dbt-cli-mcp
The DBT CLI MCP Server is a Model Context Protocol server that facilitates interaction with dbt projects through standardized MCP tools. It allows AI coding agents to execute dbt commands and supports major dbt operations with command-line interface access.
What is the purpose of the DBT CLI MCP Server?
The DBT CLI MCP Server allows AI coding agents to interact with dbt projects using standardized MCP tools, facilitating the execution of dbt commands and management of dbt environments.
What are the prerequisites for installing the DBT CLI MCP Server?
You need Python 3.10 or higher, the 'uv' tool for Python environment management, and the dbt CLI installed.
How do I specify the project directory when using MCP tools?
You must specify the full absolute path to your dbt project directory with the 'project_dir' parameter. Relative paths will not work correctly.
What should I do if I encounter a 'Could not find profile named' error?
Ensure that the profiles.yml file is present in the project directory and contains the profile referenced in dbt_project.yml. Also, verify that you are using an absolute path for 'project_dir'.
How can I run integration tests for the DBT CLI MCP Server?
You can run all integration tests using 'python integration_tests/run_all.py' or a specific test with 'python integration_tests/test_dbt_run.py'.