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MasterGo Design

Organization
mastergo-design

MasterGo Magic MCP is a standalone MCP (Model Context Protocol) service designed to connect MasterGo design tools with AI models.

Publishermastergo-design
Repositorymastergo-magic-mcp
LanguageTypeScript
Forks
43
Stars
255
Available tools
0
Transport typestdio
Categories
LicenseMIT
Links
  • Connect tools to AI workflows

    MasterGo Design exposes MCP capabilities that can be used by compatible AI clients and agents.

  • 0 available tools

    Browse the callable actions below, including names and descriptions when provided by the server.

  • Ready-to-copy setup

    Use the installation snippets to configure this server in your preferred MCP client.

  • Open source signals

    255 stars and 43 forks from the linked repository.

MasterGo Magic MCP

Ask DeepWiki

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

  1. Visit https://mastergo.com
  2. Enter personal settings
  3. Click the Security Settings tab
  4. Find the personal access token
  5. Click to generate the token

Permission Requirements

Important: If the tool is connected but returns a "no permission" error, please check the following conditions:

  1. Account Version Requirement:

    • Requires Team Edition or higher MasterGo account
    • Personal free edition does not support MCP tool access
  2. 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_TOKEN or MASTERGO_API_TOKEN: MasterGo API token
  • API_BASE_URL: API base URL
  • RULES: 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

  1. Visit Smithery Marketplace
  2. Click the "Connect" or "Install" button
  3. Select your MCP client (e.g., Claude Desktop, Cursor, etc.)
  4. Follow the prompts to complete installation and configuration

LINGMA Usage

Search for LINGMA in the VSCode extension marketplace and install it.

After logging in, click on [MCP tools] in the chat box.

Click on [MCP Square] at the top to enter the MCP marketplace, find the MasterGo design collaboration tool and install it.

After installation, go back to [MCP Servers], and edit our MCP service to replace it with your own MasterGo token.

Finally, switch the chat mode to agent mode in the chat interface.

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

json
{
  "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

json
{
  "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

json
{
  "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

json
{
  "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 tools
  • http-util.ts: Utility for handling HTTP requests to the MasterGo API
  • types.d.ts: TypeScript type definitions for the project

src/tools

Contains implementations of MCP tools:

  • base-tool.ts: Base class for all MCP tools
  • get-dsl.ts: Tool for retrieving DSL (Domain Specific Language) data from MasterGo design files
  • get-component-link.ts: Tool for retrieving component documentation from links
  • get-meta.ts: Tool for retrieving metadata information
  • get-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 usage
  • component-workflow.md: Component development workflow documentation guiding structured component development process

Local Development

  1. Run yarn and yarn build to install dependencies and build the code
  2. Find the absolute path of dist/index.js
  3. Add local MCP configuration with your token
json
"mastergo-mcp-local": {
  "command": "node",
  "args": [
    "absolute/path/to/dist/index.js",
    "--token=mg_xxxxxx",
    "--url=https://mastergo.com",
    "--debug"
  ],
  "env": {}
},
  1. 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

Installation

TypingMind
Prerequisites:

Node.js 18+

{
  "mcpServers": {
    "mastergo-magic-mcp": {
      "command": "npx",
      "args": [
        "-y",
        "@mastergo/magic-mcp"
      ],
      "env": {
        "MG_MCP_TOKEN": "<YOUR_TOKEN_HERE>",
        "MG_MCP_URL": "https://mastergo.com"
      }
    }
  }
}

Use MasterGo Design MCP with multiple AI models

TypingMind connects MCP tools at the workspace level, so once MasterGo Design is connected, you can use it with different AI models in TypingMind instead of setting it up separately for each model. This MCP runs locally through the TypingMind MCP connector on your device.

Setup guide to use the local connector

Use this when the MCP server needs access to local files, apps, or private resources on your computer.

1

Open the MCP settings

In TypingMind, go to Settings, Advanced Settings, then Model Context Protocol and choose Setup Connector.

  1. Open TypingMind in your browser.
  2. Click the Settings icon.
  3. Go to Advanced Settings.
  4. Open the Model Context Protocol section.
  5. Click Setup Connector and choose This Device.
TypingMind MCP connector setup screen with This Device selected
2

Run the connector command

Choose This Device, copy the command from TypingMind, and run it in Terminal. Keep the process running while you use MCP.

  1. Copy the setup command shown by TypingMind.
  2. Open Terminal on macOS or Windows Terminal on Windows.
  3. Paste and run the command.
  4. Approve the package install if Terminal asks you to proceed.
  5. Keep the Terminal window running while using MCP tools.
3

Add MasterGo Design as a server

When the connector status is Ready, click Edit Servers and paste the MCP server configuration.

  1. Wait until the connector status shows Ready.
  2. Click Edit Servers.
  3. Paste the MasterGo Design MCP server configuration.
  4. Save the server list.
  5. Refresh if you want to confirm the connector is still ready.
TypingMind MCP settings showing active server and Edit Servers button
{
  "mcpServers": {
    "mastergo-design": {
      "command": "npx",
      "args": [
        "-y",
        "@mastergo/magic-mcp"
      ]
    }
  }
}
4

Use it across models

Save the server list, open Plugins, enable the MasterGo Design MCP tools, then select any supported AI model in TypingMind and use the tools in chat or assign them to an AI agent.

  1. Open the Plugins page in TypingMind.
  2. Enable the MasterGo Design MCP tools.
  3. Start a chat and choose the AI model you want to use.
  4. Use the MCP tools in chat or assign them to an AI agent.
  5. Switch to another AI model whenever needed without reconnecting MCP.
TypingMind chat using enabled MCP tools with a selected AI model
Can you use MasterGo Design to help me with this task?
MasterGo Design
Sure. I read it.
Here is what I found using MasterGo Design.

Frequently asked questions

What is the MasterGo Design MCP server used for?

MasterGo Design is an MCP server that lets compatible AI clients connect to external tools and context. In TypingMind, you can add this MCP server once and make its tools available in your AI workspace.

Can I use MasterGo Design MCP with multiple AI models in TypingMind?

Yes. TypingMind connects MCP tools at the workspace level, so you can use MasterGo Design with different AI models such as Claude, ChatGPT, Gemini, or other models you have configured in TypingMind without setting up the MCP server separately for each model.

Why use MasterGo Design MCP with TypingMind?

TypingMind is one of the best frontends for LLM chat because it brings multiple AI models, prompts, plugins, AI agents, API keys, and MCP tools into one workspace. With MasterGo Design connected, you can use its MCP tools across your preferred models while keeping your chat workflow organized in TypingMind.

How do I connect MasterGo Design MCP to TypingMind?

MasterGo Design runs through the TypingMind local MCP connector. This is best when the MCP server needs access to local files, desktop apps, command-line tools, or private resources on your computer.

What tools does MasterGo Design MCP provide in TypingMind?

MasterGo Design exposes MCP capabilities that can be enabled from the TypingMind Plugins page and used in chat or assigned to AI agents.

Do I need to share my API keys with TypingMind to use MasterGo Design MCP?

No. TypingMind is local-first and lets you keep your model providers, API keys, prompts, and MCP configuration under your control. If MasterGo Design requires authentication, add the required headers, OAuth settings, or local configuration for that MCP server when you create the connection.

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