# kaggle-mcp-server

> Use this tool when you need to manage Kaggle resources efficiently, as it solves problems related to competition, dataset, and model management through a natural language interface, accepting text-based inputs and providing outputs in a user-friendly format, ideal for data scientists and Kaggle users seeking streamlined workflow management. It enables users to interact with the Kaggle API using everyday language, simplifying tasks such as submitting competitions, sharing datasets, and collaborating on notebooks. This tool is particularly useful for those who want to automate repetitive tasks or prefer a more intuitive way of interacting with the Kaggle platform.

Canonical page: https://skillsregistry.net/skills/tripathysagar-kaggle-mcp-server  
JSON: https://api.skillsregistry.net/v1/skills/tripathysagar-kaggle-mcp-server

## Description

A full-featured MCP server with 96 tools for the Kaggle API, enabling users to manage competitions, datasets, notebooks, models, discussions, and workflows via natural language.

## Trust

- **Trust score (0–1):** 0.68
- **Verification tier:** scanned
- **Last scanned:** 2026-08-31

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** other
- **Updated:** 2026-08-31

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/byztpftxqy)
- **Repository:** <https://github.com/tripathysagar/kaggle-mcp-server>

## 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": "tripathysagar-kaggle-mcp-server"
    }
  }
}
```

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

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt