by ralfbecher · MCP Server · ★ 46
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.
| Stars | 46 |
| Forks | 5 |
| Language | Python |
| Category | MCP Server |
| Quality Score | 35.3/100 |
| Last Updated | 2026-05-22 |
| Created | 2026-02-10 |
| Platforms | cli, mcp, python |
| Est. Tokens | ~1458k |
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orionbelt-semantic-layer is 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, Databri. It is categorized as a MCP Server with 46 GitHub stars.
orionbelt-semantic-layer is primarily written in Python. It covers topics such as agentic-ai, ai-analytics, ai-workflow.
You can find installation instructions and usage details in the orionbelt-semantic-layer GitHub repository at github.com/ralfbecher/orionbelt-semantic-layer. The project has 46 stars and 5 forks, indicating an active community.