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.

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