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Access Kaggle competitions, datasets, notebooks, and models through one MCP tool.
Copy the install command and let the AI configure it · recommended for beginners
Please install the "io.github.Seif-Sameh/Kaggle-mcp" MCP server from askskill: Run: claude mcp add 'io-github-seif-sameh-kaggle-mcp' -- npx -y mcp-server-kaggle
Use Kaggle to search for datasets related to customer churn prediction. Prioritize results updated within the last two years, with high download counts and clear column descriptions, then briefly compare the top 5 datasets and their best use cases.
A ranked dataset list with key metrics, links, and recommendations on which one to use.
List Kaggle competitions related to time series forecasting, including the theme, current status, evaluation metric, and a priority order for beginner practice.
A competition shortlist with comparison notes to help the user choose practice or reference projects.
For an image classification task, find high-quality Kaggle notebooks and reusable models, then summarize the methods, frameworks used, and the pros and cons of each.
A curated list of notebooks and models with summarized implementation ideas worth reusing.
Manage Kaggle competitions, datasets, notebooks, and models with natural language.
Automate Kaggle competitions, datasets, and submissions through Rube MCP.
Centralize knowledge, run semantic search, ingest documents, and generate RAG answers.
Let AI read, edit, and execute Jupyter notebooks directly.
Search Japanese KAKEN grants, projects, and researchers through Claude.
Connect to Jupyter via MCP to run code and explore data interactively.