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Kaggle-MCP: Kaggle API Integration for Claude AI

@54yyyu

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基本情報

カテゴリ

データと分析

ライセンス

MIT

トランスポート

stdio

作者

54yyyu

Kaggle-MCP: Kaggle API Integration for Claude AI について

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.

#mcp#kaggle#claude-ai#mcp-server

Kaggle-MCP: Kaggle API Integration for Claude AI の設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

{
  "mcpServers": {
    "kaggle-mcp-54yyyu": {
      "command": "uv",
      "args": [
        "pip",
        "install",
        "git+https://github.com/54yyyu/kaggle-mcp.git"
      ]
    }
  }
}

Kaggle-MCP: Kaggle API Integration for Claude AI のツール

ツール一覧はまだありません

この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。

ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

What is Kaggle-MCP?

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. It is built for data scientists, machine learning practitioners, and anyone who wants to interact with Kaggle’s resources using natural language.

How to use Kaggle-MCP?

Install via the provided one-line script (curl on macOS/Linux, powershell on Windows) or manually with pip or uv. After installation, run kaggle-mcp-setup to update your Claude Desktop configuration, or manually add the server entry to the Claude Desktop config file. Obtain Kaggle API credentials from your Kaggle account settings, place the kaggle.json file in ~/.kaggle/, and secure it with chmod 600. Then ask Claude to list competitions, download datasets, search kernels, and more.

Key features of Kaggle-MPC

  • 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

Use cases of Kaggle-MPC

  • 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

よくある質問

1

How do I set up Kaggle API credentials?

Go to your Kaggle account settings, click “Create New API Token” to download a `kaggle.json` file, move it to `~/.kaggle/kaggle.json`, and set permissions with `chmod 600 ~/.kaggle/kaggle.json`. Alternatively, authenticate directly through Claude using the `authenticate()` tool with your username and API key.

2

Where is the Claude Desktop configuration file located?

The configuration file is typically at `~/Library/Application Support/Claude/claude_desktop_config.json` on macOS, `%APPDATA%\Claude\claude_desktop_config.json` on Windows, and `~/.config/Claude/claude_desktop_config.json` on Linux.

3

What are the system requirements?

Python 3.8 or newer, Claude Desktop or API access, a Kaggle account with API credentials, and MCP Python SDK 1.6.0+.

4

How can I install Kaggle-MCP?

Use the one‑line installer: `curl -LsSf https://raw.githubusercontent.com/54yyyu/kaggle-mcp/main/install.sh | sh` on macOS/Linux or the PowerShell equivalent on Windows. You can also install manually with `pip install git+https://github.com/54yyyu/kaggle-mcp.git` (or with `uv`).

5

What can I do with Kaggle-MCP after setup?

You can list active competitions, view leaderboards, download datasets (e.g., Boston housing), search for kernels about sentiment analysis, find datasets about climate change, and authenticate with your username and API key—all through natural‑language commands to Claude.

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