How do I install Kaggle?

Copy the stdio config for Cursor, Claude Desktop, Claude Code, or VS Code on this page. It uses the publisher's install, not a PlugMCP proxy.

Does Kaggle need an API key?

The publisher lists these environment variables: KAGGLE_USERNAME, KAGGLE_API_KEY.

What transport does Kaggle use?

Kaggle runs locally over stdio.

When was Kaggle last checked?

Last checked 2026-11-09. MCP server for the Kaggle API: competitions, datasets, kernels, and models.

Kaggle MCP server

Power your agent

Add this server

The publisher's own command. Not a PlugMCP endpoint.

Add to Cursor Add to VS Code Run on PlugMCP

Host a copy with our keys and logs.

Local command

uvx mcp-server-kaggle==0.1.1

Credentials from the publisher

KAGGLE_USERNAME — Your Kaggle account username
KAGGLE_API_KEY — Your Kaggle API key (from https://www.kaggle.com/account)

Claude Code has no install link for a local command. Copy the command below and run it in a terminal.

shClaude Code

1KAGGLE_USERNAME=<value> KAGGLE_API_KEY=<secret> claude mcp add io.github.seif-sameh-kaggle-mcp -- uvx mcp-server-kaggle==0.1.1

Run in a terminal.

jsonClaude Desktop

1{2  "mcpServers": {3    "io.github.seif-sameh-kaggle-mcp": {4      "command": "uvx",5      "args": [6        "mcp-server-kaggle==0.1.1"7      ],8      "env": {9        "KAGGLE_USERNAME": "<value>",10        "KAGGLE_API_KEY": "<secret>"11      }12    }13  }14}

claude_desktop_config.json

Local · pypiPublisher installStep-by-step: add this in Claude

Remote URL or a command on your machine? How the two installs differ

Run on PlugMCP

Host a copy with our keys and logs.

A new server you create. It is not this listing's official endpoint. Use the publisher install when you want their URL and their credentials.

Launch

Server facts

Local

Transport: stdio
Version: 0.1.1
API key

Tools

No tool list yet. Remote servers get one after the first health check.

FAQ

Questions

Kaggle MCP Server

A Model Context Protocol (MCP) server that provides seamless integration with the Kaggle API. Interact with Kaggle competitions, datasets, kernels, and models through MCP-compatible clients like Claude Desktop.

Features

Competitions: List, download files, submit, view leaderboards and submissions
Datasets: Search, download, create, and manage datasets with version control
Kernels: List, push, pull, and manage Kaggle notebooks and scripts
Models: Create, update, and manage ML models and instances with full version control

Installation

Prerequisites

Python 3.10 or higher
A Kaggle account with API credentials

Install from PyPI

The recommended way is to run the server with uvx, which handles the install for you:

uvx mcp-server-kaggle

Or install it explicitly:

pip install mcp-server-kaggle
# or
uv tool install mcp-server-kaggle

Install from Source

For development or local modifications:

git clone https://github.com/Seif-Sameh/Kaggle-mcp.git
cd Kaggle-mcp
uv sync

Setup

1. Get Your Kaggle API Credentials

Go to https://www.kaggle.com/account
Scroll to the "API" section
Click "Create New Token"
This downloads kaggle.json with your credentials

2. Configure Credentials

Option A: Environment Variables (Recommended)

export KAGGLE_USERNAME=your_username
export KAGGLE_API_KEY=your_api_key

Or add to your ~/.zshrc or ~/.bashrc:

echo 'export KAGGLE_USERNAME=your_username' >> ~/.zshrc
echo 'export KAGGLE_API_KEY=your_api_key' >> ~/.zshrc
source ~/.zshrc

Option B: Using .env File

Create a .env file in your project directory:

KAGGLE_USERNAME=your_username
KAGGLE_API_KEY=your_api_key

Usage

With Claude Desktop

The recommended way to use Kaggle MCP is with Claude Desktop.

Locate your Claude Desktop config file:
- macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
- Windows: %APPDATA%\Claude\claude_desktop_config.json
- Linux: ~/.config/Claude/claude_desktop_config.json
Add the Kaggle MCP server configuration:

{
  "mcpServers": {
    "kaggle": {
      "command": "uvx",
      "args": ["mcp-server-kaggle"],
      "env": {
        "KAGGLE_USERNAME": "YOUR_KAGGLE_USERNAME",
        "KAGGLE_API_KEY": "YOUR_KAGGLE_API_KEY"
      }
    }
  }
}

{
  "mcpServers": {
    "kaggle": {
      "command": "uv",
      "args": [
        "--directory",
        "/ABSOLUTE/PATH/TO/Kaggle-mcp",
        "run",
        "mcp-server-kaggle"
      ],
      "env": {
        "KAGGLE_USERNAME": "YOUR_KAGGLE_USERNAME",
        "KAGGLE_API_KEY": "YOUR_KAGGLE_API_KEY"
      }
    }
  }
}

Restart Claude Desktop
Start using Kaggle through Claude!

Try asking Claude:

"List the latest Kaggle competitions"
"Download the Titanic dataset"
"Show me my recent competition submissions"
"Search for NLP datasets"

Standalone Usage

Run the MCP server directly:

mcp-server-kaggle

Or as a Python module:

python -m kaggle_mcp

Available Tools

Competitions (8 tools)

Tool	Description
`competitions_list`	List and search available competitions
`competition_list_files`	List all files in a competition
`competition_download_file`	Download a specific competition file
`competition_download_files`	Download all competition files
`competition_submit`	Submit predictions to a competition
`competition_submissions`	View your submission history
`competition_leaderboard_view`	View the competition leaderboard
`competition_leaderboard_download`	Download leaderboard data

Datasets (10 tools)

Tool	Description
`datasets_list`	Search and filter datasets
`dataset_metadata`	Get dataset metadata
`dataset_list_files`	List files in a dataset
`dataset_status`	Check dataset processing status
`dataset_download_file`	Download a specific dataset file
`dataset_download_files`	Download all dataset files
`dataset_create`	Create a new dataset
`dataset_initialize`	Initialize dataset metadata
`dataset_create_version`	Create a new dataset version

Kernels (7 tools)

Tool	Description
`kernels_list`	Search and filter kernels
`kernel_list_files`	List files in a kernel
`kernel_initialize`	Initialize kernel metadata
`kernel_push`	Push a kernel to Kaggle
`kernel_pull`	Download a kernel
`kernel_output`	Download kernel output files
`kernel_status`	Check kernel execution status

Models (14 tools)

Tool	Description
`models_list`	Search and filter models
`model_get`	Get model details and metadata
`model_initialize`	Initialize model metadata
`model_create`	Create a new model
`model_update`	Update model information
`model_delete`	Delete a model
`model_instance_get`	Get model instance details
`model_instance_initialize`	Initialize model instance metadata
`model_instance_create`	Create a new model instance
`model_instance_update`	Update a model instance
`model_instance_delete`	Delete a model instance
`model_instance_version_create`	Create a new model version
`model_instance_version_download`	Download a model version
`model_instance_version_delete`	Delete a model version

Examples

Example 1: Working with Competitions

Ask Claude:

"List active Kaggle competitions about computer vision"

Claude will use the competitions_list tool to search and display relevant competitions.

Example 2: Downloading Datasets

Ask Claude:

"Download the Titanic dataset to my Downloads folder"

Claude will use dataset_download_files to fetch all dataset files.

Example 3: Submitting to Competitions

Ask Claude:

"Submit my predictions.csv to the Titanic competition with the message 'Initial baseline model'"

Claude will use competition_submit to upload your submission.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Add this server

Host a copy with our keys and logs.

Server facts

Tools

Questions

How do I install Kaggle?

Does Kaggle need an API key?

What transport does Kaggle use?

When was Kaggle last checked?

Documentation

Kaggle MCP Server

Features

Installation

Prerequisites

Install from PyPI

Install from Source

Setup

1. Get Your Kaggle API Credentials

2. Configure Credentials

Usage

With Claude Desktop

Standalone Usage

Available Tools

Competitions (8 tools)

Datasets (10 tools)

Kernels (7 tools)

Models (14 tools)

Examples

Example 1: Working with Competitions

Example 2: Downloading Datasets

Example 3: Submitting to Competitions

License