MasterGo Design▌
by mastergo-design
Extract design file metadata from MasterGo for analysis or code with ease. Great for web page design programs or convert
Extracts design file metadata from MasterGo files using a personal access token, enabling direct retrieval of design element details for analysis and code generation.
Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.
best for
- / Frontend developers generating code from designs
- / Design teams automating design-to-code workflows
- / AI-powered design analysis and validation
capabilities
- / Extract DSL data from MasterGo design files
- / Retrieve design element metadata
- / Connect MasterGo designs to AI models
- / Analyze design file structure
- / Apply custom design rules
what it does
Extracts design file metadata and DSL data from MasterGo design files using a personal access token. Enables AI models to analyze design elements and generate code from MasterGo projects.
about
MasterGo Design is an official MCP server published by mastergo-design that provides AI assistants with tools and capabilities via the Model Context Protocol. Extract design file metadata from MasterGo for analysis or code with ease. Great for web page design programs or convert It is categorized under developer tools, design.
how to install
You can install MasterGo Design 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
MasterGo Design is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
readme
MasterGo Magic MCP
MasterGo Magic MCP is a standalone MCP (Model Context Protocol) service designed to connect MasterGo design tools with AI models. It enables AI models to directly retrieve DSL data from MasterGo design files.
Key Features
- Retrieves DSL data from MasterGo design files
- Runs directly with npx
- No external dependencies required, only Node.js environment needed
Tutorial
Usage
Obtaining MG_MCP_TOKEN
- Visit https://mastergo.com
- Enter personal settings
- Click the Security Settings tab
- Find the personal access token
- Click to generate the token
Permission Requirements
Important: If the tool is connected but returns a "no permission" error, please check the following conditions:
-
Account Version Requirement:
- Requires Team Edition or higher MasterGo account
- Personal free edition does not support MCP tool access
-
File Location Requirement:
- Design files must be placed in Team Projects
- Files in draft box cannot be accessed via MCP tools
Command Line Options
npx @mastergo/magic-mcp --token=YOUR_TOKEN [--url=API_URL] [--rule=RULE_NAME] [--debug] [--no-rule]
Parameters:
--token=YOUR_TOKEN(required): MasterGo API token for authentication--url=API_URL(optional): API base URL, defaults to http://localhost:3000--rule=RULE_NAME(optional): Add design rules to apply, can be used multiple times--debug(optional): Enable debug mode for detailed error information--no-rule(optional): Disable default rules
You can also use space-separated format for parameters:
npx @mastergo/magic-mcp --token YOUR_TOKEN --url API_URL --rule RULE_NAME --debug
Environment Variables
Alternatively, you can use environment variables instead of command line arguments:
MG_MCP_TOKENorMASTERGO_API_TOKEN: MasterGo API tokenAPI_BASE_URL: API base URLRULES: JSON array of rules (e.g.,'["rule1", "rule2"]')
Installing via Smithery Marketplace
Smithery is an MCP server marketplace that makes it easy to install and manage MCP services.
Method 1: Install via Smithery Website
- Visit Smithery Marketplace
- Click the "Connect" or "Install" button
- Select your MCP client (e.g., Claude Desktop, Cursor, etc.)
- Follow the prompts to complete installation and configuration
LINGMA Usage
Search for LINGMA in the VSCode extension marketplace and install it.
<img src="https://github.com/mastergo-design/mastergo-magic-mcp/blob/main/images/image-20250507174245589.png" alt="image-20250507174245589" style="zoom:25%;" />After logging in, click on [MCP tools] in the chat box.
<img src="https://github.com/mastergo-design/mastergo-magic-mcp/blob/main/images/image-20250507174511910.png" alt="image-20250507174511910" style="zoom:25%;" />Click on [MCP Square] at the top to enter the MCP marketplace, find the MasterGo design collaboration tool and install it.
<img src="https://github.com/mastergo-design/mastergo-magic-mcp/blob/main/images/image-20250507174840456.png" alt="image-20250507174840456" style="zoom:25%;" />After installation, go back to [MCP Servers], and edit our MCP service to replace it with your own MasterGo token.
<img src="https://github.com/mastergo-design/mastergo-magic-mcp/blob/main/images/image-20250507175005364.png" alt="image-20250507175005364" style="zoom:25%;" />Finally, switch the chat mode to agent mode in the chat interface.
<img src="https://github.com/mastergo-design/mastergo-magic-mcp/blob/main/images/image-20250507175107044.png" alt="image-20250507175107044" style="zoom:25%;" />cursor Usage
Cursor Mcp usage guide reference: https://docs.cursor.com/context/model-context-protocol#using-mcp-tools-in-agent
You can configure the MCP server using either command line arguments or environment variables:
Option 1: Using command line arguments
{
"mcpServers": {
"mastergo-magic-mcp": {
"command": "npx",
"args": [
"-y",
"@mastergo/magic-mcp",
"--token=<MG_MCP_TOKEN>",
"--url=https://mastergo.com"
],
"env": {}
}
}
}
Option 2: Using environment variables
{
"mcpServers": {
"mastergo-magic-mcp": {
"command": "npx",
"args": ["-y", "@mastergo/magic-mcp"],
"env": {
"MG_MCP_TOKEN": "<YOUR_TOKEN>",
"API_BASE_URL": "https://mastergo.com"
}
}
}
}
cline Usage
Option 1: Using command line arguments
{
"mcpServers": {
"@master/mastergo-magic-mcp": {
"command": "npx",
"args": [
"-y",
"@mastergo/magic-mcp",
"--token=<MG_MCP_TOKEN>",
"--url=https://mastergo.com"
],
"env": {}
}
}
}
Option 2: Using environment variables
{
"mcpServers": {
"@master/mastergo-magic-mcp": {
"command": "npx",
"args": ["-y", "@mastergo/magic-mcp"],
"env": {
"MG_MCP_TOKEN": "<YOUR_TOKEN>",
"API_BASE_URL": "https://mastergo.com"
}
}
}
}
Project Structure
src Directory
The src directory contains the core implementation of the MasterGo Magic MCP service:
index.ts: Entry point of the application that initializes the MCP server and registers all toolshttp-util.ts: Utility for handling HTTP requests to the MasterGo APItypes.d.ts: TypeScript type definitions for the project
src/tools
Contains implementations of MCP tools:
base-tool.ts: Base class for all MCP toolsget-dsl.ts: Tool for retrieving DSL (Domain Specific Language) data from MasterGo design filesget-component-link.ts: Tool for retrieving component documentation from linksget-meta.ts: Tool for retrieving metadata informationget-component-workflow.ts: Tool providing structured component development workflow for Vue and React components, generating workflow files and component specifications
src/markdown
Contains markdown files with additional documentation:
meta.md: Documentation about metadata structure and usagecomponent-workflow.md: Component development workflow documentation guiding structured component development process
Local Development
- Run
yarnandyarn buildto install dependencies and build the code - Find the absolute path of
dist/index.js - Add local MCP configuration with your token
"mastergo-mcp-local": {
"command": "node",
"args": [
"absolute/path/to/dist/index.js",
"--token=mg_xxxxxx",
"--url=https://mastergo.com",
"--debug"
],
"env": {}
},
- Restart your editor to ensure the local MCP is enabled
After successful execution, you can debug based on the local running results. You can build your own MCP service based on your modifications.
We welcome your code contributions and look forward to building MasterGo's MCP service together.
License
ISC
FAQ
- What is the MasterGo Design MCP server?
- MasterGo Design 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 MasterGo Design?
- This profile displays 25 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.4 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
4.4★★★★★25 reviews- ★★★★★Mei Johnson· Dec 24, 2024
Strong directory entry: MasterGo Design surfaces stars and publisher context so we could sanity-check maintenance before adopting.
- ★★★★★Yash Thakker· Dec 4, 2024
We wired MasterGo Design into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
- ★★★★★Chaitanya Patil· Nov 23, 2024
Strong directory entry: MasterGo Design surfaces stars and publisher context so we could sanity-check maintenance before adopting.
- ★★★★★Li Robinson· Nov 15, 2024
We wired MasterGo Design into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
- ★★★★★Oshnikdeep· Oct 14, 2024
Useful MCP listing: MasterGo Design is the kind of server we cite when onboarding engineers to host + tool permissions.
- ★★★★★Li Menon· Oct 6, 2024
MasterGo Design reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
- ★★★★★Shikha Mishra· Sep 21, 2024
We evaluated MasterGo Design against two servers with overlapping tools; this profile had the clearer scope statement.
- ★★★★★Ava Dixit· Sep 13, 2024
MasterGo Design is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
- ★★★★★Michael Smith· Sep 13, 2024
Strong directory entry: MasterGo Design surfaces stars and publisher context so we could sanity-check maintenance before adopting.
- ★★★★★Sakshi Patil· Aug 12, 2024
I recommend MasterGo Design for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
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