agentcad CLI
agentcad gives an AI agent 3D design: build123d scripts, STEP export, renders, geometry checks and a live browser preview
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Extended access
Why this level
- Executes Python scripts the agent writes and writes model files, renders and logs into the project directory
Install
- Works in
In your terminal, with SkillFoxx CLI
npx skillfoxx add cli/agentcadDetects the agents on your machine, shows the access level and pins the version.
Other ways to install
Access and checks
How we reviewExtended accessThe tool runs code or makes network calls and only reads external data.
- Executes Python scripts the agent writes and writes model files, renders and logs into the project directory
This is third-party code. Review the repository files before installing.
What it does
agentcad is a local CLI for designing 3D models through a coding agent. The agent writes Python scripts with the build123d library and `agentcad run` executes them and saves a version: a STEP file, a four-view PNG, geometric metrics and optionally STL, GLB or OBJ meshes. CadQuery is supported too. The workflow is fixed in five stages: inspect, specify, build, validate, deliver. `agentcad inspect` and `agentcad measure` return topology and dimensions, `agentcad check-spec` checks a model against a `spec.json` file, `agentcad diff` compares versions and `agentcad view` opens a comparison of two STEP files. A successful build opens a stable preview page where a person pins comments to a part surface and the agent reads them with `agentcad review list`. `agentcad init` places an agent guide in the project, and a separate skill installs through `npx skills add jdilla1277/agentcad-skill`. There is also an MCP mode: `pip install agentcad[mcp]`.
Who it is for. Engineers and makers who ask Claude Code or Cursor to design a part for 3D printing or machining and want to see the result and verify dimensions.
Good fit when
- You want a stand or enclosure with exact dimensions that the agent builds from a description
- A model goes to 3D printing and needs STL or STEP files that passed validation
- A part edit must not break other geometry, so `agentcad diff` compares versions
- A client wants to leave comments directly on the model surface in a browser
Not a fit when
- You need a full CAD package with a graphical editor: agentcad works through scripts and an agent
- You need proprietary drawing formats with no STEP detour
- The machine has no Python 3.12: the tool installs through pip
Example request
Design a phone stand at a 60 degree angle, 80 mm wide, and show me a previewLimitations
- Python and the `agentcad` package from pip are required, and a virtual environment is recommended. The skill installs only guidance, and the executable must be installed separately.
- The README figures come from one CADGenBench run with GPT-5 Nano by the author, who states it is not an evaluation of the current release.
- The JSON response goes to stdout and human messages to stderr, so do not merge the streams with `2>&1` before parsing.
- Cloud projects and MCP attachments need separate setup, described in `agentcad docs`.
How to disable. Remove the package with `pip uninstall agentcad`, then the project `build` directories and the `agentcad` entry in `.mcp.json`. An installed skill is removed like any skills folder.
FAQ
How do I install agentcad?
Run `pip install agentcad` in a Python 3.12 virtual environment, then `agentcad init --name <project>`. For MCP use `pip install agentcad[mcp]`.
Which formats does agentcad export?
STEP for each version, a four-view PNG and STL, GLB or OBJ meshes through `--export`. The browser viewer can export a turntable GIF.
Is signup required?
No. The tool is open source under Apache 2.0, runs locally and needs no account.
How do I connect agentcad as an MCP server?
Install `agentcad[mcp]` and add an `agentcad` entry to `.mcp.json` with the `python` command and the arguments `-m agentcad.mcp`.
How does the skill differ from the package?
The skill from `npx skills add jdilla1277/agentcad-skill` installs guidance only. The `agentcad` executable comes from pip separately.
Discussion
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README in short
The README shows a quick start with an agent prompt, then describes the five-stage process and what each stage offers: inspect, specify, build, validate and deliver. It goes on to surface comments, CadQuery compatibility, MCP integration, cloud projects, requirements and license.