Figma to React Native▌
by kailashappdev
Easily convert Figma designs to code. Extract components from Figma files, generate hierarchies & metadata for smooth Fi
Extracts and analyzes components from Figma design files, enabling seamless integration between Figma designs and React Native development through component hierarchy processing and metadata generation.
Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.
best for
- / React Native developers converting designs to code
- / Teams bridging design-to-development workflow
- / Rapid prototyping from Figma mockups
capabilities
- / Extract components from Figma files
- / Generate React Native components with TypeScript
- / Maintain component hierarchy from designs
- / Handle component props and nested structures
- / Create organized component folders
what it does
Extracts components from Figma design files and automatically generates corresponding React Native components with proper typing and styling.
about
Figma to React Native is a community-built MCP server published by kailashappdev that provides AI assistants with tools and capabilities via the Model Context Protocol. Easily convert Figma designs to code. Extract components from Figma files, generate hierarchies & metadata for smooth Fi It is categorized under developer tools, design.
how to install
You can install Figma to React Native 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
MIT
Figma to React Native is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
readme
Figma to React Native MCP
Convert Figma designs to React Native components using Cursor's MCP. This tool extracts components from your Figma designs and generates corresponding React Native components with proper typing and styling.
Installation
For Development
Add to your eas.json:
{
"mcpServers": {
"figma-to-code": {
"command": "node",
"args": ["PATH_TO_REPO/build/index.js"],
"env": {
"FIGMA_TOKEN": "your_figma_token",
"FIGMA_FILE": "your_figma_file_id",
"PROJECT_DIR": "your_project_directory"
}
}
}
}
For End Users
Install the MCP server in your Cursor IDE:
npx -y @smithery/cli@latest install @kailashg101/mcp-figma-to-code --client claude --config "{
"figmaToken": "YOUR_FIGMA_TOKEN",
"figmaFile": "YOUR_FIGMA_FILE_ID",
"projectDir": "YOUR_PROJECT_DIRECTORY"
}"
Usage
After installation, you can use the following prompts in Cursor:
Extract All Components
using the extract_components mcp tool get all components from figma and generate their corresponding react native components in components folder
Extract Specific Component
using the extract_components mcp tool get the [ComponentName] component from figma and generate its corresponding react native component in components folder
Configuration
The config object accepts the following parameters:
{
"figmaToken": string, // Your Figma access token
"figmaFile": string, // Your Figma file ID (from the URL)
"projectDir": string // Where to generate the components
}
Features
Current:
- ✅ Extract components from Figma
- ✅ Generate React Native components
- ✅ Maintain component hierarchy
- ✅ Handle component props and types
- ✅ Support nested components
Coming Soon:
- 🚧 GraphQL schema generation
Development
To contribute or modify:
- Clone the repository
- Install dependencies:
npm install
- Build:
npm run build
- Run locally:
npm start
Environment Variables
When running locally, you'll need these in your .env:
FIGMA_TOKEN=your_figma_token
FIGMA_FILE=your_figma_file_id
PROJECT_DIR=your_project_directory
Error Handling
Common errors and solutions:
- "Failed to create client": Check if all environment variables are properly set
- "Components page not found": Ensure your Figma file has a page named "Components"
- "Failed to fetch Figma file": Verify your Figma token and file ID
License
MIT
For issues and feature requests, please open an issue on GitHub.
FAQ
- What is the Figma to React Native MCP server?
- Figma to React Native 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 Figma to React Native?
- This profile displays 28 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.5 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.Install MCP server: npm install -g [package-name] or via GitHub
- 2.Add server configuration to ~/.claude/mcp.json
- 3.Provide required credentials and configuration
- 4.Restart Claude Desktop to load new server
- 5.Test basic functionality with simple prompts
- 6.Explore capabilities and experiment with use cases
- 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
4.5★★★★★28 reviews- ★★★★★Daniel Tandon· Dec 24, 2024
Figma to React Native is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
- ★★★★★Amina Verma· Dec 12, 2024
According to our notes, Figma to React Native benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
- ★★★★★Isabella Kapoor· Nov 15, 2024
Figma to React Native reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
- ★★★★★Amina Menon· Nov 3, 2024
Figma to React Native has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
- ★★★★★Amina Iyer· Oct 22, 2024
We evaluated Figma to React Native against two servers with overlapping tools; this profile had the clearer scope statement.
- ★★★★★Harper Wang· Oct 6, 2024
I recommend Figma to React Native for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
- ★★★★★Piyush G· Sep 25, 2024
Figma to React Native is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
- ★★★★★Kofi Malhotra· Sep 13, 2024
According to our notes, Figma to React Native benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
- ★★★★★Oshnikdeep· Sep 1, 2024
We evaluated Figma to React Native against two servers with overlapping tools; this profile had the clearer scope statement.
- ★★★★★Li Rahman· Sep 1, 2024
Figma to React Native is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
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