The MasterGo Magic MCP server enables AI models to interact with MasterGo design files through:
- Retrieve DSL Data: Extract structured design data using
mcp__getDsl
, including component hierarchy, design properties, and code generation rules by providing file and layer IDs. - Extract Component Documentation: Fetch documentation via
mcp__getComponentLink
using URLs from the componentDocumentLinks array in the DSL data. - Integration with AI Models: Serves as a bridge between AI and MasterGo, enabling design analysis and code generation based on the retrieved data.
- Support for Local Development: Allows developers to build and customize the MCP service for debugging purposes.
Provides the runtime environment required for the MCP server to operate, with no external dependencies needed beyond Node.js.
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
Command Line Options
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
You can also use space-separated format for parameters:
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
cline Usage
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
yarn
andyarn build
to install dependencies and build the code - Find the absolute path of
bin/cli.js
- Add local MCP configuration with your token
- 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
You must be authenticated.
hybrid server
The server is able to function both locally and remotely, depending on the configuration or use case.
A standalone Model Context Protocol service that connects MasterGo design tools with AI models, enabling AI models to directly retrieve DSL data from MasterGo design files.
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