OrionBelt Analytics is a Python-based MCP server that analyzes relational database schemas and generates comprehensive ontologies in RDF/Turtle format with direct SQL mappings.
From the registry: Ontology-based MCP server for database schema analysis and RDF/OWL ontology generation

$ git clone https://github.com/ralfbecher/orionbelt-analytics && cd orionbelt-analytics && uv synchttps://github.com/ralfbecher/orionbelt-analyticsPlease install the `orionbelt-analytics` MCP server into my current AI client (that's you).
Required prerequisites (do these first if not already done):
- **Python 3.13+** — Required runtime (https://www.python.org/)
- **uv** — Python package manager Run: `pip install uv` (https://github.com/astral-sh/uv)
- **Clone and install** — Clone repo and run uv sync Run: `git clone https://github.com/ralfbecher/orionbelt-analytics && cd orionbelt-analytics && uv sync` (https://github.com/ralfbecher/orionbelt-analytics)
- **Database credentials** — Credentials for the database to analyze (PostgreSQL, MySQL, Snowflake, ClickHouse, Dremio, BigQuery, DuckDB, or Databricks)
Canonical MCP server config (stdio transport):
- command: `uv`
- args: ["run","python","-m","orionbelt_analytics"]
Note: Ontology-based MCP server for Text-2-SQL with GraphRAG. Requires cloning and uv sync. Database connection configured separately. Python 3.13+ required. BSL 1.1 license.
Add this MCP server to my current client's config in the correct format for you. If you need secrets or credentials I haven't provided, ASK me — do not invent values or leave raw placeholders. After adding it, tell me how to verify the server is connected.R2RML_BASE_IRIConfigurable base IRI for R2RML mapping generation.