# Figma MCP Server - Project Overview
## Introduction
The Figma MCP Server is a Model Context Protocol (MCP) implementation that provides a bridge between AI assistants and the Figma API. This allows AI systems to interact with Figma files, components, and other resources through a standardized protocol, enabling rich integrations and automations with Figma designs.
## Purpose
This project aims to:
1. Provide AI assistants with the ability to access and manipulate Figma files
2. Enable structured access to Figma resources through the MCP protocol
3. Bridge the gap between design tools and AI systems
4. Support design workflows with AI-assisted operations
## Core Features
- **File Access**: Retrieve Figma files and inspect their contents
- **Node Operations**: Access specific nodes within Figma files
- **Comment Management**: Read and write comments on Figma files
- **Image Export**: Export nodes as images in various formats
- **Search Capabilities**: Search for text and elements within files
- **Component Access**: View and work with Figma components
- **Version History**: Access file version history
## Technology Stack
- **TypeScript**: Type-safe implementation
- **Bun**: JavaScript/TypeScript runtime and package manager
- **MCP SDK**: Model Context Protocol implementation
- **Figma REST API**: Official Figma API with TypeScript definitions
- **Zod**: Schema validation for parameters and configurations
## Project Structure
```
/figma
├── dist/ # Compiled output
├── docs/ # Documentation
├── src/
│ ├── config/ # Configuration files
│ ├── services/ # API and external service integrations
│ └── utils/ # Utility functions
├── types/ # Type definitions
├── .env # Environment variables
├── Makefile # Build and run commands
├── README.md # Project README
├── package.json # Dependencies and scripts
└── tsconfig.json # TypeScript configuration
```
## Integration with AI Systems
This MCP server enables AI assistants to:
1. Retrieve design information from Figma
2. Answer questions about design files
3. Generate images and assets from Figma files
4. Add comments and feedback to designs
5. Search for specific elements or text within designs
6. Track version history and changes
With these capabilities, AI systems can provide more contextual and helpful responses when users ask about their Figma designs, streamlining the design workflow and enhancing collaboration between designers and stakeholders.
