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Orionbelt Analytics

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by ralforion

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.

Install

$claude mcp add orionbelt-analytics http://localhost:9000/mcp

Set up this server

This server needs project-specific setup. Follow the project instructions; no reusable public launch command is available yet.

Project instructions
agentic-aichromadbclaude-desktopclickhousedatabricksdremiographragknowledge-graphmcpmcp-servermodel-context-protocolontologyowlpostgresqlr2rmlrdfsemantic-layersnowflakesparqltext-to-sql

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27 of 27 tools

Documented tools (27)

From project documentation. A server handshake does not verify each tool’s description or behavior.

add_rdf_knowledge

Add custom metadata triples to the RDF store

apply_semantic_names

Apply LLM-suggested semantic names and descriptions to ontology

cleanup_workspace

Delete all workspace files for the current connection and start fresh

connect_database

Connect to any supported database using .env credentials

discover_schema

Analyze schema structure with automatic GraphRAG + ontology generation

download_artifact

Download ontology or R2RML mapping as a Turtle file

execute_sql_query

Execute SQL with OBQC validation, security checks, and fan-trap detection

generate_chart

Generate Plotly charts (bar, line, scatter, heatmap) with MCP-UI rendering

generate_ontology

Generate RDF/OWL ontology from schema with SQL mapping annotations

get_semantic_model

Retrieve a stored semantic model by name

get_table_details

Get detailed column, key, and constraint info for a specific table

GraphRAG

graphrag_find_join_path

Discover join paths between tables via graph traversal

graphrag_query_context

Get optimized context for SQL generation (85-95% token reduction)

graphrag_search

Semantic search + schema overview (auto-initialized by discoverschema)

list_schemas

List available schemas in the connected database

list_semantic_models

List all stored semantic models for the current connection

load_my_ontology

Load a custom .ttl ontology file from an import folder

measurable_from

Measure-capable tables for an anchor grain (one-to-many closure)

plan_composite_query

Advise a fan-trap-safe Composite Fact Layer (UNION ALL) decomposition

query_sparql

Execute SPARQL queries (SELECT, ASK, CONSTRUCT — auto-detected)

reachable_from

Dimension-capable tables for an anchor grain (many-to-one closure)

reset_cache

Clear cached schema and ontology data for the current session

sample_table_data

Preview table data with row limit and injection protection

save_semantic_model

Save a semantic model (e.g., OBML YAML) to the workspace

store_ontology_in_rdf

Persist ontology in Oxigraph for SPARQL access

suggest_semantic_names

Detect abbreviations and cryptic names for business-friendly renaming

Tool change history

Compared across complete checks of the same configuration. Tools were listed, not invoked. Input-schema changes are not measured here.

No complete tool checks yet.

FAQ

Questions about Orionbelt Analytics MCP Server

How do I connect Orionbelt Analytics MCP Server to Claude?
The listing records `claude mcp add orionbelt-analytics http://localhost:9000/mcp` as its setup step. Run it, then follow the repository's instructions for the client configuration; the listing names Claude Desktop, Claude Code, ChatGPT as compatible clients.
Is Orionbelt Analytics MCP Server free?
MCPVault has not verified a licence for this server. Check the upstream terms and pricing before use; connected APIs may require a paid account.
What can Orionbelt Analytics MCP Server do?
Orionbelt Analytics MCP Server documents 27 tools to the agent, including add_rdf_knowledge, apply_semantic_names, cleanup_workspace. The descriptions above come from project documentation. A live handshake does not test individual tool behavior.