ralfbecher/orionbelt-semantic-layer — API-first semantic engine and query planner for AI agents that compiles declarative YAML models into…

Description and use

rAlfbecher’s **orionbelt-semantic-layer** is an API‑first semantic engine and query planner designed for AI agents. It transforms declarative YAML models into optimized, dialect‑specific SQL, supporting a wide range of backends—including BigQuery, PostgreSQL, Snowflake, ClickHouse, Dremio, Databricks, DuckDB, and MySQL—so developers can query heterogeneous data stores with a single, unified semantic layer.

Problem

ralfbecher/orionbelt-semantic-layer helps connect AI assistants to real tools and data through a standard protocol.

Outcome

Medium: useful for prototypes or internal workflows, with dependency and maintenance checks before production.

Workflow

• connect AI agents to tools
• ship Model Context Protocol servers
• standardize integrations

Evidence

API-first semantic engine and query planner for AI agents that compiles declarative YAML models into optimized, dialect-specific SQL across BigQuery, PostgreSQL, Snowflake, ClickHouse, Dremio, Databricks, DuckDB, and MySQL.

Source