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Understanding Figma Console MCP

New to AI-powered design tools? This guide explains everything you need to know—no technical background required.

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What is an MCP?

MCP stands for Model Context Protocol. Think of it as a universal translator that lets AI assistants (like Claude, ChatGPT, or Cursor) communicate with external tools and services. Without MCP, AI assistants are limited to what they already know. With MCP, they can:
  • Connect to tools like Figma, GitHub, or databases
  • Read real data from your actual projects
  • Take action on your behalf (with your permission)
Simple analogy: If an AI assistant is like a helpful colleague, MCPs are like giving them access to your tools. Instead of describing your Figma file over chat, they can actually look at it.

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What is Figma Console MCP?

Figma Console MCP is a specific MCP server that connects AI assistants to Figma. It transforms your design system from static files into a queryable API.

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What it enables:

Extract

Pull design tokens, components, and styles as structured data

Create

Build UI components and layouts directly in Figma through conversation

Debug

Capture console logs, errors, and screenshots from Figma plugins

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In plain English:

Instead of manually copying values from Figma, you can ask: 
"What's the padding on the Button component?"
Instead of transcribing tokens to CSS, you can say: 
"Export all color variables as CSS custom properties"
Instead of building UI by hand, you can describe: 
"Create a card component with an image, title, and action button"
The AI reads your actual design system, uses your real tokens, and generates accurate code—or creates designs directly in Figma.

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Why Does This Matter?

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The Problem

Every time a developer opens Figma, eyeballs the padding, and writes margin: 16px instead of var(--spacing-md)—that’s design system debt. Common pain points:
  • Design tokens manually transcribed to CSS (and often wrong)
  • Component specs described in Slack messages
  • “Just check Figma” that leads to guesswork and approximation
  • Designs and code drift apart over time

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The Solution

What if your design system was queryable? Figma Console MCP makes this real. Your design system becomes:
  • Programmable — Tokens export to CSS, Tailwind, or Sass automatically
  • Queryable — AI can look up any value, any component, any style
  • Alive — Single source of truth that developers can access directly
  • Creative — AI can create designs using your actual tokens and components
Result: Developers stop guessing at values. Design debt decreases. Designs and code stay in sync.

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Who Is This For?

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Make Your Design System Programmable

Your design system is a product. Developers are your users. Give them an API.With Figma Console MCP, you can:
  • Export design tokens in any format (CSS, Tailwind, Sass, JSON)
  • Generate documentation automatically
  • Let developers query component specs directly
  • Create consistent UI through AI-assisted design
Example prompt:
"Generate a style guide from my color and typography variables"

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How Do I Get Started?

Getting connected takes about 2 minutes with our recommended setup.

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Quick Setup (Remote Mode)

1

Open Claude Desktop Settings

Claude menu → Settings → Connectors
2

Add Custom Connector

Click “Add Custom Connector”
3

Enter Connection Details

  • Name: Figma Console
  • URL: https://figma-console-mcp.southleft.com/sse
4

Start Using

That’s it! Ask Claude anything about your Figma files.
First time using design tools? The AI will automatically open a browser window for Figma authorization. Just click “Allow” once and you’re connected.

Full Setup Guide

Detailed instructions for Claude Desktop, Claude Code, Cursor, and other AI clients.

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What Can I Do With It?

Here are real prompts you can try right now:

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Design System Extraction

Get all design variables from https://figma.com/design/YOUR_FILE_ID

Export color styles as Tailwind config

Show me the Button component with a visual reference image

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Component Implementation

Get the Card component specs and help me implement it in React

What's the spacing between elements in the navigation bar?

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Plugin Debugging

Watch console logs for 60 seconds while I test my plugin

Show me only error logs from the last 5 minutes

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Design Creation (Local Mode)

Create a notification toast with icon, title, and dismiss button

Build a user profile card using the Avatar and Button components

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Remote vs Local Mode

Figma Console MCP offers two ways to connect:
FeatureRemote ModeLocal Mode
Setup2 minutes, zero install15 minutes, requires Node.js
AuthenticationAutomatic (OAuth)Manual token setup
Read operations✅ Full access✅ Full access
Write operations❌ Read-only✅ Create designs
Variables APIEnterprise plan requiredWorks with any plan
Best forMost usersPlugin developers, design creation
Start with Remote Mode. It’s the fastest way to get value. If you need write capabilities or plugin debugging, you can upgrade to Local Mode later.

Compare Modes in Detail

Understand the technical differences and choose the right setup.

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Frequently Asked Questions

No! You interact through natural language. Just describe what you want in plain English, and the AI handles the technical details.
Yes. Remote mode uses OAuth (the same secure login as “Sign in with Google”). Your credentials are never shared with the MCP server—only temporary access tokens. Local mode keeps everything on your machine.
No—they’re complementary! Figma’s official MCP generates code from designs. Figma Console MCP extracts raw data, debugs plugins, and creates designs. Use both for the complete workflow.
Any MCP-compatible client: Claude Desktop, Claude Code, Cursor, Windsurf, Zed, and others. If your AI tool supports MCP servers, it works with Figma Console MCP.
Yes! Figma Console MCP is open-source (MIT license). The hosted remote server is free to use. You can also self-host if you prefer.

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Next Steps

Setup Guide

Connect your AI assistant in minutes

Use Cases

Real-world examples and workflows

All Tools

Complete reference for 36+ tools
Open Source — Figma Console MCP is MIT licensed. Contribute, customize, or self-host for enterprise requirements on GitHub.