Agentcad is an open-source MCP server and CLI that gives coding agents the ability to design, render, and export real CAD output. It falls into the category of AI-assisted CAD tools and is specifically built for developers who work with agents such as Claude Code, Cursor, or Windsurf. The core value is enabling these agents to autonomously generate valid, printable geometry without constant human oversight. The tool runs locally, requires no signup, and is completely free under the Apache-2.0 license. By integrating through MCP, agentcad acts as a seamless bridge between natural language prompts and concrete 3D models. This allows developers to hand off CAD tasks to their agents, streamlining the design process from concept to prototype.
The concrete problem agentcad solves is that AI agents often produce flawed geometry on the first attempt, requiring tedious manual debugging. Without a tight feedback loop, agents generate invalid shapes that cannot be printed. Agentcad provides a rapid iterative cycle where the agent runs a script and immediately receives geometric metrics and renderings. This allows the agent to catch its own mistakes before they reach the developer. Pre-execution validation checks catch errors in under 100 milliseconds, ensuring only valid geometry proceeds. As a result, developers spend less time babysitting AI outputs and more time trusting their agents to handle complex modeling tasks.
The first major feature group is execution and validation. Agentcad lets agents execute Python scripts using build123d primitives with `show_object` pre-injected. On each successful run, it produces versioned STEP files along with detailed metrics like volume, face count, dimensions, and validity status. The validation step performs pre-execution checks that catch syntax errors and logical issues quickly. This instant feedback enables the agent to iterate rapidly and correct flaws autonomously. By automating validation, agentcad ensures only robust models proceed to rendering and export, reducing wasted time on bad geometry.
The second major feature group is rendering and export. After a successful run, agentcad generates PNG previews from four angles: top, isometric front-right, isometric back-right, and isometric back-left. These visualizations allow both the agent and the human to inspect the design from multiple perspectives. For export, agentcad supports STL, GLB, and OBJ formats, covering 3D printing and web-based viewers. This means a design created by an AI agent can be directly used in a slicer or embedded in a webpage without extra conversion. The combination of render and export closes the loop from abstract code to tangible visual and physical outputs.
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The third feature group includes inspection and diff capabilities. Agentcad provides topology reports that list faces, edges, and other geometric elements, aiding in debugging complex models. The diff feature allows comparison of successive versions, making it easy to track design iteration. Additionally, agentcad offers MCP integration for tools like Claude Code, Cursor, and Windsurf via a `.mcp.json` configuration. It also includes an installable agent skill on skills.sh and ClawHub that automatically informs agents of its capabilities. These integrations make agentcad a versatile addition to any AI coding workflow, further enhancing the agent's autonomy.
The overall workflow follows a run-render-inspect-fix loop. The agent writes a Python script using build123d primitives; agentcad executes it and returns a JSON payload with status, metrics, and render paths. The agent reads this output and can autonomously correct errors before rerunning. The tool is designed for human–agent collaboration, where the developer can also view previews and exported files. Setup is minimal: scripts need zero imports because common functions are pre-injected. For MCP usage, only a single command in the agent's configuration file is required, and the first run caches the environment via uvx. This streamlined setup ensures low friction for adoption.
Concrete use cases shown in the gallery include designing an electronics enclosure with snap-fit lid from a single prompt, producing a model with 30 faces and valid geometry. Other examples are a chess rook with 59 faces, a hollow vase, and a phone stand with back support and front lip. The most complex is a 3D reconstruction of the 1903 Wright Flyer, a 234-part biplane built entirely from prompts. These outcomes demonstrate that agentcad enables agents to generate production-ready, printable geometry across a range of complexity. The output files (STL, STEP) can be directly used for 3D printing or further engineering. This empowers developers to prototype physically from natural language descriptions.
Target users are developers working with AI coding agents such as Claude Code, Cursor, and Windsurf. They are typically familiar with Python and interested in automating 3D design. The tool runs locally on Python 3.10-3.12 and is entirely open source under Apache-2.0, with no signup required. Pricing is free, making it accessible to hobbyists and professionals alike. Agentcad's platform is command-line based but integrates deeply with agent environments through MCP and agent skills. In summary, agentcad empowers AI agents to produce real CAD output directly from prompts, saving developers time and enabling rapid prototyping from idea to physical object.
Developers using AI coding agents such as Claude Code, Cursor, or Windsurf who need to generate 3D models programmatically. Also suitable for engineers and designers looking to automate CAD tasks with AI, open-source enthusiasts seeking free, local CAD tools, and Python developers familiar with build123d. The tool is tailored for those who want to hand off repetitive 3D modeling work to their agents and focus on higher-level design decisions.