Figma Pilot
MCP that let AI agents control Figma through code execution
Installation
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Documentation
figma-pilot
AI agents control Figma through code execution.
English | δΈζ
Demo
OpenAI Landing Page
Prompt: "Create an OpenAI style landing page introducing the upcoming GPT 5.3 release on Figma"
Manus Design System
Prompt: "Generate a Manus design system components based on the screenshot, on Figma"
Design Philosophy
This project is inspired by Anthropic's Code execution with MCP approach.
Instead of exposing dozens of individual MCP tools (which bloat the context window and slow down agents), figma-pilot provides only 3 tools:
| Tool | Description |
|---|---|
figma_status | Check connection status |
figma_execute | Execute JavaScript code with full Figma API |
figma_get_api_docs | Get API documentation |
The AI writes code to interact with Figma. This means:
- 90%+ fewer tokens in tool definitions
- Batch operations - modify 100 elements in one call
- Data filtering - filter results before returning to context
- Complex workflows - loops, conditionals, error handling
Quick Start
Prerequisites
- Node.js >= 18
- Figma Desktop app
- An MCP-compatible AI client (Claude Desktop, Claude Code, Cursor, Codex, etc.)
1. Install MCP Server
# Claude Code
claude mcp add figma-pilot -- npx @youware-labs/figma-pilot-mcp
# Other MCP clients - add to your MCP config:
{
"mcpServers": {
"figma-pilot": {
"command": "npx",
"args": ["@youware-labs/figma-pilot-mcp"]
}
}
}
Config locations:
- Claude Desktop:
~/.config/claude/claude_desktop_config.json(macOS/Linux) - Cursor:
~/.cursor/mcp.json
2. Install Skill (Recommended)
The skills/ folder contains API documentation that helps AI agents use figma_execute correctly. Install it to your AI client's skill directory:
| AI Client | Skill Directory |
|---|---|
| Claude Code / Codex | ~/.codex/skills/figma-pilot |
| Cursor | ~/.cursor/skills-cursor/figma-pilot |
| Claude Desktop | ~/.claude/skills/figma-pilot |
After installation, restart your AI client to pick up the new skill.
3. Install Figma Plugin
- Download
figma-pilot-plugin-vX.X.X.zipfrom Releases - Unzip the file
- In Figma: Plugins > Development > Import plugin from manifest...
- Select
manifest.jsonfrom the unzipped folder - Run: Plugins > Development > figma-pilot
4. Verify Connection
Ask your AI agent:
Check the Figma connection status
Usage Examples
Natural Language
Create a card with a title and description
What the AI Generates
Creating a Card:
await figma.create({
type: 'card',
name: 'User Card',
children: [
{ type: 'text', content: 'Card Title', fontSize: 18, fontWeight: 600 },
{ type: 'text', content: 'Description here', fontSize: 14, fill: '#666' }
]
});
Batch Modifying Elements:
const { nodes } = await figma.query({ target: 'selection' });
const rects = nodes.filter(n => n.type === 'RECTANGLE');
for (const rect of rects) {
await figma.modify({ target: rect.id, fill: '#0066FF', cornerRadius: 8 });
}
console.log(`Modified ${rects.length} rectangles`);
Accessibility Check:
const result = await figma.accessibility({
target: 'page',
level: 'AA',
autoFix: true
});
console.log(`Fixed ${result.fixedCount} of ${result.totalIssues} issues`);
API Reference
// Query & Modify
figma.query({ target }) // Query elements
figma.create({ type, ... }) // Create elements
figma.modify({ target, ... }) // Modify elements
figma.delete({ target }) // Delete elements
figma.append({ target, parent }) // Move into container
// Components
figma.listComponents() // List components
figma.instantiate({ component }) // Create instance
figma.toComponent({ target }) // Convert to component
figma.createVariants({ ... }) // Create variants
// Accessibility & Tokens
figma.accessibility({ target }) // WCAG checking
figma.createToken({ ... }) // Create design token
figma.bindToken({ ... }) // Bind token to element
// Export
figma.export({ target, format }) // Export as image
Full documentation: skills/SKILL.md
Architecture
βββββββββββββββ stdio βββββββββββββββββββ HTTP ββββββββββββββββ
β MCP Client β <------------> β MCP Server β <-----------> β Figma Plugin β
β β β (with bridge) β port 38451 β β
βββββββββββββββ βββββββββββββββββββ ββββββββββββββββ
Development
Project Structure
figma-pilot/
βββ packages/
β βββ cli/ # CLI application
β βββ plugin/ # Figma plugin
β βββ mcp-server/ # MCP server (npm package)
β βββ shared/ # Shared TypeScript types
βββ scripts/
β βββ install.sh # Installation script
β βββ package-plugin.sh
βββ skills/ # API documentation for AI agents
Building from Source
git clone https://github.com/youware-labs/figma-pilot.git
cd figma-pilot
bun install && bun run build
Creating a Release
# Build and package
bun run build
./scripts/package-plugin.sh 0.x.x
# Publish to npm
cd packages/mcp-server && npm publish --access public
# Create GitHub release
gh release create v0.x.x dist/releases/figma-pilot-plugin-v0.x.x.zip \
--title "v0.x.x" \
--notes "Release notes here"
Troubleshooting
Plugin Not Connecting
- Ensure MCP server is running (check your AI client's MCP status)
- Plugin should show "Connected" in Figma
- Try reopening the plugin
- Check that port 38451 is not blocked
Port 38451 Already in Use
lsof -i :38451
kill <PID>
MCP Server Not Found
For offline use, install globally:
npm install -g @youware-labs/figma-pilot-mcp
Plugin Error: "ENOENT: no such file or directory, lstat '.../dist/main.js'"
This error means the dist folder is missing from the plugin directory. This can happen if:
- The downloaded zip file was incomplete
- You're using the source code directly without building
Solution:
If you have the source code, build the plugin:
cd packages/plugin
bun install
bun run build
Or build from the project root:
bun run build:plugin
After building, verify that packages/plugin/dist/main.js and packages/plugin/dist/ui.html exist, then import the plugin again in Figma.
License
MIT - YouWare Labs


