What is OpenSCAD 3D Model Generator?
OpenSCAD 3D Model Generator is a AI tool that Transforms natural language descriptions into parametric 3D models through a pipeline of image generation, object segmentation, 3D modeling, and OpenSCAD code conversion for customizable 3D printing.. It has a Nerq Trust Score of 46/100 (D). 132 GitHub stars. Published by https://github.com/jhacksman/openscad-mcp-server. Last analyzed September 2026.
Why This Score
- ⚠️ Security: 0/100 — Some security concerns
- ⚠️ Maintenance: 0/100 — Maintenance activity is low
- ⚠️ Community: 132 stars, 0 downloads — Growing community
- ⚠️ Transparency: License: Not specified — No license specified
Trust & Safety Overview
What OpenSCAD 3D Model Generator Does
OpenSCAD 3D Model Generator is a mcp_server in the AI tool category. Transforms natural language descriptions into parametric 3D models through a pipeline of image generation, object segmentation, 3D modeling, and OpenSCAD code conversion for customizable 3D printing.. It is published by https://github.com/jhacksman/openscad-mcp-server and has no specified license. With 132 GitHub stars and 0 downloads, it has a growing community of users and contributors.
Who Should Use OpenSCAD 3D Model Generator
OpenSCAD 3D Model Generator is recommended only for experimental use. Consider alternatives with higher trust scores for production systems.
Details
| Author | https://github.com/jhacksman/openscad-mcp-server |
|---|---|
| Category | AI tool |
| License | Not specified |
| Type | mcp_server |
| Source | View on GitHub |
| Security Score | 0/100 |
| Activity Score | 0/100 |
How to Get Started
Check the trust score before installing:
curl nerq.ai/v1/preflight?target=openscad-3d-model-generator
Setup guide · Full safety report · Production review · Is it safe?
Safer Alternatives
| Tool | Trust | Stars |
|---|---|---|
| MarkItDown | 42 | 92.8K |
| Fetch | 50 | 89.4K |
| Time | 50 | 89.4K |
| Filesystem | 50 | 89.4K |
| Sequential Thinking | 50 | 89.4K |
Frequently Asked Questions
Last updated September 2026. Trust scores based on automated analysis of public data.