#semantic-layer

Give AI agents structured database intelligence. Deterministic SQL, NULL trap detection, EXPLAIN pre-flight. MIT licensed.

OrionBelt Semantic Layer is an API-first engine that transforms declarative YAML model definitions into optimized SQL for Postgres, Snowflake, ClickHouse, Dremio, and Databricks. It provides a unified abstraction over your data warehouse, so analysts and applications can query using business concepts (dimensions, measures, metrics) instead of raw SQL. Every capability — model loading, validation, query compilation, and diagram generation — is exposed through a REST API and an MCP server, making OrionBelt easy to integrate into any application, workflow, or AI assistant.

Ultra-fast to deploy agentic-first mcp-ready semantic layer. Let your data be like water. Bonnard is a CLI for building and deploying semantic layers. Define metrics and dimensions in YAML, deploy a governed MCP server, and serve AI agents and BI tools. Supports Snowflake, BigQuery, Databricks, PostgreSQL, and more. Ships with native integrations for Claude Code, Cursor, and Codex. GitHub: https://github.com/meal-inc/bonnard-cli Docs: https://docs.bonnard.dev/docs/ npm: https://www.npmjs.com/package/@bonnard/cli

An open-source Text2SQL tool that transforms natural language into SQL using graph-powered schema understanding. Ask your database questions in plain English, QueryWeaver handles the weaving.

🤖 The Semantic Engine for Model Context Protocol(MCP) Clients and AI Agents 🔥

Mirror of

MCP Server for querying DBT Semantic Layer

MCP Server for Interacting with Cube Semantic Layers