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arrismo/kaggle-mcp

by Various

MCP server for Kaggle

A

MCP

arrismo/kaggle-mcp

Added 1 June 2026

#kaggle #mcp-server

Overview

A Python-based MCP server that exposes Kaggle API functionality as callable tools for AI agents. It enables language models to retrieve datasets, query competitions, and submit results through the Model Context Protocol. The server acts as a bridge between Kaggle's data science platform and agentic workflows.

Best for

Best for
Developers automating Kaggle data science workflows through AI agents

Use cases

  • Fetching Kaggle datasets for automated data analysis
  • Submitting competition entries via AI assistants
  • Querying competition leaderboards and metadata

Notes

A Python-based MCP server that exposes Kaggle API functionality as callable tools for AI agents. It enables language models to retrieve datasets, query competitions, and submit results through the Model Context Protocol. The server acts as a bridge between Kaggle’s data science platform and agentic workflows.

35 stars on GitHub. Last updated 2026-05-21. Licensed MIT.

Use cases

  • Fetching Kaggle datasets for automated data analysis
  • Submitting competition entries via AI assistants
  • Querying competition leaderboards and metadata

Pros

  • Simple setup for integrating Kaggle with MCP-based tools
  • Open source with Python, easy to modify or extend
  • Enables automation of common Kaggle tasks via LLMs

Cons

  • Small community and limited documentation due to low star count
  • Requires Kaggle API credentials and manual configuration
  • May not cover all Kaggle features or handle rate limits gracefully

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.

Pros

  • Simple setup for integrating Kaggle with MCP-based tools
  • Open source with Python, easy to modify or extend
  • Enables automation of common Kaggle tasks via LLMs

Cons

  • Small community and limited documentation due to low star count
  • Requires Kaggle API credentials and manual configuration
  • May not cover all Kaggle features or handle rate limits gracefully