Tommybez Dbt Semantic Layer MCP Server

🚀 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.

🚀 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. For example:

• Ask about available metrics: "What metrics are available in my dbt semantic layer?"
• Query specific metrics: "Show the monthly revenue by product category for the last quarter."
• Analyze trends: "What is the week-over-week growth rate 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 Analysis: Filter, group, and sort metrics for deeper insights.
• 📈 Result Visualization: Display query results in an easy-to-understand format.

📦 Installation

Via Smithery (Recommended)

The easiest way is to install 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 business metrics.
• Consistent metric definitions across data tools.
• Simplification of complex metrics for all team members to use.

About This 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 through filtering, grouping, and sorting.
• Visualize results in your AI assistant interface.

Prerequisites

• A dbt Cloud account with the semantic layer enabled.
• API access to your dbt Cloud instance.
• Node.js (v14 or higher).

Troubleshooting

When encountering issues:

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

🤝 Contribution

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.

🙏 Acknowledgments

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