Dbt Cli MCP Server

Dbt Cli MCP connects Dbt Cli MCP to AI assistants that speak the Model Context Protocol. A Model Context Protocol (MCP) server that wraps the dbt CLI tool, enabling AI coding agents to interact with dbt projects through standardized MCP tools.

What Dbt Cli MCP does

A Model Context Protocol (MCP) server that wraps the dbt CLI tool, enabling AI coding agents to interact with dbt projects through standardized MCP tools.

Key capabilities

• Execute dbt commands through MCP tools
• Support for all major dbt operations (run, test, compile, etc.)
• Command-line interface for direct interaction
• Environment variable management for dbt projects
• Configurable dbt executable path
• Flexible profiles.yml location configuration

Requirements

• Python 3.10 or higher - uv tool for Python environment management - dbt CLI installed

Practical notes

• Maintained by MammothGrowth, written in Python.

Recorded tools

• dbt_run — Run dbt models (requires absolute project_dir)
• dbt_test — Run dbt tests (requires absolute project_dir)
• dbt_ls — List dbt resources (requires absolute project_dir)
• dbt_compile — Compile dbt models (requires absolute project_dir)
• dbt_debug — Debug dbt project setup (requires absolute project_dir)
• dbt_deps — Install dbt package dependencies (requires absolute project_dir)
• dbt_seed — Load CSV files as seed data (requires absolute project_dir)
• dbt_show — Preview model results (requires absolute project_dir)

More MCP options

Compare MCP servers by category, or browse hosted MCP servers if you prefer an endpoint over a local process.

Maintainer setup documentation.