Keboola MCP Server
Build production-grade data pipelines with just a prompt
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Keboola MCP Server lets an AI assistant such as Claude, Cursor, or ChatGPT build real data pipelines through the Model Context Protocol. Describing a workflow in words produces production infrastructure on Keboola's platform, with error handling, logging, and governance built in rather than left as an exercise.
It effectively gives an agent the capabilities of a data engineer: connecting sources, transforming data, scheduling jobs, and managing the pipeline lifecycle.
It is aimed at data teams and technical users who want to move from a described requirement to a running, governed pipeline quickly, using an AI assistant they already work in rather than building each pipeline by hand.
AI-assisted draft, human-reviewed before publishing — see how we choose & review tools.
Why we picked it
Keboola MCP Server made the cut for producing production infrastructure, not a prototype — error handling, logging, and governance built in from the description itself is worth naming against agent-built pipelines that work in a demo and fall over the first time something goes wrong in production.
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