Zendesign MCP Server
An MCP server that allows Cursor users to fetch real-time information about Zendesign design system components.
README
Zendesign MCP Server
Setup and Installation
Prerequisites
- Python 3.8+
- uv package manager
Installation
- Clone or download this repository
- Install dependencies using uv:
uv sync
Running the Server
To start the MCP server:
uv run python server.py
The server will start on port 9000 using Server-Sent Events (SSE) transport.
You should see output indicating the server is running:
FastMCP server running on port 9000
Adding to Cursor
To use this MCP server with Cursor, you need to configure it in your Cursor settings:
Method 1: Via Cursor Settings UI
- Open Cursor
- Go to Cursor Settings (⌘+, on Mac or Ctrl+, on Windows/Linux)
- Navigate to Features → Beta → Model Context Protocol
- Add a new MCP server with the following configuration:
- Name:
Zendesign - Command:
uv - Arguments:
["run", "python", "server.py"] - Working Directory:
/path/to/your/zd-mcp(replace with your actual project path)
- Name:
Method 2: Via Configuration File
Add the following to your Cursor MCP configuration file:
{
"mcpServers": {
"zendesign": {
"command": "uv",
"args": ["run", "python", "server.py"],
"cwd": "/path/to/your/zd-mcp"
}
}
}
Note: Replace /path/to/your/zd-mcp with the actual absolute path to your project directory.
Verification
After adding the server to Cursor:
- Restart Cursor
- The Zendesign MCP server should appear in your available tools
- You can now ask Cursor questions about Zendesign components, and it will use the MCP server to fetch real-time information
Example Usage in Cursor
Once configured, you can interact with the Zendesign design system through Cursor:
- "Show me the button component from Zendesign"
- "What are the styling options for the card component?"
- "Get the design system guidelines from Zendesign"
Troubleshooting
Server Won't Start
- Ensure all dependencies are installed:
uv sync - Check that port 9000 is not in use by another application
- Verify Python version compatibility
Cursor Can't Connect
- Ensure the server is running before starting Cursor
- Verify the working directory path is correct in your MCP configuration
- Check Cursor's MCP logs for connection errors
Component Not Found
- Verify the component name is correct (e.g., 'button', 'card', 'input')
- Check that the Zendesign API is accessible from your network
Development
This server uses:
- FastMCP: For MCP protocol implementation
- requests: For HTTP API calls to Zendesign
- asyncio: For asynchronous operations
To modify or extend the server, edit server.py and restart the server for changes to take effect.
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.