developer-tools

Feuse (Figma Design-to-Code)

panzer-jack

by panzer-jack

Automate your figma to code workflow. Convert Figma designs to HTML, extract SVGs, analyze color, and generate CSS with

Automates Figma design-to-code workflows by extracting design data, downloading SVG assets, analyzing color variables, and generating API models with design token conversion for CSS frameworks like UnoCSS and TailwindCSS.

github stars

39

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Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.

Built-in Figma integrationMultiple CSS framework supportAutomated design-to-code validation

best for

  • / Frontend developers converting Figma designs to code
  • / Design system teams maintaining design tokens
  • / Web developers automating asset extraction workflows

capabilities

  • / Extract design tokens from Figma files
  • / Download SVG and PNG assets automatically
  • / Generate CSS variables for TailwindCSS/UnoCSS
  • / Convert Figma color variables to design tokens
  • / Compare generated code with original designs
  • / Generate TypeScript interfaces from API docs

what it does

Converts Figma designs to code by extracting design tokens, downloading assets, and generating CSS variables for frameworks like TailwindCSS and UnoCSS.

about

Feuse (Figma Design-to-Code) is a community-built MCP server published by panzer-jack that provides AI assistants with tools and capabilities via the Model Context Protocol. Automate your figma to code workflow. Convert Figma designs to HTML, extract SVGs, analyze color, and generate CSS with It is categorized under developer tools.

how to install

You can install Feuse (Figma Design-to-Code) in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.

license

MPL-2.0

Feuse (Figma Design-to-Code) is released under the MPL-2.0 license.

readme

feuse-mcp

Frontend Useful MCP (Model Context Protocol) Tools - Essential utilities for web developers to automate API integration, Figma design-to-code conversion, and development workflow optimization.
license license
English | [中文](README.zh.md) ## 📖 Documentation [feuse-mcp Official Documentation](https://panzer-jack.github.io/feuse-mcp/en) ## ✨ Features - 🎨 **Figma Integration**: Built-in integration with [Figma-Context-MCP](https://github.com/GLips/Figma-Context-MCP/discussions) for seamless Figma design-to-code conversion and automatic asset extraction - 📝 **API Automation**: Generate TypeScript interface types, API URL constants, mock data, and request functions from API documentation - 🖼️ **Asset Management**: Download SVG and PNG images from Figma files with organized file structure - 🎯 **Similarity Comparison**: Compare generated code pages with original Figma prototypes for accuracy validation - 🛠️ **Project Standards**: Generate global specification guidance files for Copilot & Cursor based on current project architecture - 🔧 **Color Variables**: Extract and convert Figma color variables to CSS/design tokens in specified standards (UnoCSS, TailwindCSS, or custom structures) ## 🔧 Available Toolset (Continuously Updated) | Tool Name | Category | Description | Input Parameters | Notes | | ------------------------------- | ------------------ | ---------------------------------------------------------------------- | ------------------------------------ | -------------------------------------------------------------------------------------------- | | **Figma-To-Code** | Figma Integration | Generate frontend code based on Figma styling info with PNG assistance | `fileKey`, `nodeId`(optional) | Auto-adapts to local configs (ESLint etc), supports responsive layouts | | **extract-svg-assets** | Asset Analysis | Analyze Figma DSL structure and auto-extract SVG resources | `fileKey`, `nodeId`(optional) | Intelligent Figma file analysis, batch extraction of SVG icons/vectors | | **extract-color-vars** | Design Tokens | Extract color variables from Figma DSL to CSS framework configs | `fileKey`, `nodeId`(optional) | Supports UnoCSS, TailwindCSS, or custom file format output | | **similarity-figma** | Quality Control | Compare Figma prototypes with project page screenshots | `url`, `fileKey`, `nodeId`(optional) | Visual comparison with intelligent similarity scoring and detailed analysis | | **api-automation** | Development Tools | Parse backend API docs and generate types, constants, mock data | `apiDocs` | Supports multiple API doc formats, generates complete frontend API toolkit | | **initialize-project-standard** | Project Management | Analyze project structure and generate Copilot/Cursor global rules | No parameters | Auto-generates intelligent coding assistant project context and standards | | **Download-Figma-Images** | Asset Management | Batch download SVG and PNG image resources from Figma by node ID | `fileKey`, `nodes[]`, `localPath` | Supports imageRef handling, auto-creates directory structure (low-level tool for other MCPs) | | **download-svg-assets** | Asset Management | Download SVG vector resources from Figma by image/icon node ID | `fileKey`, `nodes[]`, `localPath` | SVG format only, supports complex node structures (low-level tool for other MCPs) | ## 🚀 Quick Start ### Configuration Add to your MCP client configuration: Get your Figma API key from [Figma Developer Settings](https://www.figma.com/developers/api#authentication). ```json { "feuse-mcp": { "command": "npx", "args": ["feuse-mcp@latest"], "env": { "FIGMA_API_KEY": "YOUR_FIGMA_API_KEY" } } } ``` ## 🔧 For Code Contributors ### Setup ```bash # Clone the repository git clone https://github.com/your-username/feuse-mcp.git cd feuse-mcp # Install dependencies pnpm install # Build pnpm build ``` Add to your MCP client configuration: Get your Figma API key from [Figma Developer Settings](https://www.figma.com/developers/api#authentication). ```json { "feuse-mcp": { "command": "npx", // Configure path "args": ["YOUR/PATH/TO/dist/main.cjs"], "env": { "FIGMA_API_KEY": "YOUR_FIGMA_API_KEY" } } } ``` ## 📁 Project Structure ``` feuse-mcp/ ├── src/ │ ├── main.ts # Main entry point │ ├── services/ # Core services │ │ ├── figma/ # Figma integration │ │ ├── similarity/ # Visual comparison │ │ └── utility/ # Utility toolset │ ├── types/ # TypeScript definitions │ └── utils/ # Helper functions ├── docs/ # Documentation └── dist/ # Built files ``` ## 🤝 Contributing Contributions are welcome! Feel free to submit a Pull Request. For major changes, please open an issue first to discuss what you would like to change. ### Development Guidelines 1. Follow the existing code style 2. Update documentation as needed ## 📝 License This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details. **If you have more interesting, fun, and cool ideas, please submit them in issues immediately ! ! !** ## 🙏 Acknowledgments - [Figma-Context-MCP](https://github.com/GLips/Figma-Context-MCP/discussions) for providing Figma design analysis capabilities - [fastmcp](https://github.com/punkpeye/fastmcp) for providing MCP rapid development framework - All contributors and users of this project

FAQ

What is the Feuse (Figma Design-to-Code) MCP server?
Feuse (Figma Design-to-Code) is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
How do MCP servers relate to agent skills?
Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
How are reviews shown for Feuse (Figma Design-to-Code)?
This profile displays 44 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.6 out of 5—verify behavior in your own environment before production use.

Use Cases

Extended AI Capabilities

Add new capabilities to Claude beyond text generation

Example

Access external data sources, execute code, interact with tools and services

Transform Claude from chatbot to action-taking agent

Context Enhancement

Provide Claude with access to relevant context and data

Example

Load project documentation, access knowledge bases, query databases

Get more accurate, context-aware responses

Workflow Automation

Automate multi-step workflows combining AI and external tools

Example

Research → Summarize → Create document → Send notification

Complete complex tasks end-to-end without manual steps

Implementation Guide

Prerequisites

  • Claude Desktop 0.7.0+ or Cursor IDE with MCP support
  • Basic understanding of MCP architecture and capabilities
  • Access credentials for integrated services (if required)
  • Willingness to experiment and iterate on configuration

Time Estimate

15-60 minutes depending on server complexity

Installation Steps

  1. 1.Install MCP server: npm install -g [package-name] or via GitHub
  2. 2.Add server configuration to ~/.claude/mcp.json
  3. 3.Provide required credentials and configuration
  4. 4.Restart Claude Desktop to load new server
  5. 5.Test basic functionality with simple prompts
  6. 6.Explore capabilities and experiment with use cases
  7. 7.Document successful patterns for reuse

Troubleshooting

  • MCP server not loading: Check config syntax, verify installation
  • Connection errors: Check network, firewall, credentials
  • Feature not working: Read server docs, check required parameters
  • Performance issues: Monitor resource usage, check for network latency
  • Conflicts with other servers: Check port assignments, namespace collisions

Best Practices

✓ Do

  • +Read server documentation thoroughly before setup
  • +Start with simple use cases to validate functionality
  • +Test in non-production environment first
  • +Monitor resource usage and performance
  • +Keep servers updated for bug fixes and new features
  • +Document configuration for team members
  • +Use environment variables for sensitive configuration

✗ Don't

  • Don't grant overly permissive access to MCP servers
  • Don't skip reading security considerations in docs
  • Don't expose sensitive data without proper controls
  • Don't run untrusted MCP servers without code review
  • Don't ignore error messages—investigate root cause

💡 Pro Tips

  • Combine multiple MCP servers for powerful workflows
  • Create custom MCP servers for your specific needs
  • Share successful configurations with team
  • Use MCP inspector for debugging
  • Join MCP community for tips and troubleshooting

Technical Details

Architecture

Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.

Protocols

  • Model Context Protocol (MCP)
  • JSON-RPC 2.0
  • stdio or HTTP transport

Compatibility

  • Claude Desktop
  • Cursor IDE
  • Custom MCP clients

When to Use This

✓ Use When

Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.

✗ Avoid When

Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.

Integration

  • Tool composition: Chain multiple MCP tools in workflows
  • Context augmentation: Provide AI with relevant external data
  • Action delegation: Let AI execute tasks on external systems
  • Bidirectional sync: Keep AI context and external systems in sync

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.

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Ratings

4.644 reviews
  • Arjun Park· Dec 20, 2024

    Useful MCP listing: Feuse (Figma Design-to-Code) is the kind of server we cite when onboarding engineers to host + tool permissions.

  • Dhruvi Jain· Dec 12, 2024

    According to our notes, Feuse (Figma Design-to-Code) benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.

  • Pratham Ware· Dec 8, 2024

    We evaluated Feuse (Figma Design-to-Code) against two servers with overlapping tools; this profile had the clearer scope statement.

  • Dev Robinson· Dec 8, 2024

    According to our notes, Feuse (Figma Design-to-Code) benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.

  • Arjun Choi· Dec 4, 2024

    I recommend Feuse (Figma Design-to-Code) for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.

  • Carlos Mensah· Nov 27, 2024

    We wired Feuse (Figma Design-to-Code) into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.

  • Michael Dixit· Nov 23, 2024

    Feuse (Figma Design-to-Code) reduced integration guesswork — categories and install configs on the listing matched the upstream repo.

  • Arya Shah· Nov 11, 2024

    Strong directory entry: Feuse (Figma Design-to-Code) surfaces stars and publisher context so we could sanity-check maintenance before adopting.

  • Aisha Singh· Nov 11, 2024

    We evaluated Feuse (Figma Design-to-Code) against two servers with overlapping tools; this profile had the clearer scope statement.

  • Oshnikdeep· Nov 3, 2024

    We wired Feuse (Figma Design-to-Code) into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.

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