8/11/2025

Can Generative AI Actually Design Your Home in Revit via an MCP?

Hey everyone. Let's talk about something that's been buzzing around the architecture & design world like crazy: Artificial Intelligence. You've probably seen the stunning, sometimes bizarre, architectural renderings floating around online, all generated by AI. It’s led to this massive question: can AI actually design your home? Not just make a pretty picture, but create a real, buildable model in a program like Revit?

The short answer is… kinda. But the long answer is WAY more interesting. It involves a whole new layer of tech, a bit of a language lesson on what "generative" really means, & a healthy dose of reality. Turns out, we've hit a major milestone, & it's all thanks to something called the Model Control Protocol, or MCP. This could genuinely change how buildings get designed. So, let's get into it.

The New Translator in Town: What the Heck is a Model Control Protocol (MCP)?

Alright, so for the longest time, getting a super-smart AI like Claude to talk to a complex program like Revit was a clunky, custom-coded nightmare. Every new task needed a new script. It was like trying to have a conversation where you had to hire a new translator for every single sentence.

Then, Anthropic (the folks behind Claude) released something called the Model Control Protocol (MCP). The best way to think of it is like a USB-C port for AI. Before USB-C, you had a different cable for your phone, your camera, your external hard drive… it was a mess. USB-C standardized it. MCP aims to do the same thing for connecting AI models to applications.

It's basically a standardized set of rules, an open framework, that lets an AI communicate with a program like Revit. Instead of writing a million little one-off scripts, developers can build an MCP server for Revit. This server acts as a go-between. The AI sends a command in a standard format—like "get me information on all the doors on the first floor"—& the MCP server translates that into an action Revit can understand using its own API.

This is a HUGE deal. It decouples the AI from the specific, nitty-gritty code of Revit. The AI just needs to "speak MCP." This opens the door for AI assistants to not just read what's in your Revit model, but to actually edit it using plain English. And because it's a standard, it could eventually allow an AI to coordinate between the architectural model, the structural model, & the MEP model all at once, creating a much more connected BIM ecosystem.

Let's Get Our Terms Straight: Generative AI vs. Generative Design

This is where a lot of people get tripped up. The terms "Generative AI" & "Generative Design" are often used interchangeably, but they're really two different beasts. Knowing the difference is key to understanding what's actually happening.

Generative AI is what you probably think of first. This is stuff like Midjourney, DALL-E, or Claude. You give it a prompt—"a modern cabin in the woods with a glass facade," for example—& it creates something new based on the mountains of data it was trained on. It's fantastic for brainstorming, concept generation, & creating visual styles. It operates in what one expert calls the "fuzzy creative realm of pixels." It's an artist, a poet, a brainstormer.

Generative Design, on the other hand, is an optimizer. It's been around for a while, particularly in tools from Autodesk. With generative design, you don't give it a creative prompt; you give it a set of goals & constraints. For example, you might say: "I need to arrange the furniture in this office layout. My goals are to maximize the amount of natural light for each desk, keep the noise levels low in this section, & facilitate easy movement between these three departments. Here are the dimensions of the room & the furniture."

The computer will then generate thousands of design options, analyzing each one based on your goals. It's not "creating" in a human sense; it's using algorithms to explore a solution space & find the highest-performing options. It's a ruthless problem-solver.

The real magic happens when these two start working together. You could use Generative AI to come up with a stunning initial concept for a building, & then use Generative Design to optimize its floor plan for energy efficiency & construction cost. It’s the perfect blend of right-brain creativity & left-brain logic.

So, What Can AI Actually Do in Revit Today?

This is the exciting part. With the development of MCP & tools like Revit Vibe, we're moving beyond theory & into actual application. We're not at the point where you can just say "design me a three-bedroom house" & get a perfect, permit-ready set of drawings. But what it can do is pretty mind-blowing.

Here are some real examples of what's possible right now:

Text-to-3D Model: You can literally type a detailed description of a building into an AI like Claude—specifying floor sizes, room types, window styles, etc.—& the AI, connected to Revit via MCP, will generate a 3D BIM model in seconds. And we're not talking about a "dumb" visual model; it's a real BIM model with editable properties.
Natural Language Editing: This is where it gets REALLY powerful for day-to-day work. Imagine a huge, complex model with thousands of elements. Instead of manually selecting things, you can just type commands like: "Find all the outward-opening doors & change them to inward-opening." The AI does it instantly. Or "Create a new 3D view where all the stairs are red & everything else is semi-transparent." Boom, done in a second.
Intelligent Analysis & Documentation: You can ask the AI to do things that would normally take ages. For example, "Color-code all the fire-rated walls based on their rating & give me a report of how many of each there are." The AI will not only color the walls in the model but also spit out a detailed list.
Automating Tedious Chores: Think about all the time architects spend on repetitive tasks. AI-enhanced plugins & scripts can now automate things like creating sheet layouts, tagging elements based on their properties, & organizing project views. It’s like having the world’s most efficient intern.

This is all still pretty new, & right now it's mostly enthusiast developers & early adopters pushing the envelope. But it's not hard to see where this is going. This kind of intuitive, language-based control is the future.

Honestly, it mirrors what we're seeing in other business areas. The whole point is to make complex systems more accessible & automate repetitive communication. For example, here at Arsturn, we help businesses build no-code AI chatbots trained on their own data. The goal is to provide instant, 24/7 support & answer customer questions without them having to dig through menus or wait for a human. It's about creating a seamless conversational interface to get things done, whether you're designing a building in Revit or helping a customer on a website.

Is Anyone Actually Using This Stuff?

It's a fair question. Is this just a bunch of cool tech demos, or is it being used in the real world? The answer is both. The natural language text-to-BIM stuff is very new, but the principles of generative design have been used on some pretty high-profile projects.

A great example is Autodesk's own office in Toronto. They wanted to design the layout to encourage "happenstance interactions"—those random encounters between people from different teams that often spark new ideas. That's a really hard thing to design for manually. So, they used generative design. They fed the AI their goals & constraints, & it produced about 10,000 layout options in just a few days. The architects then acted as reviewers, choosing the best option. It completely flipped the traditional design process on its head.

We've also seen it used by major firms like the Bjarke Ingels Group (BIG) on complex facade projects & by others to explore sustainable design options for buildings, optimizing for things like energy use & natural daylight from the very beginning of the design process.

So yes, while some of the most futuristic-sounding applications are still emerging, the core idea of using AI to explore & optimize designs is already here & delivering real value.

The Elephant in the Room: The Big Limitations & Challenges

Okay, let's pump the brakes a little. As exciting as all this is, AI is NOT a magic bullet. There are some serious limitations & challenges that we need to be honest about.

The "Human Touch" is Still Missing: AI is trained on existing data. It's great at remixing & optimizing, but it can't truly innovate in a way a human can. It lacks cultural understanding, emotional intuition, & the ability to listen to a client's unspoken needs. An AI can give you a design, but an architect can translate your life into a home.
Garbage In, Garbage Out: AI models are only as good as the data they're trained on. If the data is biased or incomplete, the designs it produces can be flawed, uninspired, or just plain weird. There's a real risk of creating homogenized, soulless architecture if we rely on it too much.
The Reality Gap: An AI might generate an absolutely stunning design that is structurally impossible, violates a dozen building codes, or would cost a billion dollars to build. There's a HUGE gap between a cool-looking concept & a feasible, buildable project. The expertise of a human architect & engineer is still absolutely essential to bridge that gap.
Skills & Over-Reliance: This new technology requires a new set of skills. Architects are becoming less about manual drafting & more about being expert prompt writers & AI directors. There's also the danger that we become so reliant on these tools that our own critical thinking & problem-solving skills begin to atrophy.
Who Gets Sued? The ethical & legal questions are a minefield. If an AI-generated design fails, who's responsible? The architect who used the tool? The software company? The AI developer? These are thorny issues that the industry is only just beginning to grapple with.

It's important to approach these tools with a healthy dose of skepticism. The most successful implementations will be those that see AI as a partner, not a replacement. This is why having control over the AI is so important. When businesses use a solution like Arsturn, for example, they aren't just letting a generic AI run wild. They are carefully training it on their own specific documents, website content, & knowledge base. This ensures the AI's responses are accurate, on-brand, & aligned with the business's goals, which helps mitigate a lot of the "runaway AI" fears. The same principle applies to architecture; the architect must remain the one who trains & guides the AI.

The Future Architect: Conductor of an AI Orchestra

So, back to our original question: Can Generative AI really design your home in Revit? Not entirely, & not on its own. Not yet, anyway.

What it can do is fundamentally change the process. The role of the architect is shifting from being a lone artist or a master drafter to something more like the conductor of an orchestra. They are the ones with the vision, the taste, & the deep understanding of the project's goals. The AI, with its immense processing power, becomes the orchestra.

The architect will guide the AI, asking it to explore thousands of options, to automate the tedious tasks, & to provide data-driven insights. This frees them up to focus on what humans do best: creativity, strategic thinking, client relationships, & navigating the complex realities of getting a building built.

The developments we're seeing with the Model Control Protocol are just the beginning. Within the next couple of years, I think we'll see these tools become much more refined & integrated into standard workflows. It's an exciting & slightly terrifying time to be in the industry, but one thing is for sure: the way we design our built world is about to change forever.

Hope this deep dive was helpful! I'm really curious to hear what you all think about this. Is it the future, or just a passing fad? Let me know in the comments.