dbt Semantic Layer MCP Server
A Model-Connector-Presenter (MCP) server for seamlessly querying the dbt Semantic Layer through Claude Desktop and other compatible AI assistants.
What is the dbt Semantic Layer?
The dbt Semantic Layer is a powerful feature that allows you to define metrics once in your dbt project and reuse them consistently across your entire data stack. It provides:
- A single source of truth for business metrics
- Consistent metric definitions across all data tools
- Simplified access to complex metrics for all team members
About This Project
This MCP server acts as a bridge between AI assistants (like Claude) and the dbt Semantic Layer, enabling you to:
- Query metrics directly through natural language conversations
- Explore available metrics and their definitions
- Analyze data with dimensional breakdowns and filters
- Visualize results within your AI assistant interface
Features
- 🔍 Metric Discovery: Browse and search available metrics in your dbt Semantic Layer
- 📊 Query Creation: Generate and execute semantic queries through natural language
- 🧮 Data Analysis: Filter, group, and order metrics for deeper insights
- 📈 Result Visualization: Display query results in an easy-to-understand format
Prerequisites
- A dbt Cloud account with Semantic Layer enabled
- API access to your dbt Cloud instance
- Node.js (v14 or later)
Installation
Via Smithery (Recommended)
The easiest way to install is via Smithery:
npx -y @smithery/cli install @TommyBez/dbt-semantic-layer-mcp --client claude
Usage
Once installed and configured, you can interact with the dbt Semantic Layer directly from Claude Desktop:
- Ask about available metrics: "What metrics are available in my dbt Semantic Layer?"
- Query specific metrics: "Show me monthly revenue for the last quarter grouped by product category"
- Analyze trends: "What's the week-over-week growth in user signups?"
Troubleshooting
If you encounter issues:
- Verify your API credentials are correct
- Ensure your dbt Cloud project has Semantic Layer enabled
- Check that your metrics are properly defined in your dbt project
Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
License
This project is licensed under the MIT License - see the LICENSE file for details.
