OpenSCAD MCP Server

The OpenSCAD MCP Server bridges the gap between natural‑language or visual prompts and parametric 3D modeling. By exposing a set of MCP resources, it lets AI assistants generate realistic renderings of objects from text or image inputs, refine those images through a review workflow, and then convert the approved views into fully‑editable OpenSCAD scripts. The result is a powerful pipeline that turns creative ideas into reusable, parametric CAD files ready for simulation or manufacturing.

The server solves the recurring challenge of turning unstructured input into robust, editable geometry. Traditional 3D modeling workflows require manual sketching or complex CAD tools; this MCP server automates the heavy lifting. It first uses AI image generators—Google Gemini or Venice.ai—to create high‑quality depictions of the target object. Multiple viewpoints are produced automatically, ensuring that the subsequent reconstruction step has enough data for accurate depth estimation. An approval mechanism allows users or AI agents to vet the generated images before they are fed into a CUDA‑accelerated Multi‑View Stereo (MVS) engine, which stitches the views into a dense point cloud and meshes it into a parametric model.

Key capabilities include:

• AI‑driven image generation that supports both text prompts and image seeds, giving designers a rapid way to prototype visual concepts.
• Multi‑view orchestration that guarantees consistent geometry across viewpoints, essential for high‑quality reconstruction.
• Image approval workflow that integrates seamlessly with AI assistants, enabling automated or human‑in‑the‑loop validation.
• CUDA MVS processing that leverages GPU power to perform reconstruction in minutes, even for complex scenes.
• OpenSCAD code generation that preserves the parametric nature of the model, allowing downstream edits without re‑reconstruction.
• Export to CSG, AMF, 3MF, and SCAD so the output can be consumed by a wide range of CAD tools or 3D printers.
• Optional printer discovery that lets users send finished models directly to networked devices.

Real‑world scenarios illustrate its utility: a product designer can describe a new gadget in plain English, let the server generate a parametric prototype, tweak dimensions via OpenSCAD variables, and instantly iterate. An educational platform could let students experiment with 3D printing concepts by generating models from simple prompts, while a rapid‑prototype lab can convert hand sketches into printable parts without manual modeling. In research, the ability to reconstruct objects from AI‑generated images accelerates object recognition studies or digital twin creation.

Integration into an AI workflow is straightforward: the MCP server exposes resources for image generation, approval, reconstruction, and export. An AI assistant can invoke these in sequence—prompting the user for a description, requesting multiple images, asking for approval, then retrieving a ready‑to‑print SCAD file. Because the server runs locally or on a dedicated LAN, latency is minimal and data privacy is maintained.

Unique advantages stem from its end‑to‑end automation, GPU‑accelerated reconstruction, and strict parametric output. By coupling AI creativity with deterministic CAD generation, developers gain a single platform that transforms ideas into tangible 3D assets, reducing both time and expertise required to produce high‑quality models.