# Kaggle AI integration on Definable

> Kaggle is a platform for data science and machine learning competitions, offering datasets, notebooks, and a collaborative community.

## What this connects

Kaggle is a platform for data science and machine learning competitions, offering datasets, notebooks, and a collaborative community.

Vendor: https://www.kaggle.com

## Tools available

**35** tools available. First 12:

- `KAGGLE_COMPETITION_DOWNLOAD_FILES` — Download competition data files — Downloads all data files for a Kaggle competition as a single zip archive. Returns the local file path where the zip was saved. Note: You must have accepted the competition's rules on Kaggle's website before downloading (403 error if not accepted).
- `KAGGLE_COMPETITION_SUBMIT` — Submit Competition Entry — Submit an entry to a Kaggle competition using a previously uploaded file. Prerequisites: 1. You must have accepted the competition rules on Kaggle's website 2. You must have uploaded your submission file and obtained a blob_file_tokens (use Kaggle's file upload API endpoint first) This action performs the final submission step after file upload. The blob token identifies your uploaded file and associates it with your competition submission.
- `KAGGLE_CONFIG_DIR` — Get Kaggle Config Directory — Tool to retrieve the directory of the Kaggle API configuration file. Use when you need to locate the directory containing your kaggle.json credentials.
- `KAGGLE_CONFIG_INIT` — Initialize Kaggle Configuration — Initialize Kaggle API client configuration. This action sets up the necessary configuration file for Kaggle API access by first attempting to use the Kaggle CLI's 'kaggle config init' command. If the CLI is unavailable, it falls back to creating a kaggle.json file at ~/.kaggle/kaggle.json (or $KAGGLE_CONFIG_DIR/kaggle.json if that environment variable is set). The action is idempotent - if configuration already exists, it will not overwrite it. No parameters are required; the action uses environment variables and metadata when available. Run this before other Kaggle actions when credentials are missing or when KAGGLE_CONFIG_VIEW returns empty/error output.
- `KAGGLE_CONFIG_KEYS` — List Kaggle Configuration Keys — Tool to list local Kaggle API configuration keys. Use when you need to see which configuration options are set without revealing values.
- `KAGGLE_CONFIG_PATH` — Get Kaggle Config Path — Tool to retrieve local Kaggle API configuration file path. Use when you need to know the location of the Kaggle config before operations.
- `KAGGLE_CONFIG_RESET` — Reset Kaggle Configuration — Tool to reset local Kaggle CLI configuration to defaults. Clears CLI-managed keys ('competition', 'path', 'proxy').
- `KAGGLE_CONFIG_SET` — Set Kaggle Configuration — Tool to set a Kaggle CLI configuration parameter. Use when updating local CLI settings such as default download path or proxy. Ensure Kaggle CLI is installed.
- `KAGGLE_CONFIG_UNSET` — Unset Kaggle Configuration — Tool to unset a Kaggle CLI configuration parameter. Use when removing local CLI settings such as default download path or proxy. Ensure Kaggle CLI is installed.
- `KAGGLE_CONFIG_VIEW` — View Kaggle Configuration — View local Kaggle API credentials and configuration settings. This action reads Kaggle configuration from local sources (does NOT make API calls to Kaggle). Configuration is retrieved in the following precedence order: 1. kaggle.json file (from KAGGLE_CONFIG_DIR env var, ~/.config/kaggle/, or ~/.kaggle/) 2. 'kaggle config view' CLI output (for proxy/path settings) 3. Environment variables (KAGGLE_USERNAME, KAGGLE_KEY) 4. Authorization header from metadata Use this action to: - Verify Kaggle credentials are configured before making API calls - Check current proxy settings - Debug authentication issues Returns empty strings for username/key if no credentials are found; use KAGGLE_CONFIG_INIT to set up credentials first. Note: username and key are independent — an empty username field does not indicate missing or invalid credentials. WARNING: This action returns sensitive API key data in plain text.
- `KAGGLE_DATASET_CREATE` — Dataset Create — Create a new Kaggle dataset with metadata. IMPORTANT: Dataset creation requires at least one data file. Ensure files are uploaded before calling this action. The 'id' field must use your authenticated Kaggle username as the owner. Returns the creation status and any message from the Kaggle API.
- `KAGGLE_DATASET_INIT` — Kaggle Dataset Init — Tool to initialize a dataset-metadata.json file in a local folder. Use when preparing a dataset folder before uploading to Kaggle.

## Auth

Auth schemes: `API_KEY`.

## How agents use Kaggle

Inside a Definable workflow, Kaggle is one of the tools the **Distributor specialist** can call. Example coordination patterns:

- **Researcher → Kaggle** — the Researcher (GPT-5.5) pulls context from Kaggle (records, threads, documents), synthesises findings, and briefs the rest of the team.
- **Writer → Distributor → Kaggle** — the Writer (Claude Opus 4.7) drafts copy in brand voice, the Verifier passes it, then the Distributor writes the result into Kaggle (create record, post message, draft email).
- **Designer / Engineer → Distributor → Kaggle** — the Designer ships an asset or the Engineer ships a code change, the Distributor delivers it via Kaggle (attach file, open PR comment, post status).

The Verifier checks every Kaggle call. On rate limit, schema drift, or auth refresh it self-heals and retries — the workflow completes without manual intervention.

## Categories

- artificial intelligence — https://definable.ai/apps/category/artificial-intelligence/
- developer tools — https://definable.ai/apps/category/developer-tools/

## Related

- HTML page: https://definable.ai/apps/kaggle/
- Same category (artificial intelligence): https://definable.ai/apps/category/artificial-intelligence/
- All integrations: https://definable.ai/apps/
- Workflow (multi-agent loop): https://definable.ai/workflow/
- Apps llms.txt index: https://definable.ai/llms-apps.txt