Dbt Semantic Layer MCP Server

🚀 dbt Semantic Layer MCP Server

A Model-Connector-Presenter (MCP) server for seamlessly querying the dbt semantic layer via Claude Desktop and other compatible AI assistants.

🚀 Quick Start

This MCP server serves as a bridge between AI assistants (such as Claude) and the dbt semantic layer, enabling you to interact with the dbt semantic layer directly from Claude Desktop after installation and configuration:

1. Inquire about available metrics: "What metrics are available in my dbt semantic layer?"
2. Query specific metrics: "Show the monthly revenue by product category for the last quarter."
3. Analyze trends: "What is the week-on-week growth of user registrations?"

✨ Features

• 🔍 Metric Discovery: Browse and search for available metrics in the dbt semantic layer.
• 📊 Query Creation: Generate and execute semantic queries through natural language.
• 🧮 Data Calculation: Filter, group, and sort data for deeper insights.
• 📈 Result Visualization: Display query results in an easy-to-understand format.

📦 Installation

Via Smithery (Recommended)

The easiest way to install is via Smithery:

npx -y @smithery/cli install @TommyBez/dbt-semantic-layer-mcp --client claude

📚 Documentation

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 metric facts.
• Consistent metric definitions across data tools.
• Simplified complex metrics for all team members to use.

About the Project

This MCP server acts as a bridge between AI assistants (such as Claude) and the dbt semantic layer, enabling you to:

• Query metrics directly through natural language conversations.
• Browse and search for available metrics and their definitions.
• Conduct data analysis using dimensional breakdowns and filters.
• Visualize results in your AI assistant interface.

💡 Troubleshooting

If you encounter issues:

• Verify that your API credentials are correct.
• Ensure that the semantic layer is enabled in your dbt Cloud project.
• Check that metrics are correctly defined in your dbt project.

🤝 Contribution

Contributions are welcome! Feel free to submit a Pull Request.

📄 License

This project is released under the MIT License - see the LICENSE file for details.

🙏 Acknowledgments

• dbt Labs for creating the dbt semantic layer.
• Smithery for providing the MCP deployment platform.
• LiteMCP for providing the MCP development package.