DataHub's MCP server gives AI agents the enterprise context they need to work with your data. Surface curated knowledge — runbooks, FAQs, business definitions, and vocabularies — so agents operate with the same shared understanding as your teams. Search across datasets, dashboards, and pipelines, then pull ownership, governance policies, quality signals, and documentation to understand what you're looking at. Trace lineage at the table and column level. Surface real SQL queries to see how data is actually used. Apply tags, glossary terms, owners, and descriptions at scale. The context layer that makes AI agents enterprise-ready.
How to use
- 1Add it in ChatGPT
Open DataHub Cloud in ChatGPT's Plugin directory (button above), select + to add it and sign in if asked.
- 2Use it in a chat
Type @ in the composer and pick DataHub Cloud, or start your message with its name. ChatGPT may also suggest it when it fits what you ask.
Skills 5
- datahub-lineage
Use this skill when the user wants to explore lineage, trace data dependencies, perform impact analysis, find root causes, map data pipelines, or understand how data flows between systems. Triggers on: "what feeds into X", "what depends on X", "show lineage for X", "impact analysis", "trace the pipeline", "root cause", "upstream of X", "downstream of X", or any request involving data lineage and dependency tracking.
- datahub-quality
Use this skill when the user wants to manage data quality in DataHub: create or run assertions, check assertion outcomes, raise or resolve incidents, create notification subscriptions, or diagnose health problems across their estate. Triggers on: "create assertion", "run assertion", "check quality", "data quality", "health check", "raise incident", "resolve incident", "subscribe to", "failing assertions", "active incidents", or any request involving data quality, assertions, incidents, or quality notifications.
- datahub-search
Search and explore the DataHub Cloud data catalog — find datasets, dashboards, pipelines, columns, owners, tags, domains, and any metadata. Use when the user wants to find, discover, or look up anything in their data catalog.
- datahub-setup
Verify and troubleshoot the DataHub Cloud connection — confirm the MCP server is reachable, authentication is working, and Claude can access the catalog. Use when the user wants to set up DataHub, test the connection, or fix connectivity issues.
- datahub-sql-workflow
Ground text-to-SQL work in DataHub catalog evidence. Use when a user asks to write, draft, debug, or execute SQL; answer a data question that requires SQL; calculate a metric; query named tables; or investigate SQL results with DataHub MCP tools available. Always begin with find_sql_context, even when the user already supplied tables or dataset URNs.
Things to ask
- “Find the tables that answer this question in DataHub.”
- “Trace what breaks downstream if I change this column.”
- “Write SQL for this, grounded in DataHub catalog context.”