ralfbecher/orionbelt-semantic-layer
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.
Use in a workflow
ralfbecher/orionbelt-semantic-layer helps connect AI assistants to real tools and data through a standard protocol.
- connect AI agents to tools
- ship Model Context Protocol servers
- standardize integrations
Limitations and review notes
Medium: useful for prototypes or internal workflows, with dependency and maintenance checks before production.
- Source: github
- Language: Python
- Record date: 2026-09-05T17:31:58.069Z