Advertise
MCP.so
Sign In

Zeplin MCP Server for AI-Assisted UI Implementation

@zeplin

Repository

Basic information

Category

Other

License

MIT

Transports

stdio

Author

zeplin

About Zeplin MCP Server for AI-Assisted UI Implementation

MCP server for Zeplin - used for screen and component code generation 💻

#mcp-server#ui-implementation#zeplin

Zeplin MCP Server for AI-Assisted UI Implementation config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "mcp-server-zeplin": {
      "command": "npx",
      "args": [
        "@zeplin/mcp-server@latest"
      ]
    }
  }
}

Zeplin MCP Server for AI-Assisted UI Implementation tools

4

Fetches detailed design specifications for a specific Zeplin component, including its properties, variants, layers, and associated design tokens. Use this when you need to understand the structure and styling of a single, reusable UI element from Zeplin.

Fetches detailed design data for a specific screen from Zeplin. This includes screen variants, layer information (structure, position, styling), annotations, and project-level design tokens. Use this to understand screen layout, content, and interactions for development or review.

Downloads a specific visual asset (e.g., SVG icon, PNG image) for a given layer from Zeplin and saves it to a local path. Use this tool when an asset referenced in the design (obtained from `get_screen` or `get_component`) is missing from the codebase and needs to be fetched directly from Zeplin.

Download design tokens for a project or styleguide

Overview

What is Zeplin MCP Server for AI-Assisted UI Implementation?

Zeplin MCP Server for AI-Assisted UI Implementation connects AI agents—such as Cursor, Windsurf, and VS Code with GitHub Copilot—to Zeplin design projects. It enables agents to fetch component and screen specs, design annotations, and design tokens (colors, typography, spacing) so they can generate UI code that matches the intended designs.

How to use Zeplin MCP Server for AI-Assisted UI Implementation?

Install the server via NPX (npx @zeplin/mcp-server@latest) and set the ZEPLIN_ACCESS_TOKEN environment variable with your Zeplin personal access token. Configuration is done in your MCP client’s settings (e.g., Cursor or VS Code). One-click installation links are provided for Cursor and VS Code.

Key features of Zeplin MCP Server for AI-Assisted UI Implementation

  • Fetches component and screen specs with detailed layer information
  • Retrieves design annotations for interaction and behavior guidance
  • Provides design tokens (colors, typography, spacing) for reuse
  • Supports limiting context via includeVariants and targetLayerName parameters
  • Works with Cursor, Windsurf, VS Code, and Claude Code

Use cases of Zeplin MCP Server for AI-Assisted UI Implementation

  • Implement UI components or entire screens from Zeplin designs in an AI‑assisted code editor
  • Re-use existing design tokens to maintain visual consistency
  • Build complex screens by implementing individual components first, then assembling them

Frequently asked questions

1

What are the prerequisites for using the server?

Node.js (v20 or later), a Zeplin account, and a Zeplin personal access token generated from your Zeplin profile under Developer → Personal access tokens.

2

How do I provide my Zeplin access token?

Set the environment variable `ZEPLIN_ACCESS_TOKEN` to your personal access token. In MCP client configs (e.g., Cursor), this goes in the `env` object shown in the README.

3

What runtime does the server require?

The server runs on Node.js v20 or later and is executed via `npx`. No additional runtime dependencies beyond Node.js are needed.

4

How can I reduce context usage when fetching large designs?

Use the `includeVariants: false` parameter to fetch only the linked screen version, or use `targetLayerName` to focus on a specific component or layer. An iterative component‑first workflow also keeps each request smaller.

5

What code style does the project follow?

The project uses ESLint with 2‑space indentation, double quotes, semicolons, no trailing spaces, and organized imports. Run `npm run lint:fix` before submitting changes.

Comments

More Other MCP servers

YOUB

Connect your AI assistant to your own YOUB endurance training account. Read recorded activities with full analysis, planned sessions, race goals, wellness (HRV, sleep, resting HR) and your athletic profile. Create or mov

Yuppsy

Yuppsy MCP: build and publish real estate websites from your AI assistant. Yuppsy lets your AI assistant create live websites for real estate agents and individual property listings. You don't need a designer or any code

Handl

Handl speaks the Model Context Protocol. Your whole billing operation — projects, invoices, clients, reports, approvals — as tools any AI assistant can call, inside your autonomy rules.

Blender

ahujasid

Open-source MCP to use Blender with any LLM

23.6K

Lemon.io

lemon-io

Request dedicated senior developers to work on your project, write job descriptions, and prep technical interviews — all without leaving your Claude chat. Just describe what you need, and Lemon.io MCP does the rest. 1–3

Advertise