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Build ML preprocessing, training, deployment, and prediction workflows in Teradata.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "tdprepview-mcp" yet — see the docs or source repo.
Design a machine learning pipeline for customer churn data in a Teradata database, including missing value handling, categorical encoding, feature scaling, and training a binary classification model.
A Teradata-ready preprocessing and model training workflow description or configuration.
Deploy a trained Teradata machine learning model to production and provide the steps to run batch predictions on new customer data.
A model deployment plan and a method for running predictions on new data.
Analyze numeric and categorical features in a Teradata table, recommend suitable preprocessing strategies, and generate a reusable preprocessing workflow.
Preprocessing recommendations by feature type and a reusable workflow.
Connect to Teradata via MCP to query SQL and explore metadata.
Query and analyze the Titanic passenger database through MCP with AI agents.
Directly manage DEM MDM data through 12 MCP tools for AI agents.
Run end-to-end data science workflows through natural language commands.
Use natural language to manage TeamDesk data, search records, and generate documents.
Explore and compare Texas public school data for school choice and research.