About
Palette converts Figma designs into production-ready React or Vue components using the Delicious Design System. It maps visual designs directly to the organization's existing component library rather than generating generic code. Key features of Palette: - Converts Figma designs to React or Vue code using `@dealicious/design-system-react` and `@dealicious/design-system` component libraries - Maps designs to specific components including Button, Input, Check, Switch, Dropdown, Text, Tag, Chip, Badge, Toast, Tab, Pagination, Accordion, and LayerPopup - Analyzes Figma file structures and extracts design specifications - Lists available design system components to ensure code consistency - Restricted to dealicious-inc organization members
README
Palette MCP
Figma 디자인을 기존 Design System 컴포넌트를 활용하여 React/Vue 코드로 변환하는 MCP(Model Context Protocol) 서버입니다.
[](https://smithery.ai/server/@anthropic/palette-mcp) [](https://www.npmjs.com/package/@anthropic/palette-mcp) [](https://opensource.org/licenses/MIT)
🚀 빠른 시작
Smithery.ai에서 설치 (권장)
1. Smithery.ai에서 palette-mcp 검색
2. "Install" 클릭
3. 환경 변수 입력:
- FIGMA_ACCESS_TOKEN: Figma API 토큰 (필수)
- GITHUB_TOKEN: GitHub 토큰 (필수, 조직 인증 및 디자인 시스템 접근용)
Cursor에서 수동 설치
~/.cursor/mcp.json 파일에 다음 추가:
{
"mcpServers": {
"palette": {
"type": "stdio",
"command": "npx",
"args": ["-y", "palette-mcp"],
"env": {
"FIGMA_ACCESS_TOKEN": "YOUR_FIGMA_TOKEN_HERE",
"GITHUB_TOKEN": "YOUR_GITHUB_TOKEN_HERE"
}
}
}
}
환경 변수
| 변수명 | 필수 | 설명 |
|--------|------|------|
| FIGMA_ACCESS_TOKEN | ✅ | Figma Personal Access Token |
| GITHUB_TOKEN | ✅ | GitHub 토큰 (dealicious-inc 조직 인증 및 디자인 시스템 접근용) |
| FIGMA_MCP_SERVER_URL | ❌ | Figma MCP 서버 URL (기본값: http://127.0.0.1:3845/mcp) |
> ⚠️ 참고: GITHUB_TOKEN은 dealicious-inc 조직 멤버십 확인에 사용됩니다. 조직 멤버만 Palette MCP를 사용할 수 있습니다.
#### Figma Access Token 발급: 1. Figma → Settings → Account 2. Personal Access Tokens → Generate new token
---
📖 사용법
Cursor에서 사용
Figma에서 디자인을 선택하고 "Copy link to selection"으로 URL을 복사한 후:
https://www.figma.com/design/akI7EwlWemAf8KJup9F2ZS/...?node-id=45733-32370
를 React 코드로 작성해줘
지원하는 명령
| 명령 | 설명 |
|------|------|
| convert_figma_to_react | Figma 디자인을 React 컴포넌트로 변환 |
| convert_figma_to_vue | Figma 디자인을 Vue 컴포넌트로 변환 |
| list_design_system_components | 사용 가능한 디자인 시스템 컴포넌트 목록 |
| analyze_figma_file | Figma 파일 구조 분석 |
---
🎨 지원하는 Design System 컴포넌트
React Components (@dealicious/design-system-react)
| 카테고리 | 컴포넌트 | |----------|----------| | Actions | Button, TextLink | | Forms | Input, Check, Radio, Switch, Dropdown, TextField | | Data Display | Text, Tag, Chip, Badge, LabeledText | | Feedback | Toast, Notice, Error, LoadingSpinner, Tooltip | | Navigation | Tab, Pagination, ArrowPagination, Accordion | | Overlays | LayerPopup, LayerAlert |
Vue Components (@dealicious/design-system)
| 카테고리 | 컴포넌트 | |----------|----------| | Actions | SsmButton, SsmTextLink | | Forms | SsmInput, SsmCheck, SsmSwitch, SsmDropdown | | Data Display | SsmText, SsmTag, SsmChip, SsmBadge | | Navigation | SsmTab, SsmPagination, SsmAccordion |
---
🔧 로컬 개발
설치
git clone https://github.com/Opti-kjh/palette.git
cd palette
yarn install
환경 설정
cp .env.example .env
.env 파일에 FIGMA_ACCESS_TOKEN 추가
빌드 및 실행
# 빌드
yarn build개발 모드
yarn devMCP 서버 실행
yarn mcp
테스트
# MCP Inspector로 테스트
npx @anthropic-ai/mcp-inspector ./dist/index.js
---
📁 프로젝트 구조
src/
├── index.ts # MCP 서버 메인 파일
├── services/
│ ├── figma.ts # Figma API 연동
│ ├── design-system.ts # 디자인 시스템 메타데이터
│ └── code-generator.ts # React/Vue 코드 생성
└── utils/
├── figma-mcp-client.ts # Figma MCP 클라이언트
└── request-manager.ts # 요청 관리
---
⚠️ 중요: 디자인 시스템 사용 원칙
이 MCP 서버는 항상 디자인 시스템 컴포넌트를 사용합니다.
---
🤝 기여
이슈 및 PR은 GitHub에서 환영합니다.
📄 라이선스
MIT License - LICENSE 참조
Related MCP Servers
AI Research Assistant
hamid-vakilzadeh
AI Research Assistant provides comprehensive access to millions of academic papers through the Semantic Scholar and arXiv databases. This MCP server enables AI coding assistants to perform intelligent literature searches, citation network analysis, and paper content extraction without requiring an API key. Key features include: - Advanced paper search with multi-filter support by year ranges, citation thresholds, field of study, and publication type - Title matching with confidence scoring for finding specific papers - Batch operations supporting up to 500 papers per request - Citation analysis and network exploration for understanding research relationships - Full-text PDF extraction from arXiv and Wiley open-access content (Wiley TDM token required for institutional access) - Rate limits of 100 requests per 5 minutes with options to request higher limits through Semantic Scholar
Linkup
LinkupPlatform
Linkup is a real-time web search and content extraction service that enables AI assistants to search the web and retrieve information from trusted sources. It provides source-backed answers with citations, making it ideal for fact-checking, news gathering, and research tasks. Key features of Linkup: - Real-time web search using natural language queries to find current information, news, and data - Page fetching to extract and read content from any webpage URL - Search depth modes: Standard for direct-answer queries and Deep for complex research across multiple sources - Source-backed results with citations and context from relevant, trustworthy websites - JavaScript rendering support for accessing dynamic content on JavaScript-heavy pages
Math-MCP
EthanHenrickson
Math-MCP is a computation server that enables Large Language Models (LLMs) to perform accurate numerical calculations through the Model Context Protocol. It provides precise mathematical operations via a simple API to overcome LLM limitations in arithmetic and statistical reasoning. Key features of Math-MCP: - Basic arithmetic operations: addition, subtraction, multiplication, division, modulo, and bulk summation - Statistical analysis functions: mean, median, mode, minimum, and maximum calculations - Rounding utilities: floor, ceiling, and nearest integer rounding - Trigonometric functions: sine, cosine, tangent, and their inverses with degrees and radians conversion support