Use Kaggle with your AI.
Connect your account once and let the AI you already use work with it, without building another integration. Transform Kaggle into your primary data science engine. Deploy autonomous agents to intercept trending datasets, track competition discussions, and engage data
Developed, maintained, and hosted by Vinkius.
MCP VERIFIED · PRODUCTION READY · VINKIUS GUARANTEED
Waiting for input…
Works with modern AI clients that support MCP, including ChatGPT, Claude, Cursor, and more.
Complete set · 10 capabilities
The complete Kaggle capability set.
These are the exact actions your AI can choose when you ask it to work with Kaggle.
01-04
4 capabilities in this set.
Part of 10 available through Kaggle.
- 01
Create dataset
Use this to share synthesized or processed data back with the community. Create a new Kaggle dataset
- 02
Push notebook
Use this to actively engage the community by sharing code or analysis. Push a notebook/script to Kaggle
- 03
Search competitions
Use this to find communities of highly engaged data scientists. Search Kaggle competitions
- 04
Get competition leaderboard
Useful for competitor analysis and seeing what the winning score is. Get a competition leaderboard
05-07
3 capabilities in this set.
Part of 10 available through Kaggle.
- 05
Get notebook status
Use this to poll until a notebook finishes running. Get the execution status of a Kaggle notebook
- 06
List dataset files
Required to understand the data schema before analysis. List files within a Kaggle dataset
- 07
Search datasets
Use this to find interesting datasets or communities. Search Kaggle datasets
08-10
3 capabilities in this set.
Part of 10 available through Kaggle.
- 08
Search models
Use this to find architectures being deployed and their creators. Search Kaggle models
- 09
Search notebooks
Useful for finding code examples, data exploration, or winning competition strategies. Search Kaggle notebooks/kernels
- 10
Pull notebook
Extremely useful to read other developers code and learn their strategy. Pull code from a Kaggle notebook/kernel
Observed, not estimated
739ms average. Fast in production.
Kaggle is checked daily against the live service.
- Fastest day
- 591ms
- Slowest day
- 910ms
- 14-day trend
- Slowing+31%
Connect your client
One URL. Every client.
Activate the Connector, copy your link, and paste it into the client you already use. 10 capabilities arrive ready to run.
Preview access · not provider authentication
The vk_preview_* token belongs to Vinkius preview infrastructure. It lets Claude discover and display the capabilities of Kaggle, so you can see the experience inside your AI.
It does not authenticate your account with Kaggle. Actions requiring credentials or live account data may not run until you activate the Connector and authorize the service.
Kaggle Connector
You're all set. Choose your MCP client and follow the setup instructions.
https://edge.vinkius.com/vk_preview_D9qB4MVerPWx9BW5Z9tgoSaKlq533NU0W3PDjMbm/mcpClaude Desktop
Follow the steps below to connect in seconds.
- 1In Claude Desktop, open Settings → Connectors.
- 2Click “Add custom connector” and paste the connector link above as the remote MCP server URL.
- 3Click Add and start a new chat — Kaggle capabilities are ready to use.
{
"mcpServers": {
"kaggle-market-intelligence-mcp": {
"url": "https://edge.vinkius.com/vk_preview_D9qB4MVerPWx9BW5Z9tgoSaKlq533NU0W3PDjMbm/mcp"
}
}
}
Claude
ChatGPT
Cursor
VS Code
Windsurf
Claude Code
JetBrains
Cline
Step-by-step instructions for each client are in the guide. How to connect
FAQ
Questions Kaggle owners ask.
- 01
How do I find my Kaggle API Token?
Go to your Kaggle account settings. Scroll down to the API section and click 'Create New API Token'. This will download a kaggle.json file containing your username and key.
- 02
Can the agent post replies automatically?
Yes. Using the engagement capabilities, your agent can write and post Markdown replies directly into community discussions.
- 03
How does the dataset scanning work?
The capability iterates through recent discussions in specific datasets or competitions, filtering for exact keywords like 'alternative', 'error', or 'help'. It's highly efficient for finding interception points.
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