open-ontologies-lite 0.1.1

Lightweight Python bridge to the Oxigraph RDF/OWL engine, MCP server included. No Rust toolchain, no compilation.

Open Ontologies Lite (Python bridge)

A lightweight, pip-installable Python bridge to the same Oxigraph RDF/OWL engine that powers Open Ontologies. No Rust toolchain, no compilation, no multi-gigabyte build directory — pyoxigraph ships the engine as a prebuilt wheel, so everything here is pure-Python glue installed from PyPI.

It exposes the core ontology lifecycle as both a Python library and an MCP server.

Why this exists

The full Rust engine compiles a large dependency tree from source (5+ GB of build artifacts, heavy SSD churn). This bridge is the opposite trade: install in seconds, run anywhere Python runs, keep the Oxigraph SPARQL engine underneath. It covers the core surface (validate, load, query, diff, lint, convert, stats, save), not the full 100-tool engine.

Install

pip install open-ontologies-lite        # one universal wheel, no compiler

Use as a Python library

from open_ontologies_lite import OntologyEngine

engine = OntologyEngine()
engine.load(open("ontology.ttl").read())          # load Turtle
print(engine.stats())                              # {'triples':..,'classes':..,..}

rows = engine.query(
    "SELECT ?c WHERE { ?c a <http://www.w3.org/2002/07/owl#Class> }"
)
print([r["c"] for r in rows["rows"]])

print(engine.lint())                               # missing labels/domains/ranges
print(OntologyEngine.convert(ttl, "turtle", "ntriples"))

See examples/python_usage.py for a runnable end-to-end script.

Use as an MCP server

open-ontologies-lite          # stdio MCP server
# or: python -m open_ontologies_lite

Register it with any MCP client (e.g. Claude):

{
  "mcpServers": {
    "open-ontologies-lite": { "command": "open-ontologies-lite" }
  }
}

Tools

Tool	Purpose
onto_validate	Parse RDF/OWL and report syntax validity + triple count (no load)
onto_load / onto_load_file	Load RDF text or a file into the in-memory store
onto_clear	Reset the store
onto_stats	Triple / class / property / individual counts
onto_query	SPARQL SELECT / ASK / CONSTRUCT / DESCRIBE
onto_save	Serialize the store to a file
onto_convert	Convert between Turtle / N-Triples / N-Quads / TriG / RDF-XML / N3 / JSON-LD
onto_diff	Triple-level diff between two ontologies
onto_lint	Missing labels, domains, ranges

Relationship to the Rust engine

This is the Python layer of the project. For the full engine (three-layer Dynamics/Causal/Planner architecture, HNSW semantic search, OWL2-DL tableaux reasoning, PDDL planning, governance, 100 tools), use the Rust build. Same Oxigraph core; pick the weight class you need.

License

MIT