Kaggle

---

name: kaggle

description: |

Kaggle API integration with managed authentication. Access datasets, models, competitions, and kernels.

Use this skill when users want to search, download, or interact with Kaggle resources.

For other third party apps, use the api-gateway skill (https://clawhub.ai/byungkyu/api-gateway).

compatibility: Requires network access and valid Maton API key

metadata:

author: maton

version: "1.0"

clawdbot:

emoji:

homepage: "https://maton.ai"

requires:

env:

- MATON_API_KEY

---

# Kaggle

Access Kaggle datasets, models, competitions, and notebooks via managed API authentication.

Quick Start

python <<'EOF'
import urllib.request, os, json
data = json.dumps({}).encode()
req = urllib.request.Request('https://gateway.maton.ai/kaggle/v1/datasets.DatasetApiService/ListDatasets', data=data, method='POST')
req.add_header('Authorization', f'Bearer {os.environ["MATON_API_KEY"]}')
req.add_header('Content-Type', 'application/json')
print(json.dumps(json.load(urllib.request.urlopen(req)), indent=2))
EOF

Base URL

https://gateway.maton.ai/kaggle/{native-api-path}

The gateway proxies requests to `api.kaggle.com` and automatically injects your credentials.

Authentication

All requests require the Maton API key:

Authorization: Bearer $MATON_API_KEY

**Environment Variable:** Set your API key as `MATON_API_KEY`:

export MATON_API_KEY="YOUR_API_KEY"

Getting Your API Key

1. Sign in or create an account at [maton.ai](https://maton.ai)

2. Go to [maton.ai/settings](https://maton.ai/settings)

3. Copy your API key

Connection Management

Manage your Kaggle connections at `https://ctrl.maton.ai`.

List Connections

python <<'EOF'
import urllib.request, os, json
req = urllib.request.Request('https://ctrl.maton.ai/connections?app=kaggle&status=ACTIVE')
req.add_header('Authorization', f'Bearer {os.environ["MATON_API_KEY"]}')
print(json.dumps(json.load(urllib.request.urlopen(req)), indent=2))
EOF

Create Connection

python <<'EOF'
import urllib.request, os, json
data = json.dumps({'app': 'kaggle'}).encode()
req = urllib.request.Request('https://ctrl.maton.ai/connections', data=data, method='POST')
req.add_header('Authorization', f'Bearer {os.environ["MATON_API_KEY"]}')
req.add_header('Content-Type', 'application/json')
print(json.dumps(json.load(urllib.request.urlopen(req)), indent=2))
EOF

Open the returned `url` in a browser to complete authentication. Kaggle uses API key authentication - you'll need to provide your Kaggle username and API key from [kaggle.com/settings](https://www.kaggle.com/settings).

Delete Connection

python <<'EOF'
import urllib.request, os, json
req = urllib.request.Request('https://ctrl.maton.ai/connections/{connection_id}', method='DELETE')
req.add_header('Authorization', f'Bearer {os.environ["MATON_API_KEY"]}')
print(json.dumps(json.load(urllib.request.urlopen(req)), indent=2))
EOF

---

API Reference

Kaggle uses an RPC-style API. All requests are POST with JSON body.

POST /kaggle/v1/{ServiceName}/{MethodName}
Content-Type: application/json

---

Datasets

#### List Datasets

POST /kaggle/v1/datasets.DatasetApiService/ListDatasets
Content-Type: application/json

{}

**Request Body Parameters:**

**Example with search:**

{
  "search": "covid"
}

**Response:**

{
  "datasets": [
    {
      "id": 9481458,
      "ref": "amar5693/screen-time-sleep-and-stress-analysis-dataset",
      "title": "Screen Time, Sleep & Stress Analysis Dataset",
      "subtitle": "ML-ready dataset analyzing smartphone usage and productivity.",
      "totalBytes": 787136,
      "downloadCount": 11659,
      "voteCount": 236,
      "usabilityRating": 1,
      "licenseName": "CC0: Public Domain",
      "ownerName": "Amar Tiwari",
      "tags": [...]
    }
  ]
}

#### Get Dataset

POST /kaggle/v1/datasets.DatasetApiService/GetDataset
Content-Type: application/json

{
  "ownerSlug": "amar5693",
  "datasetSlug": "screen-time-sleep-and-stress-analysis-dataset"
}

**Response:**

{
  "id": 9481458,
  "title": "Screen Time, Sleep & Stress Analysis Dataset",
  "subtitle": "ML-ready dataset analyzing smartphone usage and productivity.",
  "totalBytes": 787136,
  "downloadCount": 11659,
  "usabilityRating": 1
}

#### List Dataset Files

POST /kaggle/v1/datasets.DatasetApiService/ListDatasetFiles
Content-Type: application/json

{
  "ownerSlug": "amar5693",
  "datasetSlug": "screen-time-sleep-and-stress-analysis-dataset"
}

**Response:**

{
  "datasetFiles": [
    {
      "name": "Smartphone_Usage_Productivity_Dataset_50000.csv",
      "creationDate": "2026-02-13T06:56:19.803Z",
      "totalBytes": 2958561
    }
  ]
}

#### Get Dataset Metadata

POST /kaggle/v1/datasets.DatasetApiService/GetDatasetMetadata
Content-Type: application/json

{
  "ownerSlug": "amar5693",
  "datasetSlug": "screen-time-sleep-and-stress-analysis-dataset"
}

**Response:**

{
  "info": {
    "datasetId": 9481458,
    "datasetSlug": "screen-time-sleep-and-stress-analysis-dataset",
    "ownerUser": "amar5693",
    "title": "Screen Time, Sleep & Stress Analysis Dataset",
    "description": "...",
    "totalViews": 44291,
    "totalVotes": 236,
    "totalDownloads": 11661
  }
}

#### Download Dataset

POST /kaggle/v1/datasets.DatasetApiService/DownloadDataset
Content-Type: application/json

{
  "ownerSlug": "amar5693",
  "datasetSlug": "screen-time-sleep-and-stress-analysis-dataset"
}

Returns binary data (ZIP file). Response headers:

---

Models

#### List Models

POST /kaggle/v1/models.ModelApiService/ListModels
Content-Type: application/json

{}

**Request Body Parameters:**

**Example:**

{
  "owner": "google"
}

**Response:**

{
  "models": [
    {
      "id": 1,
      "owner": "google",
      "slug": "gemma",
      "title": "Gemma",
      "subtitle": "Gemma is a family of lightweight, state-of-the-art models",
      "instanceCount": 16,
      "framework": "transformers"
    }
  ]
}

#### Get Model

POST /kaggle/v1/models.ModelApiService/GetModel
Content-Type: application/json

{
  "ownerSlug": "google",
  "modelSlug": "gemma"
}

**Response:**

{
  "id": 1,
  "title": "Gemma",
  "slug": "gemma",
  "owner": "google",
  "subtitle": "Gemma is a family of lightweight, state-of-the-art models",
  "publishTime": "2024-02-21T16:00:00Z",
  "instanceCount": 16
}

---

Competitions

#### List Competitions

POST /kaggle/v1/competitions.CompetitionApiService/ListCompetitions
Content-Type: application/json

{}

**Request Body Parameters:**

**Example:**

{
  "search": "nlp"
}

**Response:**

{
  "competitions": [
    {
      "id": 118448,
      "ref": "https://www.kaggle.com/competitions/ai-mathematical-olympiad-progress-prize-3",
      "title": "AI Mathematical Olympiad - Progress Prize 3",
      "url": "https://www.kaggle.com/competitions/ai-mathematical-olympiad-progress-prize-3",
      "deadline": "2026-06-06T23:59:00Z",
      "category": "Featured",
      "reward": "$1,048,576",
      "teamCount": 1234,
      "userHasEntered": false
    }
  ]
}

---

Kernels (Notebooks)

#### List Kernels

POST /kaggle/v1/kernels.KernelsApiService/ListKernels
Content-Type: application/json

{}

**Request Body Parameters:**

**Example:**

{
  "search": "titanic"
}

**Response:**

{
  "kernels": [
    {
      "id": 5660537,
      "ref": "alexisbcook/titanic-tutorial",
      "title": "Titanic Tutorial",
      "author": "alexisbcook",
      "language": "Python",
      "totalVotes": 1234,
      "totalViews": 56789
    }
  ]
}

#### Get Kernel

POST /kaggle/v1/kernels.KernelsApiService/GetKernel
Content-Type: application/json

{
  "userName": "alexisbcook",
  "kernelSlug": "titanic-tutorial"
}

**Response:**

{
  "metadata": {
    "id": 5660537,
    "ref": "alexisbcook/titanic-tutorial",
    "title": "Titanic Tutorial",
    "author": "alexisbcook",
    "language": "Python"
  }
}

---

Code Examples

JavaScript

const response = await fetch(
  'https://gateway.maton.ai/kaggle/v1/datasets.DatasetApiService/ListDatasets',
  {
    method: 'POST',
    headers: {
      'Authorization': `Bearer ${process.env.MATON_API_KEY}`,
      'Content-Type': 'application/json'
    },
    body: JSON.stringify({ search: 'covid' })
  }
);
const data = await response.json();
console.log(data);

Python

import os
import requests

response = requests.post(
    'https://gateway.maton.ai/kaggle/v1/datasets.DatasetApiService/ListDatasets',
    headers={
        'Authorization': f'Bearer {os.environ["MATON_API_KEY"]}',
        'Content-Type': 'application/json'
    },
    json={'search': 'covid'}
)
print(response.json())

---

Notes

Error Handling

| Status | Meaning |

|--------|---------|

| 200 | Success |

| 400 | Invalid request parameters |

| 401 | Invalid or missing authentication |

| 403 | Permission denied |

| 404 | Resource not found |

| 429 | Rate limited |

Resources