AI assistant integration

VectorOWL Inside Your Assistant

Teach Kimi, Claude, and Cursor to reason about your engineering ontology — OWL semantics, vector similarity, anchor constraints, and MCP coordination.

Kimi

VectorOWL Skill

A Kimi skill that embeds VectorOWL domain knowledge directly into your CLI agent. No external server required — just context and reasoning guidance.

bash

# Clone the skill into your Kimi skills directory
git clone https://github.com/OWNER/VectorOWL.git
cp -r VectorOWL/skills/kimi ~/.kimi/skills/vectorowl-neuro-symbolic-mbse

# Start Kimi — the skill triggers automatically when relevant

Works offline. Triggers when you mention VectorOWL, MBSE, OWL reasoning, anchor constraints, or MCP integration.

Claude Desktop

MCP Server

Connect Claude Desktop directly to your running VectorOWL instance. Query entities, run semantic search, and check constraints from chat.

Claude Desktop Config

{
  "mcpServers": {
    "vectorowl": {
      "command": "npx",
      "args": ["-y", "@vectorowl/mcp-server"],
      "env": {
        "VECTOROWL_API_BASE_URL": "http://localhost:8080"
      }
    }
  }
}

Requires VectorOWL API running. See skills/claude-mcp/ in the repo.

What the skill covers

OWL 2 ontology design and SPARQL-like querying patterns
Vector embedding strategies for CAD, CFD, FEA, and telemetry
Hybrid inference tuning (α parameter)
Anchor constraint catalog: scalar, relational, functional
MCP Context Server architecture and IdentityRegistry patterns
Integration plans for tool boundaries (CAD → simulation → telemetry)
Safety-case fragments and certification alignment