Rajgopal Devabhaktuni

Posted on Dec 6

Automating Figma React.js Code Generation Using an MCP Server

#reactjsdevelopment #react #mcp #figma

Build faster UI pipelines with AI-assisted design-to-code workflows

Modern product teams want UI development to move at the speed of design. But the handoff between Figma designers and React engineers is still one of the biggest bottlenecks—manual translation, pixel-pushing, styling inconsistencies, and rework.

The Model Context Protocol (MCP) unlocks a new way to bridge this gap: a server-driven, AI-powered pipeline that can ingest Figma design metadata and generate clean, production-ready React components automatically.

In this post, we’ll walk through:

What the MCP Server architecture looks like
How a custom Figma MCP Server extracts design tokens, frames, nodes
How React.js code is generated (including Tailwind, styled-components, or CSS Modules)
A real example using the MCP client and LLM
Why this pattern is the future of design-engineering automation

🧩 What Is MCP?

Model Context Protocol (MCP) is an open protocol created by Anthropic that allows tools, data sources, and applications to expose capabilities to AI models through standardized “servers.”

Think of MCP as:

A bridge between external systems (Figma) and an AI model, enabling structured, contextual transformations—like design → code.

An MCP server can expose:

*Resources *(files, schemas, nodes, design tokens)
*Tools *(commands: getFrame(id), exportComponent(), etc.)
*Events *(design updates, token changes) This makes MCP perfect for automating design-to-code workflows.

🏗️ Architecture: Figma → MCP Server → LLM → React Code

Here’s the high-level flow:
[Figma File] ↓ (API) [Figma MCP Server] ↓ structured JSON [LLM / Code Generator] ↓ React output [React UI Component Library]
The MCP server acts as the normalizer—pulling precise Figma metadata and giving the LLM the right context to generate accurate JSX.

⚙️ Building a Figma MCP Server

A minimal server exposes tools like:

{
  "tools": [
    { "name": "getNode", "description": "Fetch a Figma node by ID" },
    { "name": "getDesignTokens", "description": "Extract global color/text/spacing tokens" },
    { "name": "exportFrameAsReact", "description": "Convert a frame into a JSX component" }
  ]
}

Example MCP server snippet (Node.js)

import { Server } from "@modelcontextprotocol/sdk/server";
import { getFigmaNode, extractTokens, generateReact } from "./figma-utils.js";

const server = new Server();

server.tool("getNode", async ({ id }) => {
  return await getFigmaNode(id);
});

server.tool("getDesignTokens", async () => {
  return await extractTokens();
});

server.tool("exportFrameAsReact", async ({ frameId }) => {
  const frame = await getFigmaNode(frameId);
  return generateReact(frame);
});

server.start();

This server now exposes structured Figma data to any MCP-enabled LLM client.

🎨 How React Code Is Generated

Once the MCP server returns design JSON, the LLM converts it into:
1. Component structure
Mapped from Figma frames → React functional components.
2. Styles
Depending on preference:

Tailwind CSS
CSS Modules
Styled Components 3. Auto-extracted tokens Colors, fonts, spacing become reusable constants.

🔧 Example Input → Output

Figma MCP Server Output (simplified)

{
  "type": "FRAME",
  "name": "ButtonPrimary",
  "width": 120,
  "height": 40,
  "fills": [{ "color": "#0A66C2" }],
  "cornerRadius": 8,
  "children": [
    {
      "type": "TEXT",
      "characters": "Sign In",
      "fontSize": 16,
      "color": "#FFFFFF"
    }
  ]
}

Generated React Component

export default function ButtonPrimary() {
  return (
    <button
      className="px-4 py-2 bg-[#0A66C2] text-white rounded-lg text-[16px] font-medium"
    >
      Sign In
    </button>
  );
}

A larger UI (cards, dashboards, modals) works the same way.

🧠 The MCP + AI Advantage

1. Deterministic context
The MCP server ensures the LLM sees structured JSON—not screenshots or unstructured descriptions.
2. Repeatable code style
You can lock in:

folder structure
naming conventions
component templates
styling library
prop patterns 3. Automated updates If a designer changes a button radius from 8px → 6px: MCP event → LLM regenerates code → PR created automatically 4. Team-wide consistency All components inherit the same design tokens and base patterns.

📦 Example: Consuming the Server from an MCP Client

const response = await client.callTool("exportFrameAsReact", {
  frameId: "12345"
});

console.log(response.output);

Which returns:
/src/components/ButtonPrimary.jsx
You can extend this to automatically open a PR or auto-sync to Storybook.

🚀 Why This Changes the Design-to-Code Workflow

Traditional Handoff MCP-Driven Handoff
Manual slicing Automated extraction
Ambiguous specs Structured design metadata
Pixel mismatches Token-driven consistency
Hours → Days Seconds
Repeated rework Regenerate on demand

This is the Factory Model for UI engineering—predictable, auditable, automated.

🧭 What’s Next?

You can extend your Figma MCP Server with:

Auto-generated Storybook stories
Accessibility checks (ARIA)
Variants → React props mapping
Responsive breakpoints from AutoLayout
AI-assisted layout corrections

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