OpenSCAD MCP Server

Name: OpenSCAD MCP Server
Author: jhacksman

@jhacksman

代码仓库

关于 OpenSCAD MCP Server

Devin's attempt at creating an OpenSCAD MCP Server that takes a user prompt and generates a preview image and 3d file.

基本信息

分类

其他

运行时

python

传输方式

stdio

发布者

jhacksman

配置

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代码仓库

工具

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概览

What is OpenSCAD MCP Server?

A Model Context Protocol (MCP) server that generates parametric 3D models from text descriptions or images using AI image generation, multi-view reconstruction via CUDA Multi-View Stereo (MVS), and OpenSCAD integration. It is designed for makers, designers, and hobbyists who want to create printable 3D models from high-level prompts.

How to use OpenSCAD MCP Server?

Install dependencies (OpenSCAD, CUDA Multi-View Stereo, Python packages), set API keys in a .env file (GEMINI_API_KEY, optional VENICE_API_KEY), then start the server with python src/main.py. Interact via MCP tools such as create_3d_model_from_text, generate_image_gemini, or use the web interface at http://localhost:8000/ui/.

Key features of OpenSCAD MCP Server

AI image generation via Gemini or Venice.ai APIs
Multi-view image generation for 3D reconstruction
Image approval workflow before reconstruction
3D reconstruction using CUDA Multi-View Stereo
Remote processing on LAN servers for heavy tasks
Parametric export formats (CSG, AMF, 3MF, SCAD)
Optional 3D printer discovery and direct printing

Use cases of OpenSCAD MCP Server

Generate a low-poly 3D model from a text description like “a low-poly rabbit”
Create multiple views of an object from a single prompt and reconstruct a 3D mesh
Offload CUDA MVS reconstruction to a powerful remote server on the same LAN
Export a parametric model to OpenSCAD source for further manual refinement
Discover and send a model directly to a network 3D printer

FAQ from OpenSCAD MCP Server

What image generation options are available?

The server supports Google Gemini API (default) and optionally Venice.ai; you can also upload your own images to skip AI generation.

How does the multi-view workflow work?

Generate multiple consistent views of an object, review and approve each image, then reconstruct a 3D model from the approved set using CUDA MVS.

Can I process reconstruction on a different machine?

Yes: run the remote CUDA MVS server (python src/main_remote.py) on a LAN machine with a CUDA GPU, then configure the main server to discover or specify that remote server.