What problem does it solve?
Enables reliable connection between AI clients and dbt by generating proper MCP server configuration, resolving authentication methods, and validating server accessibility to prevent misconfiguration and broken integrations.
Core Features & Use Cases
- Configuration Generation: Provides JSON templates for local uvx-based servers and remote HTTP endpoints tailored to different clients (Claude Desktop, Claude Code, Cursor, VS Code).
- Authentication Guidance: Details when to use personal access tokens, service tokens, or OAuth, and how to securely reference credentials via environment variables.
- Verification & Troubleshooting: Includes verification steps and common fixes for path, uvx, and token errors to confirm connectivity and client integration.
- Use Case: Set up a local dbt development environment that exposes the dbt CLI and Semantic Layer to an AI tool, or configure a remote production connection to dbt Cloud for metric discovery and job administration.
Quick Start
Configure a local or remote dbt MCP server using the provided JSON templates, set required environment variables such as DBT_PROJECT_DIR and DBT_TOKEN, and run the verification steps to confirm the client can list models and metrics.