# Kaggle

> Use this tool when you need to interact with Kaggle's competitions, datasets, and models, or automate tasks such as browsing competitions, downloading datasets, and submitting to competitions. It solves problems related to machine learning model management, data science workflow automation, and integration with Kaggle's resources. The tool takes inputs like competition IDs, dataset names, and model parameters, and outputs results like competition listings, dataset downloads, and model submissions.

Canonical page: https://skillsregistry.net/skills/kaggle  
JSON: https://api.skillsregistry.net/v1/skills/kaggle

## Description

Kaggle-MCP provides a bridge between Claude AI and the Kaggle API, enabling AI assistants to interact with Kaggle's competitions, datasets, kernels, and models. The implementation offers a comprehensive set of tools for authenticating with Kaggle, browsing competitions, downloading datasets, managing kernels, and working with machine learning models. Built on the Model Context Protocol, it allows Claude to perform operations like listing active competitions, searching datasets, submitting to competitions, and creating or updating models—all while maintaining proper authentication and file handling. This integration is particularly valuable for data scientists and machine learning practitioners who want to leverage Claude's capabilities while working with Kaggle's resources.

## Trust

- **Trust score (0–1):** 0.50
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-04-29

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/kaggle)
- **Repository:** <https://github.com/54yyyu/kaggle-mcp>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "kaggle"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/kaggle` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/kaggle/pull`

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