Design-to-code tools are often compared based on how close the output looks to the original design. But once you start using the generated code, other differences start to matter just as much.
Some tools get the visuals mostly right but fall short on basic functionality. Others generate working interactions but produce structures that are hard to work with or extend. These tradeoffs aren’t obvious initially; you only see them when you actually run the code and start interacting with it.
In this blog, we will compare three popular design-to-code approaches: Figma MCP, Anima, and Kombai. We will evaluate them across four practical dimensions — visual match, functionality, component structure, and code quality and see how each performs in a real-workflow.
We used the same Figma frame and tech stack. For MCP+Cursor and Kombai, we used identical prompts; Anima was evaluated on exported UI code + the minimum manual wiring needed to match the same functional requirements.
What is Figma MCP
Figma MCP is an implementation of the Model Context Protocol(MCP) that exposes the internal structure of Figma designs to AI models.
Instead of working from screenshots or images, the model can access layout data, components, variables, and constraints directly from the design file.
When the model understands what is a component, what is repeated, and how elements relate to each other, it’s less likely to drift from the original design. This results in code that better reflects the designer’s intent than prompting from images alone.
That said, Figma MCP doesn’t generate code on its own. It acts as a bridge, allowing tools like Cursor to generate from Figma designs with much better context.
This also means that the quality of the output depends heavily on the model you’re using, the prompts you write, and how much you guide the process.
What is Anima
Anima is a Figma-to-Code tool that converts designs into code.
You install the Anima plugin directly inside Figma, where you select a frame, choose a target framework, and then it generates code based on the visual structure of the design.
You can copy the generated code, or you can open it in Anima’s playground to edit and preview before the final export.
It can be a good option for quick prototyping, but the generated code often needs cleanup before you can use it in a real project.
What is Kombai
Kombai takes an engineering-first approach to the design-to-code problem.
Instead of translating Figma files pixel by pixel, Kombai tries to understand the design the way a frontend developer would.
It looks beyond the layer tree to understand what the UI is supposed to be, even when the design has messy grouping, extra layers, or inconsistently used components.
When generating code, Kombai prioritizes production quality over visual parity alone. It applies framework-specific best practices and produces structured, reusable components that follow the conventions of the chosen stack.
Kombai also works well in the context of an existing codebase. It analyzes your project’s patterns and adapts its output to match them, so the generated code feels native to the repo instead of something that needs to be heavily rewritten.
The Test Setup
To compare how these three methods differ, we took a Figma template and tested it across:
- Figma MCP with Cursor,
- Anima
- Kombai
Each tool was given the same task, the same tech stack, and the same prompts. We used two prompts, one for initial UI setup and another for implementing the functionalities.
Here’s the first one that we used: “Convert this frame into a React + TypeScript + Tailwind page with high visual fidelity.”
To evaluate the results, we compared them on the following dimensions:
- Design match
- Component structure
- Functionality and interactivity
- Code quality
The following section breaks down how each tool performed against these criteria.
Head-to-head comparison: Figma MCP Vs Anima Vs Kombai
In this section, we will see how each tool performed across the above mentioned grounds and compare them side by side.
Design Match
Here, we want to examine the fidelity that each tool provides and see how closely it aligns with the original Figma design.
With a reference in place, we often want the same match. That includes using the same typography, colors, icons, etc. So, a tool that provides high visual fidelity wins here.
This is our original design reference:
Figma MCP
Here’s what Figma MCP + Cursor(Auto) generated:
Notice the right sidebar, which has white cards in the original design, but here, the entire section is green with no such distinction. The stats card at the bottom doesn't match. Similarly, the notification and user profile are in the wrong section.
The language element’s style (EN) doesn't match the original, and the left sidebar’s font and icon color are also different.
Overall, the fidelity of the Figma MCP’s output is relatively low. Broad elements are accurate, while small details are off.
Anima
Here’s the output Anima generated:
If you look at the right sidebar, it’s different from the original design. Anima made the entire sidebar light green, whereas only the background was supposed to have that color, with cards being white.
It also missed a few authors' profiles. The original one had six authors; this one has just four.
Apart from that, there are a few minor things that Anima got wrong. For example, the language element should be positioned at the top right, rather than its current location. The user profile and notification have excessive space between them, along with a mismatched color for the notification icon.
Overall, the fidelity of the Anima's output is also low.
Kombai
Here’s the page Kombai produced:
The fidelity of the output is significantly close to the original design. Almost everything matches correctly. The colors are correct, and all the elements from the original design were incorporated well by Kombai. There are correct number of authors' profiles as well, without missing any element.
The only detail Kombai missed is that the audio player card doesn’t have the wavy illustrations, and in the bottom stats cards, the content is not aligned horizontally.
Functionality and interactivity
For functionality and interactivity, we want to verify two things. First, the search function should work so that typing a book name or an author’s name from the list brings that book up. A user can see the details about a book by clicking on it.
Secondly, clicking a book updates the player, highlighting the selected book. The dummy audio player should function, i.e., a user should be able to select a book and choose to play or pause it. There won’t be any actual audio; we are just verifying the logical flow using the HTML Audio element.
Here’s the second prompt that I used for implementing these functionalities :
“Implement a working search that filters books by title and author, a properly implemented audio player with play/pause, progress with proper visual, and a dedicated book details page. Clicking on any book should navigate to its details page, display relevant book information (title, author, description, duration, cover), and allow the user to play from the details page. A user should also be able to play from the dashboard list.”
Figma MCP + Cursor (Auto)
Here’s the interactivity output of Figma MCP + Cursor:
Figma MCP implemented the book details page as well as the audioplayer function correctly, but it did not implement the playback from the dashboard page.
In the prompt, I asked to let a user play a book from the dashboard book list, along with the details page. Currently, playback is available only when I open the details page. Functionality details are not fully implemented by Figma MCP + Cursor.
Anima
Here’s the output showing the functionality Anima generated:
Anima implemented the search functionality smoothly. It also did the details page well, but where it lacked was the audio player.
The forward and backward buttons were not working; only the play and pause buttons worked. Overall, the functionality for this page was pretty decent except for this part.
Kombai
Below is the output of Kombai showcasing the functionalities:
Kombai implemented the required functionalities accurately. The search function works. I can read details about a book and play it both from the details page and the dashboard, something that Figma MCP missed.
The audioplayer also works well. I can play, pause, or drag the audio using forward and backward buttons, and it all matches the timestamp perfectly.
Component Structure
Component structure plays an important role in how usable the generated code actually is. Poorly structured components can make a codebase hard to understand, extend, or maintain.
So, in this section, we look at how each approach breaks the UI down into components, how reusable those components are, and whether the structure feels natural to work with in a real project.
Figma MCP + Cursor
Here’s the structure that Figma MCP created:
Figma MCP created a clean component structure. Major sections of the page like header, sidebar, main content, and right sidebar are split into separate components. Repeated UI elements like book cards and author cards are also extracted into their own files.
Overall, the structuring is pretty decent.
Anima
Below is the structure Anima produced:
Files like Dashboard.tsx and BookDetails.tsx contain large portions of the layout and behavior. Only basic elements live in components/ui. Sections such as book lists and authors are not consistently extracted into standalone components.
This results in fewer components and larger files. The code works for quick prototypes, but reuse and extension would require heavy manual refactoring.
Kombai
Kombai produced a very clean and readable structure:
It separated reusable components from screen-level layout.
Basic UI elements live in components/ui. Components like book cards, author cards, and the audio player are defined independently and then composed inside screens such as the Dashboard.
This makes it easier to reuse components without modifying them.
Code Quality
Here, we will focus on an important piece of the UI and look at how each tool implemented it. For the comparison, we will pick the Audioplayer component of the UI because it involves user interaction, time, and state updates.
The goal is to see how close the implementation felt to something a frontend developer would actually write for a production application.
Figma MCP + Cursor
With Figma MCP, Cursor generated an <AudioPlayer /> component along with a Zustand store to hold the playback state.
The <AudioPlayer /> component, which renders the UI, is also responsible for moving playback forward, while the store keeps track of things like the current time, total duration of the book, and whether playback is active.
There’s no real audio element. Instead, playback is simulated using a timer inside the component.
When a book is selected, and playback is active, the component starts an interval that advances time once per second:
intervalRef.current = window.setInterval(() => {
const state = useAudioPlayerStore.getState()
const newTime = state.currentTime + 1
if (newTime >= state.duration) {
onPlayPause?.()
state.setCurrentTime(state.duration)
} else {
state.setCurrentTime(newTime)
}
}, 1000)
As long as playback is active, the timer increments currentTime once per second. When the value reaches duration, the component sets the time to the end and triggers onPlayPause.
There’s no browser-driven playback here. Time moves forward because the component explicitly updates it on a fixed interval.
The UI simply reflects whatever state exists in the store. Progress is calculated from currentTime and duration:
const progress = duration > 0 ? (clampedTime / duration) * 100 : 0
Clicking the progress bar converts the click position into a timestamp and writes it back to the state. This keeps the progress bar and timestamps aligned with whatever value currentTime happens to be at.
The issue with this implementation is that the source of playback is the timer inside the component, not browser playback events. There’s no real audio element involved. The player isn’t reacting to browser playback events; it’s just advancing time on a schedule.
This is more like a mock player than a real one. It works for this demo, but it’s not how you’d typically implement real audio playback in a production app.
Anima
In Anima’s output, audio playback is implemented using a shared React context.
const AudioContext = createContext<AudioContextType | undefined>(undefined);
export const AudioProvider: React.FC<{ children: React.ReactNode }> = ({ children }) => {
const audioRef = useRef<HTMLAudioElement>(null);
return (
<AudioContext.Provider value={...}>
{children}
<audio ref={audioRef} />
</AudioContext.Provider>
);
};
The provider creates an <audio> element and listens to browser events to track the current playback time and total duration:
audio.addEventListener('timeupdate', updateTime);
audio.addEventListener('loadedmetadata', updateDuration);Play and pause are wired directly to the audio element, so basic playback works as expected:
if (isPlaying) {
audioRef.current.pause();
setIsPlaying(false);
} else {
audioRef.current.play();
setIsPlaying(true);
}Where this output falls short is in how much of that playback engine is actually used by the UI.
In the output, we saw earlier that the only interaction that works is play and pause. Forward or backward buttons don’t work.
So while the underlying implementation is fine, Anima did not use it completely to execute the full prompt.
Kombai
Kombai splits the audio player into three parts: the UI component, a playback hook, and a shared store.
The <AudioPlayer /> component stays UI-only. It reads currentTime and duration from the store and updates the store when the user scrubs:
const handleProgressChange = (e: React.ChangeEvent<HTMLInputElement>) => {
const newTime = parseFloat(e.target.value);
setCurrentTime(newTime);
};
Actual playback lives inside useAudioPlayer() hook, which creates an audio element and updates the audio source when the selected book changes:
if (!audioRef.current) {
audioRef.current = new Audio();
audioRef.current.preload = 'metadata';
}
audio.src = currentlyPlaying.book.audioUrl;
audio.load();As the audio plays, the hook listens to browser events and uses them to keep playback time and duration updated from the audio element:
audio.addEventListener('timeupdate', () => {
setCurrentTime(audio.currentTime);
});
audio.addEventListener('loadedmetadata', () => {
useAudiobookStore.setState({ duration: audio.duration });
});When the audio ends, it automatically moves on to the next item in the queue:
audio.addEventListener('ended', () => {
useAudiobookStore.getState().playNextInQueue();
});And if playback fails to start, it catches that case and updates the state to paused so the UI doesn’t show a playing state incorrectly:
audio.play().catch(() => {
useAudiobookStore.setState({
currentlyPlaying: { ...currentlyPlaying, state: 'paused' },
});
});Kombai lets the browser drive playback, so the UI stays focused on rendering rather than controlling time logic. This separation of rendering, state, and playback logic is very close to how a frontend developer would normally structure this feature.
Conclusion
All three approaches aim to solve the same problem – turning designs into usable frontend code, but they do so with very different tradeoffs.
Figma MCP provides better design context than image-based prompting, but the final output still depends heavily on the model and prompts. Anima is useful for quick prototypes, but the generated code often needs heavy cleanup before it can be used in a real product.
Kombai, on the other hand, focuses more on producing structured, production-ready code that fits naturally into an existing codebase.
What matters most is understanding these differences upfront – so the tool you choose reduces work instead of adding it later.