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Devign MCP - AI-Powered Figma Design Server

A Model Context Protocol (MCP) server that lets any AI model create, read, and edit Figma designs in real time. Not limited to Claude - works with OpenAI, Gemini, local models, Cursor, VS Code, or any MCP-compatible client.

How It Works

┌──────────────┐     stdio or HTTP     ┌──────────────┐    WebSocket     ┌──────────────┐
│   AI Model   │ ◄──────────────────► │  MCP Server  │ ◄──────────────► │ Figma Plugin │
│ (any model)  │     MCP protocol      │  (Node.js)   │   localhost:3055 │  (in Figma)  │
└──────────────┘                       └──────────────┘                  └──────────────┘

The MCP server exposes 40 design tools to the AI. The Figma plugin runs inside your open Figma file and executes commands on the canvas via the Plugin API. Communication flows over a local WebSocket — no cloud services, no API keys, everything runs on your machine.

Related MCP server: Figma AI Bridge

Quick Start

Prerequisites

  • Node.js v18+

  • Figma Desktop app

  • An MCP-compatible AI client (Claude Code, Cursor, VS Code Copilot, etc.)

1. Install and Build

git clone <this-repo>
cd devign-figma-mcp
npm install
npm run build

2. Load the Figma Plugin

  1. Open the Figma desktop app

  2. Open any file you want to design in

  3. Go to Menu > Plugins > Development > Import plugin from manifest...

  4. Navigate to packages/figma-plugin/manifest.json and select it

  5. Run the plugin: Menu > Plugins > Development > Devign MCP Bridge

You'll see the plugin panel with a connection status dot. It will show red/Disconnected until you start the MCP server.

3. Start the MCP Server

npm start

The plugin dot should turn green/Connected. You're ready to go.

4. Connect Your AI

Claude Code / Claude Desktop

Add to your MCP config (~/.claude.json or Claude Desktop settings):

{
  "mcpServers": {
    "devign": {
      "command": "node",
      "args": ["/absolute/path/to/devign-figma-mcp/packages/mcp-server/dist/index.js"]
    }
  }
}

Cursor / VS Code

Add to .cursor/mcp.json or VS Code MCP settings:

{
  "servers": {
    "devign": {
      "command": "node",
      "args": ["/absolute/path/to/devign-figma-mcp/packages/mcp-server/dist/index.js"]
    }
  }
}

Any HTTP-capable Client (OpenAI, Gemini, custom apps)

Start the server in HTTP mode:

DEVIGN_TRANSPORT=http npm start

Then point your client to:

  • MCP endpoint: POST http://127.0.0.1:3100/mcp

  • Health check: GET http://127.0.0.1:3100/health

This uses the Streamable HTTP transport from the MCP spec, compatible with any client that supports it.

What You Can Do

Ask your AI things like:

  • "Create a mobile login screen with email/password fields and a submit button"

  • "Read the current page and describe the layout"

  • "Set up a design system with color tokens, text styles, and elevation shadows"

  • "Import this SVG icon and place it in the header"

  • "Create a component with Light and Dark variants"

  • "Apply auto-layout to the card frame with 16px padding and 12px gap"

  • "Export the hero section as a 2x PNG"

Full Tool List (40 tools)

Category

Tools

Creation

create_frame, add_rectangle, add_ellipse, add_text, add_shape, create_section, clone_node, set_image_fill

Components

create_component, list_components, create_instance, set_overrides, swap_component

Vectors

create_vector, create_from_svg, boolean_operation (union/subtract/intersect/exclude)

Styling

set_styles, list_styles, apply_style

Layout

apply_auto_layout

Reading

read_current_page, get_node_by_id, get_selection

Mutation

edit_node (position, size, rotation, blend modes, constraints), delete_node

Organization

group_nodes, flatten_node, create_page

Export

export_node (PNG, SVG, JPG, PDF)

Variables

list_variables, bind_variable, create_variable_collection, create_variable, set_variable_value

Design System

create_paint_style, create_text_style, create_effect_style, combine_as_variants, add_component_property

System

ping

MCP Resources

AI clients that support MCP resources can read these directly:

Resource

URI

Description

Current Page

figma://current-page

Live node tree of the open page

Selection

figma://selection

Currently selected nodes

Styles

figma://styles

All local paint, text, effect, grid styles

Variables

figma://variables

Variable collections and design tokens

Components

figma://components

Components on the current page

MCP Prompts

Guided workflows the AI can use:

Prompt

Description

create-screen

Build a full page/screen from a description

build-design-system

Set up variables, styles, and tokens from scratch

audit-accessibility

Check contrast, text sizes, and touch targets

Configuration

Environment Variable

Default

Description

DEVIGN_TRANSPORT

stdio

Transport mode: stdio or http

DEVIGN_WS_PORT

3055

WebSocket port for plugin connection

DEVIGN_WS_TIMEOUT

15000

Command timeout in ms

DEVIGN_HTTP_PORT

3100

HTTP server port (when DEVIGN_TRANSPORT=http)

Plugin UI

When the plugin is running in Figma, you'll see:

  • Green dot = Connected to MCP server, ready for AI commands

  • Red dot = Disconnected, waiting for MCP server

  • Command counter = How many commands have been processed

  • Activity log = Real-time log of commands flowing between AI and Figma

The plugin auto-reconnects if the server restarts. Keep it open while working.

Architecture

devign-figma-mcp/
├── shared/                 # Shared types and protocol definitions
│   └── src/
│       ├── commands.ts     # All command type constants
│       ├── protocol.ts     # Request/response interfaces
│       └── index.ts
├── packages/
│   ├── mcp-server/         # Node.js MCP server
│   │   └── src/
│   │       ├── index.ts    # Entry point, transport setup
│   │       ├── server.ts   # Tool/resource/prompt registration
│   │       ├── ws-bridge.ts # WebSocket bridge to plugin
│   │       ├── tools/      # 11 tool modules (40 tools total)
│   │       └── utils/      # Zod schemas, error helpers
│   └── figma-plugin/       # Figma plugin (runs in Figma)
│       ├── src/
│       │   ├── main.ts     # Command dispatcher
│       │   ├── ui.ts       # WebSocket client + UI
│       │   └── handlers/   # 11 handler modules
│       ├── manifest.json   # Figma plugin manifest
│       └── build.mjs       # esbuild config
└── package.json            # Workspace root

How commands flow:

  1. AI sends a tool call (e.g. create_frame) to the MCP server

  2. Server validates params with Zod, sends command over WebSocket to the plugin

  3. Plugin's UI thread receives the message and forwards it to the main thread

  4. Main thread dispatches to the appropriate handler, which calls the Figma Plugin API

  5. Result flows back: handler → main thread → UI thread → WebSocket → MCP server → AI

Development

# Watch mode for both server and plugin
npm run dev:server    # in one terminal
npm run dev:plugin    # in another terminal

# Build everything
npm run build

# Build individually
npm run build:server
npm run build:plugin

After changing plugin code, Figma will hot-reload if you ran the plugin via Development > Import plugin from manifest. For server changes, restart the server.

Troubleshooting

Plugin shows "Disconnected"

  • Make sure the MCP server is running (npm start)

  • Check that port 3055 is not in use by another process

  • Try restarting both the server and the plugin

AI says "Figma plugin not connected"

  • Open Figma and run the Devign MCP Bridge plugin

  • Wait for the green dot to appear before sending commands

Commands time out

  • Increase the timeout: DEVIGN_WS_TIMEOUT=30000 npm start

  • Complex operations (SVG import, large exports) may need more time

"Unknown command" errors

  • Rebuild both packages: npm run build

  • Restart the plugin in Figma

HTTP transport not working

  • Make sure you set DEVIGN_TRANSPORT=http before starting

  • Check http://127.0.0.1:3100/health to verify the server is up

License

MIT

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license - not found
-
quality - not tested
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maintenance

Maintenance

Maintainers
Response time
Release cycle
Releases (12mo)
Commit activity

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