From Figma to Front-End: Using AI to Generate Real Code in Seconds

If you’ve ever worked on a design system or front-end component library, you already know how much time gets eaten up by repetitive handoffs and rebuilding the same basic pieces over and over. It’s not just inefficient—it’s expensive, brittle, and a total momentum killer.

We’ve been experimenting with new ways to bring structure and speed to our design system workflows—especially for teams that need production-ready code fast. One method we’ve leaned into recently uses a powerful open-source tool called Figma-Context-MCP, originally designed to help port full-page designs from Figma into a format readable by agentic AI editors like Cursor.

But we figured out something else:

When structured correctly, component-level Figma designs—with variants, slots, and tokens—can be passed through this same pipeline. That means we can generate clean, scalable, design-token-compliant code with very little overhead.

This isn’t a generic design-to-code gimmick—it’s a precise, scalable workflow tailor-made for design systems.

🎥 Watch the demo:

Why this matters

We can build design systems in a fraction of the time, which drastically lowers the cost for clients.

Internal teams don’t have to decode the component library—they can just plug it in and go.

And the output is already aligned with our design token architecture, so it’s consistent by default.

Even better: for clients who don’t have large technical teams, we can handle both the design system architecture and the front-end product build so their internal devs can stay focused on the business logic.

Tools We’re Using (and Reimagining)

This workflow builds on top of some brilliant open-source work—but we’re applying it in a slightly unconventional way:

• Figma-Context-MCP: Originally built to bridge page-level designs to MCP, we’re using it to transfer structured design system components, including variants, slots, and composed parts.
• Model Context Protocol (MCP): A structured interface for design-to-code context. When paired with generative editors like Cursor, it enables highly agentic, reliable development workflows.

While we’ve built custom tools using Figma’s API in the past, this method has replaced them. It’s cleaner, more standardized, and easier to maintain—which means faster outcomes for our clients.

Real-world results

We’ve used this workflow to accelerate product delivery across teams of all sizes—from lean mid-market organizations to enterprise-level clients. It’s helping us cut development time, reduce handoff friction, and deliver design systems that are actually adopted, not just archived.

Sometimes, we’re augmenting internal teams. Sometimes, we’re building the whole thing ourselves. Either way, this AI-assisted process lets us focus on the hard problems—instead of rebuilding buttons and navs for the 47th time.

If you’re curious how this could help your team ship faster and scale smarter, let’s talk.