figmind

<div align="center"> <img src="./assets/banner.png" alt="figmind" width="100%" />

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<img src="https://cursor.com/deeplink/mcp-install-dark.svg" alt="Add to Cursor" height="32" />

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Give your AI the ability to think in Figma.

figmind connects any MCP-compatible AI client to Figma — letting it read, create, and modify designs in real time using natural language.

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Getting Started · Available Tools · Architecture · Contributing

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Demo

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How it works

Your AI  ←—— MCP ——→  figmind server  ←—— WebSocket ——→  Figma Plugin  ←——→  Canvas

figmind runs a local MCP server your AI can call. A companion Figma plugin bridges the WebSocket connection directly to your open file. All traffic stays on your machine — no cloud relay, no third-party API.

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Getting Started

Requirements

• Node.js 20+
• Cursor or any MCP-compatible AI client
• Figma Desktop (web version does not support local plugins)

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Step 1 — Configure your MCP client

One-click install for Cursor:

<img src="https://cursor.com/deeplink/mcp-install-dark.svg" alt="Add to Cursor" height="32" />

Or manually — open ~/.cursor/mcp.json and add:

{
  "mcpServers": {
    "figmind": {
      "command": "npx",
      "args": ["--yes", "figmind@latest"]
    }
  }
}

OS	Config path
macOS	~/.cursor/mcp.json
Windows	%APPDATA%\Cursor\mcp.json
Linux	~/.config/Cursor/mcp.json

Restart Cursor. The first run downloads figmind automatically (~5 seconds).

Using comment tools? Add your Figma personal access token:

"env": { "FIGMA_TOKEN": "your-figma-personal-access-token" }

Generate one at Figma → Account Settings → Security → Personal access tokens.

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Step 2 — Install the Figma plugin

1. Clone this repository
2. Run yarn install && yarn build:plugin
3. Open any file in Figma Desktop
4. Go to Plugins → Development → Import plugin from manifest
5. Select packages/figma-plugin/manifest.json
6. Run Figma MCP Bridge — the indicator turns green when connected

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Step 3 — Start designing with AI

With the plugin running and Cursor open, just ask:

Create a frame called "Hero" — 1440×900, centered on the canvas
Add a text node "Welcome back" at x:80, y:120, 32px Inter bold
List all color variable collections in this file
Apply the variable "color/primary" to the fills of node [id]
Create a mobile login screen with email and password fields
Review the design of the screen with node id [id] and fix spacing issues
Generate a 5-screen onboarding flow for a fitness app

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Available Tools

Canvas

Tool	Description
create_frame	Creates a new frame on the canvas
create_text	Creates a text node
create_from_html	Builds a node tree from HTML/CSS markup
get_file_context	Returns a summary of the current file
get_page_components	Lists all components on the current page

Nodes

Tool	Description
get_node	Returns a node's full data by ID
get_children	Lists a node's direct children
get_full_tree	Returns the full subtree of a node
find_nodes	Searches nodes by name or type
set_node_property	Updates position, size, fills, strokes, opacity, and more
move_node	Moves a node to a different parent
delete_node	Removes a node

Components

Tool	Description
create_component_instance	Instantiates a published component by key
swap_component	Swaps a component instance to a different master

Design

Tool	Description
get_design_system_kit	Returns fonts, colors, and tokens from the file
get_all_used_styles	Lists all styles used in the document
get_available_fonts	Lists all available fonts

Variables

Tool	Description
get_variable_collections	Lists all variable collections
get_variables	Lists variables, optionally filtered by collection
apply_variable_to_node	Binds a variable to a node property
get_library_variables	Lists variables from connected libraries

Prototype

Tool	Description
set_reactions	Sets prototype reactions (links, animations) on a node

Export

Tool	Description
export_node	Exports a node as an image (returns base64)
export_batch	Exports multiple nodes at once
export_page	Exports the full page

Comments (requires FIGMA_TOKEN)

Tool	Description
create_comment	Creates a comment on the file
get_comments	Lists all comments on the file

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Built-in Prompts

figmind ships with three ready-to-use prompts:

Prompt	Description
create-screen	Generate a mobile screen following the project design system
review-screen	Review a screen for design issues and layout problems
create-flow	Generate a full multi-screen user flow for a feature

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Architecture

packages/
├── mcp-server/      # Node.js — published to npm as figmind
│   └── src/
│       ├── index.ts        # Entry point (stdio transport)
│       ├── mcp.ts          # Server factory, registers all tools
│       ├── bridge.ts       # WebSocket bridge to Figma plugin
│       ├── prompts.ts      # Built-in prompts
│       └── tools/          # All MCP tool implementations
└── figma-plugin/    # Figma plugin — bridges commands to the canvas
    └── src/
        ├── code.ts         # Plugin main: executes all Figma API commands
        └── ui/ui.html      # Plugin UI (connection status indicator)

figmind uses the Model Context Protocol SDK over stdio, which means it works with any MCP-compatible client — not just Cursor.

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Contributing

Contributions are very welcome! Here's how to get started:

git clone https://github.com/guhcostan/figma-mcp-bridge.git
cd figma-mcp-bridge
yarn install
yarn dev   # starts both the MCP server (watch mode) and plugin bundler

Running tests:

yarn test

Adding a new tool

1. Create your tool in packages/mcp-server/src/tools/
2. Register it in packages/mcp-server/src/mcp.ts
3. Handle the command in packages/figma-plugin/src/code.ts
4. Add tests in packages/mcp-server/src/tools/__tests__/

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Publishing a New Version

Bump the version in packages/mcp-server/package.json, then:

git tag v1.0.1
git push --tags

GitHub Actions publishes to npm automatically on any v* tag.

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License

MIT © Gustavo Costa