MasterGo Magic MCP Server

What does “MasterGo Magic” MCP Server do?

MasterGo Magic MCP is a standalone Model Context Protocol (MCP) service designed to connect MasterGo design tools with AI models. It enables seamless integration by allowing AI models to directly retrieve DSL (Domain-Specific Language) data from MasterGo design files. By bridging the gap between design assets and AI-powered workflows, MasterGo Magic MCP enhances the development and automation of design-related tasks, such as analyzing, transforming, or generating design components. The server runs independently with minimal setup, requiring only a Node.js environment and no external dependencies, making it a streamlined solution for teams aiming to supercharge their design-to-AI pipelines.

List of Prompts

No prompt templates are documented in the provided repository.

List of Resources

No explicit MCP resources are described in the available files.

List of Tools

No explicit tools are documented in server.py or elsewhere in the repository files accessible via the provided link.

Use Cases of this MCP Server

• Automated Design Analysis: AI models can retrieve DSL data from MasterGo design files, enabling automated inspection or quality checks of design assets without manual download or preprocessing.
• Design Collaboration: By exposing design data via MCP, teams can build workflows where AI assists with design reviews, suggestions, or documentation directly from source files.
• AI-powered Design Generation: Integrate with generative AI to propose new design elements or variations based on current project files accessed through the MCP server.
• Rule-based Design Validation: Use MCP to apply custom design rules (via the --rule parameter) for automated enforcement of organizational or project-specific standards during the design process.

How to set it up

Windsurf

1. Ensure Node.js is installed on your system.
2. Obtain your MasterGo API token via your MasterGo personal security settings.
3. Open Windsurf’s configuration file.
4. Add the MasterGo Magic MCP server using the following JSON snippet in your mcpServers section:

   {
     "mastergo-magic": {
       "command": "npx",
       "args": ["@mastergo/magic-mcp@latest", "--token", "${MG_MCP_TOKEN}"]
     }
   }
   

5. Save your changes and restart Windsurf to activate the server.

Note: Secure your API token by placing it in your environment variables:

{
  "env": {
    "MG_MCP_TOKEN": "<your-token-here>"
  }
}

Claude

1. Install Node.js if not already present.
2. Retrieve your MasterGo API token.
3. Locate Claude’s configuration for MCP servers.
4. Insert the following configuration:

   {
     "mcpServers": {
       "mastergo-magic": {
         "command": "npx",
         "args": ["@mastergo/magic-mcp@latest", "--token", "${MG_MCP_TOKEN}"]
       }
     }
   }
   

5. Save and restart Claude.

Note: Store your token in an environment variable (MG_MCP_TOKEN) for security.

Cursor

1. Install Node.js environment.
2. Generate your personal MasterGo access token.
3. Open Cursor’s MCP server configuration.
4. Add this configuration:

   {
     "mcpServers": {
       "mastergo-magic": {
         "command": "npx",
         "args": ["@mastergo/magic-mcp@latest", "--token", "${MG_MCP_TOKEN}"]
       }
     }
   }
   

5. Save and restart Cursor.

Note: Use environment variables for sensitive information:

{
  "env": {
    "MG_MCP_TOKEN": "<your-token-here>"
  }
}

Cline

1. Verify Node.js is installed.
2. Obtain a MasterGo API token from your MasterGo account.
3. In Cline’s configuration file, add:

   {
     "mcpServers": {
       "mastergo-magic": {
         "command": "npx",
         "args": ["@mastergo/magic-mcp@latest", "--token", "${MG_MCP_TOKEN}"]
       }
     }
   }
   

4. Save the file and restart Cline.
5. Confirm the server is accessible and responding.

Note: Always configure your token as an environment variable.

How to use this MCP inside flows

Using MCP in FlowHunt

To integrate MCP servers into your FlowHunt workflow, start by adding the MCP component to your flow and connecting it to your AI agent:

Click on the MCP component to open the configuration panel. In the system MCP configuration section, insert your MCP server details using this JSON format:

{
  "mastergo-magic": {
    "transport": "streamable_http",
    "url": "https://yourmcpserver.example/pathtothemcp/url"
  }
}

Once configured, the AI agent is now able to use this MCP as a tool with access to all its functions and capabilities. Remember to change “mastergo-magic” to whatever the actual name of your MCP server is and replace the URL with your own MCP server URL.

Overview

Based on the above, MasterGo Magic MCP provides a clear overview and setup instructions, but lacks documentation on resources, prompt templates, and tools, which are crucial for full MCP integration. Sampling and roots support are also not indicated. This limits its score for out-of-the-box MCP ecosystem compatibility.

MCP Score