Figma ➔ Code Implementation

Highlight LangDB's capability to connect with Figma and extract design specifications that can be used to automate Python code generation.

This showcase demonstrates:

• Querying Figma design files programmatically.

• Extracting layout and component metadata.

• Using the design metadata as the basis for Python implementation

Why It Matters

• Bridge the gap between design and engineering workflows.

• Save time by automating the extraction of Figma designs.

• Empower developers to move from design-to-code faster.

How It Works

Figma Design ➔ AI Agent ➔ Extract Metadata ➔ Implement in Python

Your AI Agent/Editor reads the Figma file structure, extracts relevant information, and enables code generation based on the design layout.

MCP Server Setup

Figma MCP Server

• Authentication: Personal Access Token (API Key).

• Environment Variables: API key must be securely stored.

Steps:

1. Generate a Figma Personal Access Token from Figma Settings.

2. Configure the Figma MCP server inside LangDB using this token.

MCP Server	Authentication Type
Figma	Personal Access Token

Checkout:

• Figma MCP Server: https://app.langdb.ai/mcp-servers/figma

Interaction Flow

Example Query

Implement this Figma design <figma link> in a single react component.

Cursor Output

import React from 'react';
import './LandingPage.css';

const LandingPage = () => {
  return (
    <div className="landing-page">
      <div className="content">
        <h1 className="title">Find the project you love</h1>
        <p className="description">
          Lorem ipsum dolor sit amet, consectetur adipiscing elit. Faucibus in libero risus semper habitant arcu eget. Et integer facilisi eget diam.Lorem ipsum dolor sit ame,consectetur
        </p>
        <button className="primary-button">Explore</button>
      </div>
      </div>
    </div>

Key Takeaways

• Automate the jump from UI/UX design to functional Python code.

• Use Figma as a dynamic blueprint for real applications.