- Category
- Engineering & IT
- Developer
- dbt Labs, Inc.
- Website
- (opens in a new window)
How it works
dbt MCP Server helps users inspect dbt projects, query dbt Semantic Layer metrics, review lineage and model metadata, run dbt commands, manage dbt Platform jobs, generate dbt boilerplate, and search official dbt documentation through ChatGPT.
What else can you do?
Explain metric changes
DBT Query our Semantic Layer revenue metric for the last two quarters by customer segment. Identify the largest contributors to the change and explain the definition, filters, and time grain used.
Assess model change impact
DBT Inspect the lineage and metadata for our orders model. Identify downstream models and metrics affected by changing its customer key, and propose a focused validation checklist before implementation.
Diagnose a failed job
DBT Review the latest failed production job, its run results, and affected model metadata. Identify the likely failure point, distinguish evidence from hypotheses, and recommend the next debugging steps.
What’s included
Skills
- adding-dbt-unit-test
- answering-natural-language-questions-with-dbt
- building-dbt-semantic-layer
- configuring-dbt-mcp-server
- creating-mermaid-dbt-dag
- fetching-dbt-docs
- migrating-dbt-core-to-fusion
- migrating-dbt-project-across-platforms
- 6 more
Resources
Add plugins in a few clicks
Availability depends on the plugin, your plan, and workspace settings. Some connections require admin setup or approval. Contact your workspace admin if access is blocked.
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