by ralfbecher · MCP Server · ★ 27
Ontology-based MCP server that analyzes database schemas (PostgreSQL, Snowflake, ClickHouse, Dremio) and generates RDF/OWL ontologies with SQL mappings for fan-trap-free Text-to-SQL.
| Stars | 27 |
| Forks | 4 |
| Language | Python |
| Category | MCP Server |
| Quality Score | 35.75/100 |
| Last Updated | 2026-05-03 |
| Created | 2026-02-11 |
| Platforms | claude-code, cli, mcp, python |
| Est. Tokens | ~133k |
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orionbelt-analytics is Ontology-based MCP server that analyzes database schemas (PostgreSQL, Snowflake, ClickHouse, Dremio) and generates RDF/OWL ontologies with SQL mappings for fan-trap-free Text-to-SQL.. It is categorized as a MCP Server with 27 GitHub stars.
orionbelt-analytics is primarily written in Python. It covers topics such as agentic, agentic-ai, ai-analytics.
You can find installation instructions and usage details in the orionbelt-analytics GitHub repository at github.com/ralfbecher/orionbelt-analytics. The project has 27 stars and 4 forks, indicating an active community.