dbt MCP Server

This MCP (Model Context Protocol) server provides various tools to interact with dbt. You can use this MCP server to provide AI agents with context of your project in dbt Core, dbt Fusion, and dbt Platform.

Read our documentation here to learn more. This blog post provides more details for what is possible with the dbt MCP server.

Feedback

If you have comments or questions, create a GitHub Issue or join us in the community Slack in the #tools-dbt-mcp channel.

Architecture

The dbt MCP server architecture allows for your agent to connect to a variety of tools.

Tools

SQL

• execute_sql
• text_to_sql

Semantic Layer

• get_dimensions
• get_entities
• get_metrics_compiled_sql
• list_metrics
• list_saved_queries
• query_metrics

Discovery

• get_all_models
• get_all_sources
• get_exposure_details
• get_exposures
• get_lineage
• get_macro_details
• get_mart_models
• get_model_children
• get_model_details
• get_model_health
• get_model_parents
• get_related_models
• get_seed_details
• get_semantic_model_details
• get_snapshot_details
• get_source_details
• get_test_details
• search

dbt CLI

• build
• compile
• docs
• get_model_lineage_dev
• list
• parse
• run
• show
• test

Admin API

• cancel_job_run
• get_job_details
• get_job_run_artifact
• get_job_run_details
• get_job_run_error
• list_job_run_artifacts
• list_jobs
• list_jobs_runs
• retry_job_run
• trigger_job_run

dbt Codegen

• generate_model_yaml
• generate_source
• generate_staging_model

dbt LSP

• fusion.compile_sql
• fusion.get_column_lineage
• get_column_lineage

Examples

Commonly, you will connect the dbt MCP server to an agent product like Claude or Cursor. However, if you are interested in creating your own agent, check out the examples directory for how to get started.

Contributing

Read CONTRIBUTING.md for instructions on how to get involved!