MCP 服务器

kaggle-mcp

A full-featured MCP server for the Kaggle API — competitions, datasets, kernels, models, benchmarks, and discussions.

README

A full-featured MCP server for the Kaggle API — competitions, datasets, kernels, models, benchmarks, and discussions.

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Why kaggle-mcp?

Kaggle provides an official remote MCP server (https://www.kaggle.com/mcp) covering competitions, datasets, notebooks, models, and benchmarks — a solid foundation for most Kaggle workflows.

kaggle-mcp extends that foundation with what the official server is missing: 10 discussion tools. You can search discussions, browse by source type, filter competition discussions by recency, read solution write-ups, explore trending topics, and more — none of which are available in the official MCP.

It also runs locally over stdio, so there's no remote MCP dependency and no npx mcp-remote required.

Use kaggle-mcp if you need discussion tools or prefer a local stdio setup without remote dependencies. Use the official MCP if you prefer OAuth 2.0 auth or want zero local installation.

Quick Navigation

Section	Description
Prerequisites	Kaggle API token setup
Installation	uvx / pip / source
Configuration	Claude Desktop, Claude Code, VS Code, Cursor
Tools (51)	Competitions, Datasets, Kernels, Models, Benchmarks, Discussions
Debugging	MCP Inspector
Development	Local development setup

Prerequisites

A Kaggle API token is required. You can authenticate using either method:

<details> <summary><b>Option A: API Token (recommended)</b></summary>

Go to https://www.kaggle.com/settings → API → Create New API Token
Set the environment variable:

export KAGGLE_API_TOKEN="KGAT_xxxxxxxxxxxx"

</details>

<details> <summary><b>Option B: kaggle.json</b></summary>

Download the token file from Kaggle settings, it will be saved to ~/.kaggle/kaggle.json:

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

</details>

Installation

Note: MCP servers are launched automatically by MCP clients (Claude Code, VS Code, etc.) — you don't need to run them manually in the terminal. The commands below are what the client uses under the hood.

Using uvx (recommended)

No installation needed. uvx will automatically download and run the server:

# Used by MCP clients internally; no need to run this yourself
uvx kaggle-mcp-server

Using pip

pip install kaggle-mcp-server

From source

git clone https://github.com/Galaxy-Dawn/kaggle-mcp.git
cd kaggle-mcp
uv sync

Configuration

Claude Desktop

Add to your claude_desktop_config.json:

<details> <summary>Using uvx (recommended)</summary>

{
  "mcpServers": {
    "kaggle": {
      "command": "uvx",
      "args": ["kaggle-mcp-server"],
      "env": {
        "KAGGLE_API_TOKEN": "KGAT_xxxxxxxxxxxx"
      }
    }
  }
}

</details>

<details> <summary>Using pip</summary>

{
  "mcpServers": {
    "kaggle": {
      "command": "python",
      "args": ["-m", "kaggle_mcp.server"],
      "env": {
        "KAGGLE_API_TOKEN": "KGAT_xxxxxxxxxxxx"
      }
    }
  }
}

</details>

Claude Code

claude mcp add kaggle -- uvx kaggle-mcp-server

Or add to your project's .mcp.json (not settings.json):

{
  "mcpServers": {
    "kaggle": {
      "command": "uvx",
      "args": ["kaggle-mcp-server"],
      "env": {
        "KAGGLE_API_TOKEN": "KGAT_xxxxxxxxxxxx"
      }
    }
  }
}

VS Code

Add to .vscode/mcp.json (note: the key is "servers", not "mcpServers"):

{
  "servers": {
    "kaggle": {
      "command": "uvx",
      "args": ["kaggle-mcp-server"],
      "env": {
        "KAGGLE_API_TOKEN": "KGAT_xxxxxxxxxxxx"
      }
    }
  }
}

Cursor

Add to .cursor/mcp.json:

{
  "mcpServers": {
    "kaggle": {
      "command": "uvx",
      "args": ["kaggle-mcp-server"],
      "env": {
        "KAGGLE_API_TOKEN": "KGAT_xxxxxxxxxxxx"
      }
    }
  }
}

Tip: If you already have KAGGLE_API_TOKEN in your shell environment (e.g. in .bashrc or .zshrc), you can omit the "env" block.