Kaggle MCP Server

Full Kaggle CLI as a Model Context Protocol (MCP) server — 68 tools (v3.0).

Works with Claude Desktop, Claude Code, OpenAI Codex CLI, Cursor, Hermes Agent, Windsurf, OpenCode, VS Code MCP, Continue.dev, and any stdio MCP client.

What you can do

Transports

• --stdio preferred for agents

• --port N HTTP SSE + /rpc for custom clients

Related MCP server: Kaggle MCP Server

Install

git clone https://github.com/mtrakretech/kaggle-mcp.git
cd kaggle-mcp
pip install -r requirements.txt

Credentials (recommended: terminal setup)

python kaggle_mcp.py --setup

What it does:

1. Tells you where to get a token: https://www.kaggle.com/settings → API → Create New Token

2. Asks for username + API key (key input hidden)

3. Optionally reuses a downloaded kaggle.json (cwd / Downloads / ~/.kaggle)

4. Saves:

   • ~/.kaggle/kaggle.json (chmod 600 when possible)

   • project .env (KAGGLE_USERNAME, KAGGLE_KEY, KAGGLE_API_TOKEN)

5. Validates with kaggle quota

Non-interactive:

python kaggle_mcp.py --setup --username YOUR_USER --key YOUR_KEY
python kaggle_mcp.py --setup --from-json ~/Downloads/kaggle.json
python kaggle_mcp.py --setup --no-env          # only ~/.kaggle/kaggle.json
python kaggle_mcp.py --setup --no-validate    # skip API check

Manual alternatives:

export KAGGLE_USERNAME=your_username
export KAGGLE_KEY=your_api_key
export KAGGLE_API_TOKEN=$KAGGLE_KEY

Or hand-write ~/.kaggle/kaggle.json:

{"username":"your_username","key":"your_api_key"}

Quick test

python kaggle_mcp.py --setup          # first time
python kaggle_mcp.py --list-tools
python kaggle_mcp.py --stdio

Client setup

Replace /ABSOLUTE/PATH/TO/kaggle-mcp/kaggle_mcp.py with your real path.
Copy-paste examples: examples/.

Claude Desktop

%APPDATA%\Claude\claude_desktop_config.json (Windows) / ~/Library/Application Support/Claude/claude_desktop_config.json (macOS):

{
  "mcpServers": {
    "kaggle": {
      "command": "python",
      "args": ["/ABSOLUTE/PATH/TO/kaggle-mcp/kaggle_mcp.py", "--stdio"],
      "env": {
        "KAGGLE_USERNAME": "your_kaggle_username",
        "KAGGLE_KEY": "your_kaggle_api_key",
        "KAGGLE_API_TOKEN": "your_kaggle_api_key"
      }
    }
  }
}

Claude Code / Cursor / Windsurf

Same mcpServers.kaggle JSON shape as above.

Codex CLI (~/.codex/config.toml)

[mcp_servers.kaggle]
command = "python"
args = ["/ABSOLUTE/PATH/TO/kaggle-mcp/kaggle_mcp.py", "--stdio"]

[mcp_servers.kaggle.env]
KAGGLE_USERNAME = "your_kaggle_username"
KAGGLE_KEY = "your_kaggle_api_key"
KAGGLE_API_TOKEN = "your_kaggle_api_key"

Hermes Agent (config.yaml)

mcp_servers:
  kaggle:
    command: python
    args:
      - /ABSOLUTE/PATH/TO/kaggle-mcp/kaggle_mcp.py
      - --stdio
    env:
      KAGGLE_USERNAME: your_kaggle_username
      KAGGLE_KEY: your_kaggle_api_key
      KAGGLE_API_TOKEN: your_kaggle_api_key
    timeout: 180

Use stdio (not HTTP SSE) with Hermes.

OpenCode / VS Code / Continue

See examples/opencode_config.json, examples/vscode_mcp.json, examples/continue_config.yaml.

Tools (68)

Kernels (15)

search_kernels list_my_kernels kernel_status kernel_logs kernel_files kernel_output pull_notebook push_notebook init_kernel update_kernel delete_kernel preview_notebook toggle_kernel_visibility list_kernel_topics show_kernel_topic

Datasets (13)

search_datasets list_my_datasets dataset_details list_dataset_files download_dataset init_dataset upload_dataset update_dataset get_dataset_metadata dataset_status delete_dataset list_dataset_topics show_dataset_topic

Competitions (13)

list_competitions list_competition_files download_competition_data submit_competition list_competition_submissions competition_leaderboard list_team_submissions list_competition_episodes download_competition_replay download_competition_episode_logs list_competition_pages list_competition_topics show_competition_topic

Models (17)

list_models model_details init_model create_model update_model delete_model list_model_instances get_model_instance init_model_instance create_model_instance update_model_instance delete_model_instance list_model_instance_versions list_model_version_files download_model_version create_model_version delete_model_version list_model_topics

Forums / Benchmarks / Account (10)

list_forums list_forum_topics show_forum_topic list_benchmark_tasks list_benchmark_models benchmark_task_status get_quota get_account_info get_config

Live test notes (v3.0)

Verified working against real API on this machine:

• kernels search/list/status/logs/files/pull/preview/output

• datasets search/list/details/files/metadata/download/topics

• competitions list/files/leaderboard/pages/topics/team-submissions

• models list/get/instances/versions

• forums list/topics, benchmarks list/models, quota, config, init skeletons

Known Kaggle-side soft fails (tool wiring OK; API returns error):

• dataset_status → 404 on some public datasets

• list_competition_submissions → 400 if you never entered the competition

• list_model_version_files / some instance paths → 404 if version ref wrong

• topic show_* → 429 under rate limit (retry later)

Destructive tools (delete_*, submit_competition, push_notebook, uploads) are implemented but not auto-run in CI-style tests.

Security

• No hardcoded credentials

• Env vars or ~/.kaggle/kaggle.json only

• Key never leaves your machine except to Kaggle

License

MIT — see LICENSE

Links

• Repo: https://github.com/mtrakretech/kaggle-mcp

• Kaggle token: https://www.kaggle.com/settings

• MCP: https://modelcontextprotocol.io/