dbt
Summary
dbt Labs' official MCP server — explore project metadata, run dbt commands, and query the Semantic Layer.
Features
- Explore models, sources, and lineage in a dbt project
- Run dbt commands and read the results
- Query the Semantic Layer for governed metrics
Installation
Set up this MCP server in your favorite AI agent — copy a ready-made configuration below.
Description
dbt Labs' official MCP server connects an assistant to a dbt project and, if you use dbt Cloud, to its metadata and Semantic Layer.
Three areas of capability
- Project discovery. List models, sources, and tests; read model definitions; and trace lineage upstream and downstream. This is the fastest way to answer "what feeds this table and what breaks if I change it".
- Command execution. Run
dbt build,run,test, andcompileand read the output, so an assistant can iterate on a model until its tests pass. - Semantic Layer queries. Ask for a metric by name and get governed, consistent numbers rather than a hand-written SQL approximation that quietly disagrees with the dashboard.
Why the Semantic Layer part matters
The recurring problem with AI querying a warehouse is that it invents its own definition of a metric. Routing through the Semantic Layer means "revenue" means what your organisation has agreed it means.
Installed with uvx dbt-mcp, configured with your project directory and, optionally, dbt Cloud credentials.
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