dbt▌
by dbt-labs
dbt bridges data build tool resources and natural language, enabling top BI software features, metadata discovery, and d
Provides a bridge between dbt (data build tool) resources and natural language interfaces, enabling execution of CLI commands, discovery of model metadata, and querying of the Semantic Layer for data transformation management.
best for
- / Data analysts querying metrics in plain English
- / Analytics engineers exploring dbt project metadata
- / Business users accessing data through natural language
- / AI agents working with structured data transformations
capabilities
- / Execute SQL queries on dbt Platform infrastructure
- / Generate SQL from natural language descriptions
- / Query metrics with filtering and grouping
- / Discover model metadata and macros
- / List available metrics and saved queries
- / Get compiled SQL for metrics without execution
what it does
Connects AI agents to dbt projects, allowing natural language queries to be converted to SQL and executed against your data warehouse using dbt's Semantic Layer and metadata.
about
dbt is an official MCP server published by dbt-labs that provides AI assistants with tools and capabilities via the Model Context Protocol. dbt bridges data build tool resources and natural language, enabling top BI software features, metadata discovery, and d It is categorized under analytics data, developer tools.
how to install
You can install dbt in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
license
Apache-2.0
dbt is released under the Apache-2.0 license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
readme
dbt bridges data build tool resources and natural language, enabling top BI software features, metadata discovery, and d
TL;DR: Connects AI agents to dbt projects, allowing natural language queries to be converted to SQL and executed against your data warehouse using dbt's Semantic Layer and metadata.
What it does
- Execute SQL queries on dbt Platform infrastructure
- Generate SQL from natural language descriptions
- Query metrics with filtering and grouping
- Discover model metadata and macros
- List available metrics and saved queries
- Get compiled SQL for metrics without execution
Best for
- Data analysts querying metrics in plain English
- Analytics engineers exploring dbt project metadata
- Business users accessing data through natural language
- AI agents working with structured data transformations
Highlights
- Semantic Layer integration
- Natural language to SQL conversion
- Works with dbt Core, Fusion, and Platform