CADAgent for Fusion 360: open-source text-to-CAD inside Fusion

I installed CADAgent on a Thursday evening after seeing someone mention it in a Fusion 360 forum thread. The installation took about fifteen minutes, which included setting up an Anthropic API key, cloning the GitHub repo, and fumbling with Fusion's add-in loader because I always forget where Scripts and Add-Ins lives in the menu. By the time I typed my first prompt, the coffee I'd made specifically for the occasion was already lukewarm.

I typed: "Create a flanged mounting bracket, 80mm wide, 40mm tall, 3mm thick, with four M5 through holes on the flange." Then I watched. Fusion 360 started drawing a sketch. Lines appeared. Dimensions locked in. The sketch extruded. A second sketch appeared on the flange face. Circles for the holes. A cut-extrude punched them through. Fillets appeared on the corners. The timeline at the bottom of the screen filled up with features, real features, the kind you can click on and roll back and edit. The whole process took maybe forty seconds.

I sat there looking at a fully parametric bracket that I hadn't drawn. I clicked on the first sketch in the timeline, changed the width from 80mm to 100mm, and the entire model updated cleanly. That moment, right there, is why CADAgent is different from every other text-to-CAD tool I've tested.

What CADAgent actually is#

CADAgent is an open-source Fusion 360 add-in that connects to Anthropic's Claude API and translates text prompts into actual Fusion 360 modeling operations. It doesn't generate a STEP file and import it. It doesn't produce a mesh blob. It builds the model inside Fusion 360 the same way you would: sketch, constrain, extrude, cut, fillet, chamfer, pattern. Every operation lands in the timeline with full parametric history.

The project appeared on GitHub in March 2026. It's not backed by a company or a research lab. It's a community project that uses the Model Context Protocol (MCP) pattern to bridge Claude's language understanding with Fusion 360's API. You need a Fusion 360 license (or the free personal-use version) and your own Anthropic API key. The add-in sends your prompt to Claude, which generates a sequence of Fusion 360 API calls, and Fusion executes them in real time. You watch the model build itself.

If you've read the text-to-CAD open source overview, you know the open-source landscape is fragmented. OpenSCAD workflows, FreeCAD Python scripting, research prototypes. CADAgent is the first open-source project I've used that produces genuinely native, timeline-based output inside a professional CAD tool. That matters more than it sounds, because the parametric history is the whole point.

What works#

Simple to moderate mechanical parts. Brackets, plates, enclosures, shaft collars, standoffs. Anything you could describe in a sentence or two and build from basic sketch-and-extrude operations, CADAgent handles with surprising competence.

I ran it through a few dozen prompts over a weekend. A cable clamp with a screw slot came out clean. A motor mounting plate with a center bore and bolt pattern generated correctly on the first try. A simple L-bracket with stiffening ribs built perfectly. In each case, the timeline was readable. I could go back into any sketch, change a dimension, and the downstream features updated. That's not just a party trick. It means the output is actually usable in a production workflow, the same way a model you built yourself is usable.

The quality of the generated models also surprised me in small ways. The AI tends to use construction geometry properly. It creates offset planes when needed. It applies fillets in a sensible order, usually last, which is exactly what you'd want to avoid the kind of fillet-before-cut disasters that break feature trees. Whether that's Claude's understanding of CAD best practices or the add-in's prompting, I don't know. But the result is models that behave well when you modify them.

For the basics, CADAgent feels like having a junior colleague who knows Fusion 360 well enough to build your first draft while you go refill your coffee. You'll still want to check the work. But the starting point is solid, and it lives natively in the tool you're already using.

Where it falls apart#

Complex geometry. The moment your prompt requires multiple interacting features, compound curves, or geometry that depends on earlier geometry in non-obvious ways, CADAgent struggles. I asked it to create an electronics enclosure with a lid, snap-fit clips, and ventilation slots. It got about 70% of the way through before a shell operation failed, turning the timeline red. The model up to that point was usable, but the remaining features were dead. I ended up deleting the failed operations and finishing the enclosure manually, which took longer than if I'd just modeled it from scratch.

The AI sometimes makes bizarre construction choices. I asked for a stepped shaft and watched it extrude a full cylinder, then create a sketch on the end face, then cut away material to create the step, rather than just sketching the stepped profile and revolving it. The result was geometrically correct but the feature tree was ugly, and editing it later required understanding why the AI built it that way, which was harder than understanding my own modeling decisions.

Error recovery is basically nonexistent. When a Fusion 360 operation fails mid-sequence, the add-in doesn't back up and try a different approach. It just stops. You're left with a partial model and a red flag in the timeline. For an experienced Fusion user, this is manageable. You can fix the broken feature or delete it and finish manually. For someone who was hoping to avoid learning Fusion 360's interface, a half-built model with a cryptic error is not a great experience.

API costs add up faster than you might expect. Each prompt sends a substantial amount of context to Claude, including Fusion 360 API documentation and the current model state. A single part generation might cost $0.10 to $0.50 in API calls depending on complexity and how many retries the system needs. That's cheap compared to a CAD seat, but it's not free, and if you're iterating on a design through repeated prompts, the cost accumulates.

How it compares#

The comparison that matters most is against Zoo.dev. Zoo generates STEP files with real B-Rep geometry, but the output arrives as an orphaned solid. No feature tree, no sketches to edit. If you want to change a dimension, you're resketching or using direct editing.

CADAgent's output, when it works, is a fully parametric model. You can change a sketch dimension and watch the rest update. You can suppress features, reorder them, add new ones in between. The model behaves like a model you built yourself. That's a category difference.

AdamCAD offers parametric sliders, but the control is surface-level. CADAgent gives you the actual feature tree.

The tradeoff is reliability. Zoo produces output for almost any prompt. CADAgent produces better output for simple prompts and nothing usable for complex ones. If you need a quick STEP file, Zoo wins. If you need a model you'll work with inside Fusion, CADAgent wins, assuming the complexity stays within its limits. The full tools comparison has the side-by-side breakdown.

The bigger picture#

CADAgent isn't the only project connecting Fusion 360 to language models. There's a growing cluster of MCP-based Fusion 360 bridges on GitHub, including projects from faust-machines (80+ tools), ClaudeFusion360MCP (focused on teaching Claude about Fusion's coordinate system), and several others. The pattern is the same: use the Model Context Protocol to let an AI agent issue commands to Fusion 360's Python API. CADAgent is the one I've found most usable for actual part generation, but the ecosystem is moving fast.

What these projects share is the right insight: generating geometry inside the CAD environment, with access to the constraint solver and the parametric engine, produces fundamentally better output than generating geometry externally and importing it. A STEP file is a snapshot. A parametric model is a living document. The difference matters every time you need to make a change, which in real design work is approximately always.

The gap between CADAgent today and a truly reliable AI-assisted CAD workflow is still significant. Complex parts break. Error handling is crude. The AI's modeling strategy is sometimes baffling. But the foundation is right: open-source code, a professional CAD engine, parametric output, and an API architecture that will improve as language models improve. The first time you watch a model build itself in your timeline and then successfully edit it afterward, you'll understand why this approach matters more than prettier STEP files.

I still model most of my parts by hand. I've been doing it for over a decade and I'm faster than CADAgent for anything non-trivial. But for quick first drafts of simple parts, for roughing out a concept before committing to a design, for generating a starting point that I can refine instead of building from a blank sketch, CADAgent has earned a spot in my Fusion 360 toolbar. That's not a ringing endorsement. It's an honest one, which is worth more.

For related reading: Fusion 360 AI features covers what Autodesk is shipping officially, and the text-to-CAD guide puts CADAgent in context with every other tool in this space.