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Genix Apolo CAD

An agent-native 3D parametric CAD for industrial machinery.
Built to be driven by an AI agent (Claude Opus or others) over MCP — or by hand in your browser.

What it is

Apolo is a headless parametric CAD for designing real machines. Its edge isn't the kernel (it uses OpenCascade, like FreeCAD) but its agent-native architecture:

Every operation is a command against an API. The whole document is an editable command log. And the same JSON Schemas that generate the UI also generate the agent's tools. One single source of truth.

The upshot: an AI agent can design complete machines end to end —not just autocomplete— and verify them: detect interferences, simulate gravity, look at a render (vision) and emit fabricable shop drawings. It's STEP-interoperable, drivable by a human or an AI, and usable as a headless backend that other tools/agents call.

MVP vertical: conveyors / material handling.

What makes it different

• 🤖 Genuinely agent-native. Not a chatbot bolted onto a CAD: the agent is a first-class client of the same API as the UI. It designs, measures, validates and fixes on its own.
• 🧾 Document = command log (event-sourced). Geometry is never stored → KB-sized files, free undo/redo, parametric editing of any past command.
• 🧬 Schema-driven. Adding a command to the registry makes it appear in the toolbar, the dialogs, the properties panel and the agent's tools — without touching anything else.
• 🔢 Variables and expressions. Any numeric field accepts "=expression" (=width-2*profile). Changing a variable regenerates the whole model.
• 🎯 Declarative edge/face selectors (by direction, face, length, proximity) — goodbye to the fragile topological naming problem.
• 🧱 Machine templates = super-commands (e.g. create_belt_conveyor, create_take_up): they inherit parametric editing, undo, BOM and agent exposure for free.

How to use it

▶ Via an AI agent (MCP) — the primary way

You mostly operate Apolo by talking to an agent. It exposes 79 MCP tools, so any MCP-compatible client (Claude Code, Claude Desktop, etc.) running a capable model —Claude Opus or others— can design entire machines. The repo ships a .mcp.json:

{
  "mcpServers": {
    "apolo-cad": {
      "command": ".venv/Scripts/python.exe",
      "args": ["-m", "apolo.mcp_server"],
      "env": { "APOLO_URL": "http://127.0.0.1:8000" }
    }
  }
}

With the server up, you ask your agent in plain language:

"Design a 4 m × 600 mm belt conveyor for 1–15 kg parcels, with a hollow-shaft gearmotor and gravity-type take-up tensioning. Check there are no interferences and show me a render."

And the agent:

1. Models with run_batch (atomic batches: one regenerate, one undo step), referencing parts from the same batch with $k and dimensions with =expression.
2. Perceives with render_view (returns an image → vision), get_topology, measure.
3. Validates with check_interference, engineering_check, gravity_test (simulates what falls).
4. Documents with drawing / drawing_set / assembly_manual → shop drawings, cut lists, BOMs and step-by-step assembly manuals.

The **wr

... View full README on GitHub