the fastmcp library. It interacts with the Kaggle API to provide tools for searching and downloading datasets, and a prompt for generating EDA notebooks.
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server.py: The FastMCP server application. It defines resources, tools, and prompts for interacting with Kaggle. -
.env.example: An example file for environment variables (Kaggle API credentials). Rename to.envand fill in your details. -
requirements.txt: Lists the necessary Python packages. -
pyproject.toml&uv.lock: Project metadata and locked dependencies foruvpackage manager. -
datasets/: Default directory where downloaded Kaggle datasets will be stored.
- 1. Create a virtual environment (recommended):
Works with Claude (desktop and mobile), Cursor, Windsurf, VS Code, and any MCP-compatible AI app.
Category: Developer Tools
Don't lose this
Three weeks from now, you'll want arrismo/kaggle-mcp again. Will you remember where to find it?
Save it to your library and the next time you need arrismo/kaggle-mcp, it’s one tap away — from any AI app you use. Group it into a bench with the rest of the team for that kind of task and you can pull the whole stack at once.
⚡ Pro tip for geeks: add a-gnt 🤵🏻♂️ as a custom connector in Claude or a custom GPT in ChatGPT — one click and your library is right there in the chat. Or, if you’re in an editor, install the a-gnt MCP server and say “use my [bench name]” in Claude Code, Cursor, VS Code, or Windsurf.
a-gnt's Take
Our honest review
This plugs directly into your AI and gives it new abilities it didn't have before. arrismo/kaggle-mcp. Once connected, just ask your AI to use it. It's completely free and works across most major AI apps. This one just landed in the catalog — worth trying while it's fresh.
Tips for getting started
Tap "Get" above, pick your AI app, and follow the steps. Most installs take under 30 seconds.
What's New
Imported from awesome:punkpeye/awesome-mcp-servers
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