openscad-mcp-server

# openscad-mcp-server An MCP server that gives LLMs the ability to design, build, and visually verify 3D models using [OpenSCAD](https://openscad.org) — all through natural conversation. The server handles the entire workflow: discovering and downloading OpenSCAD libraries on demand, saving code, compiling STL files in Docker/Finch containers, rendering 8-angle inspection images, and returning those images directly to the LLM's vision model as inline base64 PNGs. A built-in workflow prompt guides the LLM through systematic per-angle inspection with confidence scoring, so it catches defects before declaring a model complete. ## Why this exists LLMs can write OpenSCAD code, but they can't run it, see the result, or iterate on mistakes. This server closes that loop. The LLM writes code, the server compiles and renders it in a container, and the LLM sees the rendered model from 8 angles — then decides whether to fix issues or finalize. Key design choices: - **Vision-native**: Rendered images come back as MCP `ImageContent` blocks, not file paths. The LLM sees the model directly. - **Zero config**: The `init` tool auto-detects Docker or Finch and uses the current working directory so files are visible in your IDE. Settings are persisted via the LLM's memory mechanism. No env vars or config files needed. - **Library-aware**: Libraries are discovered from the [official OpenSCAD catalog](https://openscad.org/libraries.html) and downloaded on demand. The server enforces that the LLM reads library source code before using it — no guessing at APIs. - **Correctness-first**: The workflow prompt requires per-angle confidence scoring (overall = min of all angles) and forbids declaring a model complete below 0.5 confidence. ## Quick start ### Prerequisites - [Docker](https://docs.docker.com/get-docker/) or [Finch](https://runfinch.com/) installed and running - Python 3.11+ (for development) or [uv](https://docs.astral.sh/uv/) (for running directly) ### Run with uvx (no in…