Cursor Talk to Figma MCP logo

Cursor Talk to Figma MCP

CommunityPopular
sonnylazuardi

TalkToFigma: MCP integration between AI Agent (Cursor, Claude Code) and Figma, allowing Agentic AI to communicate with Figma for reading designs and modifying them programmatically.

Publishersonnylazuardi
Repositorycursor-talk-to-figma-mcp
LanguageJavaScript
Forks
735
Stars
6.8K
Available tools
0
Transport typestdio
Categories
LicenseMIT
Links
  • Connect tools to AI workflows

    Cursor Talk to Figma MCP exposes MCP capabilities that can be used by compatible AI clients and agents.

  • 0 available tools

    Browse the callable actions below, including names and descriptions when provided by the server.

  • Ready-to-copy setup

    Use the installation snippets to configure this server in your preferred MCP client.

  • Open source signals

    6.8K stars and 735 forks from the linked repository.

Talk to Figma MCP

This project implements a Model Context Protocol (MCP) integration between AI agent (Cursor, Claude Code) and Figma, allowing AI agent to communicate with Figma for reading designs and modifying them programmatically.

https://github.com/user-attachments/assets/129a14d2-ed73-470f-9a4c-2240b2a4885c

Project Structure

  • src/talk_to_figma_mcp/ - TypeScript MCP server for Figma integration
  • src/cursor_mcp_plugin/ - Figma plugin for communicating with Cursor
  • src/socket.ts - WebSocket server that facilitates communication between the MCP server and Figma plugin

How to use

  1. Install Bun if you haven't already:
bash
curl -fsSL https://bun.sh/install | bash
  1. Run setup, this will also install MCP in your Cursor's active project
bash
bun setup
  1. Start the Websocket server
bash
bun socket
  1. NEW Install Figma plugin from Figma community page or install locally

Quick Video Tutorial

Video Link

Design Automation Example

Bulk text content replacement

Thanks to @dusskapark for contributing the bulk text replacement feature. Here is the demo video.

Instance Override Propagation Another contribution from @dusskapark Propagate component instance overrides from a source instance to multiple target instances with a single command. This feature dramatically reduces repetitive design work when working with component instances that need similar customizations. Check out our demo video.

Manual Setup and Installation

MCP Server: Integration with Cursor

Add the server to your Cursor MCP configuration in ~/.cursor/mcp.json:

json
{
  "mcpServers": {
    "TalkToFigma": {
      "command": "bunx",
      "args": ["cursor-talk-to-figma-mcp@latest"]
    }
  }
}

WebSocket Server

Start the WebSocket server:

bash
bun socket

Figma Plugin

  1. In Figma, go to Plugins > Development > New Plugin
  2. Choose "Link existing plugin"
  3. Select the src/cursor_mcp_plugin/manifest.json file
  4. The plugin should now be available in your Figma development plugins

Windows + WSL Guide

  1. Install bun via powershell
bash
powershell -c "irm bun.sh/install.ps1|iex"
  1. Uncomment the hostname 0.0.0.0 in src/socket.ts
typescript
// uncomment this to allow connections in windows wsl
hostname: "0.0.0.0",
  1. Start the websocket
bash
bun socket

Usage

  1. Start the WebSocket server
  2. Install the MCP server in Cursor
  3. Open Figma and run the Cursor MCP Plugin
  4. Connect the plugin to the WebSocket server by joining a channel using join_channel
  5. Use Cursor to communicate with Figma using the MCP tools

Local Development Setup

To develop, update your mcp config to direct to your local directory.

json
{
  "mcpServers": {
    "TalkToFigma": {
      "command": "bun",
      "args": ["/path-to-repo/src/talk_to_figma_mcp/server.ts"]
    }
  }
}

MCP Tools

The MCP server provides the following tools for interacting with Figma:

Document & Selection

  • get_document_info - Get information about the current Figma document
  • get_selection - Get information about the current selection
  • read_my_design - Get detailed node information about the current selection without parameters
  • get_node_info - Get detailed information about a specific node
  • get_nodes_info - Get detailed information about multiple nodes by providing an array of node IDs
  • set_focus - Set focus on a specific node by selecting it and scrolling viewport to it
  • set_selections - Set selection to multiple nodes and scroll viewport to show them

Annotations

  • get_annotations - Get all annotations in the current document or specific node
  • set_annotation - Create or update an annotation with markdown support
  • set_multiple_annotations - Batch create/update multiple annotations efficiently
  • scan_nodes_by_types - Scan for nodes with specific types (useful for finding annotation targets)

Prototyping & Connections

  • get_reactions - Get all prototype reactions from nodes with visual highlight animation
  • set_default_connector - Set a copied FigJam connector as the default connector style for creating connections (must be set before creating connections)
  • create_connections - Create FigJam connector lines between nodes, based on prototype flows or custom mapping

Creating Elements

  • create_rectangle - Create a new rectangle with position, size, and optional name
  • create_frame - Create a new frame with position, size, and optional name
  • create_text - Create a new text node with customizable font properties

Modifying text content

  • scan_text_nodes - Scan text nodes with intelligent chunking for large designs
  • set_text_content - Set the text content of a single text node
  • set_multiple_text_contents - Batch update multiple text nodes efficiently

Auto Layout & Spacing

  • set_layout_mode - Set the layout mode and wrap behavior of a frame (NONE, HORIZONTAL, VERTICAL)
  • set_padding - Set padding values for an auto-layout frame (top, right, bottom, left)
  • set_axis_align - Set primary and counter axis alignment for auto-layout frames
  • set_layout_sizing - Set horizontal and vertical sizing modes for auto-layout frames (FIXED, HUG, FILL)
  • set_item_spacing - Set distance between children in an auto-layout frame

Styling

  • set_fill_color - Set the fill color of a node (RGBA)
  • set_stroke_color - Set the stroke color and weight of a node
  • set_corner_radius - Set the corner radius of a node with optional per-corner control

Layout & Organization

  • move_node - Move a node to a new position
  • resize_node - Resize a node with new dimensions
  • delete_node - Delete a node
  • delete_multiple_nodes - Delete multiple nodes at once efficiently
  • clone_node - Create a copy of an existing node with optional position offset

Components & Styles

  • get_styles - Get information about local styles
  • get_local_components - Get information about local components
  • create_component_instance - Create an instance of a component
  • get_instance_overrides - Extract override properties from a selected component instance
  • set_instance_overrides - Apply extracted overrides to target instances

Export & Advanced

  • export_node_as_image - Export a node as an image (PNG, JPG, SVG, or PDF) - limited support on image currently returning base64 as text

Connection Management

  • join_channel - Join a specific channel to communicate with Figma

MCP Prompts

The MCP server includes several helper prompts to guide you through complex design tasks:

  • design_strategy - Best practices for working with Figma designs
  • read_design_strategy - Best practices for reading Figma designs
  • text_replacement_strategy - Systematic approach for replacing text in Figma designs
  • annotation_conversion_strategy - Strategy for converting manual annotations to Figma's native annotations
  • swap_overrides_instances - Strategy for transferring overrides between component instances in Figma
  • reaction_to_connector_strategy - Strategy for converting Figma prototype reactions to connector lines using the output of 'get_reactions', and guiding the use 'create_connections' in sequence

Development

Building the Figma Plugin

  1. Navigate to the Figma plugin directory:

    cd src/cursor_mcp_plugin
  2. Edit code.js and ui.html

Best Practices

When working with the Figma MCP:

  1. Always join a channel before sending commands
  2. Get document overview using get_document_info first
  3. Check current selection with get_selection before modifications
  4. Use appropriate creation tools based on needs:
    • create_frame for containers
    • create_rectangle for basic shapes
    • create_text for text elements
  5. Verify changes using get_node_info
  6. Use component instances when possible for consistency
  7. Handle errors appropriately as all commands can throw exceptions
  8. For large designs:
    • Use chunking parameters in scan_text_nodes
    • Monitor progress through WebSocket updates
    • Implement appropriate error handling
  9. For text operations:
    • Use batch operations when possible
    • Consider structural relationships
    • Verify changes with targeted exports
  10. For converting legacy annotations:
    • Scan text nodes to identify numbered markers and descriptions
    • Use scan_nodes_by_types to find UI elements that annotations refer to
    • Match markers with their target elements using path, name, or proximity
    • Categorize annotations appropriately with get_annotations
    • Create native annotations with set_multiple_annotations in batches
    • Verify all annotations are properly linked to their targets
    • Delete legacy annotation nodes after successful conversion
  11. Visualize prototype noodles as FigJam connectors:
  • Use get_reactions to extract prototype flows,
  • set a default connector with set_default_connector,
  • and generate connector lines with create_connections for clear visual flow mapping.

License

MIT

Installation

TypingMind
Prerequisites:

Node.js 18+

{
  "mcpServers": {
    "user-attachments-cursor-talk-to-figma-mcp": {
      "command": "npx",
      "args": [
        "-y",
        "cursor-talk-to-figma-mcp"
      ]
    }
  }
}

Use Cursor Talk to Figma MCP MCP with multiple AI models

TypingMind connects MCP tools at the workspace level, so once Cursor Talk to Figma MCP is connected, you can use it with different AI models in TypingMind instead of setting it up separately for each model. This MCP runs locally through the TypingMind MCP connector on your device.

Setup guide to use the local connector

Use this when the MCP server needs access to local files, apps, or private resources on your computer.

1

Open the MCP settings

In TypingMind, go to Settings, Advanced Settings, then Model Context Protocol and choose Setup Connector.

  1. Open TypingMind in your browser.
  2. Click the Settings icon.
  3. Go to Advanced Settings.
  4. Open the Model Context Protocol section.
  5. Click Setup Connector and choose This Device.
TypingMind MCP connector setup screen with This Device selected
2

Run the connector command

Choose This Device, copy the command from TypingMind, and run it in Terminal. Keep the process running while you use MCP.

  1. Copy the setup command shown by TypingMind.
  2. Open Terminal on macOS or Windows Terminal on Windows.
  3. Paste and run the command.
  4. Approve the package install if Terminal asks you to proceed.
  5. Keep the Terminal window running while using MCP tools.
3

Add Cursor Talk to Figma MCP as a server

When the connector status is Ready, click Edit Servers and paste the MCP server configuration.

  1. Wait until the connector status shows Ready.
  2. Click Edit Servers.
  3. Paste the Cursor Talk to Figma MCP MCP server configuration.
  4. Save the server list.
  5. Refresh if you want to confirm the connector is still ready.
TypingMind MCP settings showing active server and Edit Servers button
{
  "mcpServers": {
    "user-attachments-cursor-talk-to-figma-mcp": {
      "command": "npx",
      "args": [
        "-y",
        "cursor-talk-to-figma-mcp"
      ]
    }
  }
}
4

Use it across models

Save the server list, open Plugins, enable the Cursor Talk to Figma MCP MCP tools, then select any supported AI model in TypingMind and use the tools in chat or assign them to an AI agent.

  1. Open the Plugins page in TypingMind.
  2. Enable the Cursor Talk to Figma MCP MCP tools.
  3. Start a chat and choose the AI model you want to use.
  4. Use the MCP tools in chat or assign them to an AI agent.
  5. Switch to another AI model whenever needed without reconnecting MCP.
TypingMind chat using enabled MCP tools with a selected AI model
Can you use Cursor Talk to Figma MCP to help me with this task?
Cursor Talk to Figma MCP
Sure. I read it.
Here is what I found using Cursor Talk to Figma MCP.

Frequently asked questions

What is the Cursor Talk to Figma MCP MCP server used for?

Cursor Talk to Figma MCP is an MCP server that lets compatible AI clients connect to external tools and context. In TypingMind, you can add this MCP server once and make its tools available in your AI workspace.

Can I use Cursor Talk to Figma MCP MCP with multiple AI models in TypingMind?

Yes. TypingMind connects MCP tools at the workspace level, so you can use Cursor Talk to Figma MCP with different AI models such as Claude, ChatGPT, Gemini, or other models you have configured in TypingMind without setting up the MCP server separately for each model.

Why use Cursor Talk to Figma MCP MCP with TypingMind?

TypingMind is one of the best frontends for LLM chat because it brings multiple AI models, prompts, plugins, AI agents, API keys, and MCP tools into one workspace. With Cursor Talk to Figma MCP connected, you can use its MCP tools across your preferred models while keeping your chat workflow organized in TypingMind.

How do I connect Cursor Talk to Figma MCP MCP to TypingMind?

Cursor Talk to Figma MCP runs through the TypingMind local MCP connector. This is best when the MCP server needs access to local files, desktop apps, command-line tools, or private resources on your computer.

What tools does Cursor Talk to Figma MCP MCP provide in TypingMind?

Cursor Talk to Figma MCP exposes MCP capabilities that can be enabled from the TypingMind Plugins page and used in chat or assigned to AI agents.

Do I need to share my API keys with TypingMind to use Cursor Talk to Figma MCP MCP?

No. TypingMind is local-first and lets you keep your model providers, API keys, prompts, and MCP configuration under your control. If Cursor Talk to Figma MCP requires authentication, add the required headers, OAuth settings, or local configuration for that MCP server when you create the connection.

Related MCP Servers

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇