How do I set up Kaggle credentials?
Use either environment variables (`KAGGLE_USERNAME` and `KAGGLE_KEY`) in a `.env` file, or place your `kaggle.json` file in the standard Kaggle location (`~/.kaggle/kaggle.json` on macOS/Linux).
Kaggle MCP (MCP) Server
@arrismo
Basic information
About Kaggle MCP (MCP) Server
MCP server for Kaggle
Kaggle MCP (MCP) Server config
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"kaggle-mcp": {
"command": "python",
"args": [
"-m",
"venv",
".venv"
]
}
}
}Kaggle MCP (MCP) Server tools
Tool list not available yet
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We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.
Overview
What is Kaggle MCP (Model Context Protocol) Server?
It is a Model Context Protocol (MCP) server that exposes Kaggle dataset search, download, and EDA prompt generation to MCP clients such as Claude Desktop. It is intended for data scientists and developers who want to interact with Kaggle datasets through AI assistants.
How to use Kaggle MCP (Model Context Protocol) Server?
Install dependencies using uv sync or pip install -r requirements.txt, set up Kaggle credentials via environment variables or kaggle.json, then run the server with uv run kaggle-mcp or python src/server.py. Configure your MCP client (e.g., Claude Desktop) by adding the server to its config file with the appropriate command and environment variables.
Key features of Kaggle MCP (Model Context Protocol) Server
- Search Kaggle datasets by keyword.
- Download and unzip Kaggle datasets locally.
- Generate a starter exploratory data analysis (EDA) prompt.
- Supports Kaggle credentials via environment variables or
kaggle.json. - Runs locally, in Docker, or through Smithery.
- Communicates over MCP stdio with clients like Claude Desktop.
Use cases of Kaggle MCP (Model Context Protocol) Server
- Search for Kaggle datasets by keyword from an AI assistant.
- Download and unzip a specific dataset to a local directory.
- Generate an EDA notebook prompt to kickstart data analysis.
- Integrate Kaggle dataset workflows into a Claude Desktop session.
Frequently asked questions
What are the system requirements?
Python 3.10 or higher, a Kaggle account with an API token, and an MCP-compatible client (e.g., Claude Desktop).
How do I run the server in Docker?
Build the image with `docker build -t kaggle-mcp .` and run it with `docker run --rm -i --env-file .env kaggle-mcp` (using a `.env` file with your credentials).
How do I configure the server for Claude Desktop?
Add the server to `claude_desktop_config.json` under `mcpServers` with the command
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