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AI-driven 3D CAD via build123d: execute, render, measure, and export geometry interactively.
AI-driven 3D CAD via build123d: execute, render, measure, and export geometry interactively.
build123d-mcp is a well-designed CAD server with robust security controls. Code quality is high, with comprehensive input validation, proper path traversal protections, and strong sandbox restrictions on executed code (blocking os, subprocess, socket, eval, exec, open). Permissions are appropriately scoped to file I/O (cwd, /tmp) and network (for legitimate CAD operations). Minor code quality findings do not materially impact security. Supply chain analysis found 3 known vulnerabilities in dependencies (0 critical, 3 high severity). Package verification found 1 issue.
4 files analyzed · 7 issues found
Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.
This plugin requests these system permissions. Most are normal for its category.
Add this to your MCP configuration file:
{
"mcpServers": {
"io-github-pzfreo-build123d-mcp": {
"args": [
"build123d-mcp"
],
"command": "uvx"
}
}
}From the project's GitHub README.
An MCP (Model Context Protocol) server that exposes build123d CAD operations as tools, enabling AI assistants to build, inspect, and iterate on 3D geometry interactively.
When using an AI to write build123d scripts, the AI writes blind — it cannot see the geometry it produces. This server closes the feedback loop: the AI can create geometry, render views, query dimensions, and catch errors incrementally rather than writing complete scripts and hoping they are correct.
execute — run build123d Python code in a persistent session; use show(shape, name) to register named partsrender_view — render one or more shapes as PNG or SVG; supports assembly compositing, high-quality tessellation, and cross-section clip planesmeasure — query bounding box, volume, surface area, topology, minimum wall thickness, or clearance between two named bodiesexport — export as STEP, STL, or both in one call; targets a named object or the current shapesession_state — full JSON snapshot of active shapes, named objects, and snapshot nameshealth_check — verify VTK/SVG/STEP/STL dependencies work end-to-end before starting worksave_snapshot / restore_snapshot / diff_snapshot — checkpoint, recover, and compare geometric stateinterference — check intersection volume between two named shapeslist_objects — list all named shapes with geometry statsversion — return the server versionreset — clear the session back to empty stateSee llms.md for full tool reference and usage patterns.
All Python dependencies (build123d, vtk, etc.) are installed automatically by uv.
No clone needed. Install directly from PyPI:
pip install build123d-mcp
Or just use uv tool run — it fetches and runs the package in one step with no prior install required (see below).
The server runs over stdio — the client launches it as a subprocess using uv tool run build123d-mcp.
Note on Python version. All examples below pass
--python 3.12. VTK and cadquery-ocp do not yet ship wheels for Python 3.13+, so pinning to 3.12 is required. uv will auto-download a managed Python 3.12 if you don't already have one.
Add to your project's .mcp.json (or ~/.claude/mcp.json for global use):
{
"mcpServers": {
"build123d-mcp": {
"command": "uv",
"args": ["tool", "run", "--python", "3.12", "build123d-mcp"]
}
}
}
Restart Claude Code after editing. The tools appear automatically once connected.
Edit ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows):
{
"mcpServers": {
"build123d-mcp": {
"command": "uv",
"args": ["tool", "run", "--python", "3.12", "build123d-mcp"]
}
}
}
Restart Claude Desktop after saving.
Open Settings → MCP and add a new server entry, or edit ~/.cursor/mcp.json:
{
"mcpServers": {
"build123d-mcp": {
"command": "uv",
"args": ["tool", "run", "--python", "3.12", "build123d-mcp"]
}
}
}
For Continue extension, add to .continue/config.json:
{
"mcpServers": [
{
"name": "build123d-mcp",
"command": "uv",
"args": ["tool", "run", "--python", "3.12", "build123d-mcp"]
}
]
}
For GitHub Copilot with MCP support, add to .vscode/mcp.json in your workspace:
{
"servers": {
"build123d-mcp": {
"type": "stdio",
"command": "uv",
"args": ["tool", "run", "--python", "3.12", "build123d-mcp"]
}
}
}
For best results, paste the contents of default_prompt.md as a system prompt in your AI client. This tells the assistant to work incrementally, verify geometry after each step, and use the tools in the right order.
Active development (v0.1.0).
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