KaggleSAFE

A Model Context Protocol (MCP) server that exposes Kaggle dataset search, download, and EDA prompt generation to MCP clients such as Claude Desktop.

Features

• Search Kaggle datasets by keyword.
• Download and unzip Kaggle datasets locally.
• Generate a starter Exploratory Data Analysis (EDA) prompt for a Kaggle dataset.
• Supports Kaggle credentials via environment variables or the standard kaggle.json file.
• Runs locally, in Docker, or through Smithery.

Available MCP Capabilities

Tools

search_kaggle_datasets(query: str)

Searches Kaggle for datasets matching query and returns up to 10 results as JSON.

Returned fields include:

• ref
• title
• subtitle
• download_count
• last_updated
• usability_rating

download_kaggle_dataset(dataset_ref: str, download_path: str | None = None)

Downloads and unzips a Kaggle dataset.

• dataset_ref: Kaggle dataset reference in owner/dataset-slug format, for example kaggle/titanic.
• download_path: Optional local output path. If omitted, files are saved to ./datasets//.

Prompts

generate_eda_notebook(dataset_ref: str)

Creates a prompt for generating basic Python EDA code for the provided Kaggle dataset reference. The prompt asks for data loading, missing-value checks, visualizations, and summary statistics.

Requirements

• Python 3.10+
• Kaggle account and API token
• An MCP-compatible client

Kaggle Credentials

Create a Kaggle API token from your Kaggle account settings:

1. Go to .
2. Select Create New API Token.
3. Download kaggle.json.

Use either environment variables or the standard Kaggle config file.

Option 1: Environment variables

Create a .env file in the project root:

KAGGLE_USERNAME=your_kagg