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Connect to dbt via MCP to inspect projects and run data workflows.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "dbt-mcp" yet — see the docs or source repo.
Using the dbt MCP tool, list the models, sources, and tests in the current project and organize them by directory structure.
A structured inventory of key dbt resources, grouped by project layout for quick understanding.
Use the dbt MCP tool to run the model marts.finance.revenue_summary, then report the execution result, duration, and any failures.
A summary of run status, execution time, and any error details to confirm success or failure.
Using the dbt MCP tool, identify failed tests from the most recent run, explain the affected models and likely causes, and suggest possible fixes.
A list of failed tests, related models, cause analysis, and actionable remediation suggestions.
Interact with the dbt ecosystem for modeling, semantic queries, and metadata discovery.
Connect to dbt projects via MCP for analysis, model understanding, and insights.
Securely connect to and operate MySQL databases through the MCP protocol.
Connect to Microsoft SQL Server for queries, analysis, and visualization generation.
Connect to PostgreSQL and MySQL, run SQL, and manage database transactions.
Connect LLM apps to query and manage multiple databases through one tool.