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MasterGo Magic MCP

by eDramas
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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

Related MCP server: Framelink Figma MCP Server

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

Command Line Options

npx @mastergo/magic-mcp --token=YOUR_TOKEN [--url=API_URL] [--rule=RULE_NAME] [--debug]

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:

npx @mastergo/magic-mcp --token YOUR_TOKEN --url API_URL --rule RULE_NAME --debug

cursor Usage

Cursor Mcp usage guide reference: https://docs.cursor.com/context/model-context-protocol#using-mcp-tools-in-agent

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

cline Usage

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

License

ISC

Available Tools

2 tools
mcp__getComponentLinkA

When the data returned by mcp__getDsl contains a non-empty componentDocumentLinks array, this tool is used to sequentially retrieve URLs from the componentDocumentLinks array and then obtain component documentation data. The returned document data is used for you to generate frontend code based on components.

ParametersJSON Schema
NameRequiredDescriptionDefault
urlYesComponent documentation link URL, from the componentDocumentLinks property, please ensure the URL is valid

TDQS

A4/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description must disclose all behavioral traits. It mentions sequential retrieval but does not describe side effects, error handling for invalid URLs, or rate limits. This is adequate but not rich.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences, front-loaded with the usage condition, and contains no unnecessary words. Every sentence serves a purpose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (one parameter, no output schema) and lack of annotations, the description adequately covers purpose, usage condition, and parameter source. It could detail return value structure but notes its use for code generation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% and the parameter description in the schema already explains the URL source and validity. The tool description adds little new semantic value beyond restating the source.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool retrieves component documentation data using URLs from the componentDocumentLinks array, distinguishing it from its sibling mcp__getDsl which returns DSL data. The verb 'retrieve' and resource 'component documentation data' are specific.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly specifies the condition for use: when mcp__getDsl returns a non-empty componentDocumentLinks array. It implies sequential retrieval but does not specify when not to use it or mention alternatives beyond the sibling.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

mcp__getDslA

"Use this tool to retrieve the DSL (Domain Specific Language) data from MasterGo design files and the rules you must follow when generating code. This tool is useful when you need to analyze the structure of a design, understand component hierarchy, or extract design properties. You must provide a fileId and layerId to identify the specific design element. This tool returns the raw DSL data in JSON format that you can then parse and analyze. This tool also returns the rules you must follow when generating code. The DSL data can also be used to transform and generate code for different frameworks."

ParametersJSON Schema
NameRequiredDescriptionDefault
fileIdYesMasterGo design file ID (format: file/<fileId> in MasterGo URL)
layerIdYesLayer ID of the specific component or element to retrieve (format: ?layer_id=<layerId> / file=<fileId> in MasterGo URL)

TDQS

A4/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the burden of behavioral disclosure. It states the tool returns DSL data and rules, implying a read-only operation, but does not explicitly confirm no side effects, permissions, or rate limits.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Six sentences, each adding value: purpose, use cases, requirements, return format, additional content, and extensibility. Front-loaded with the main action.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema, the description explains the return value (DSL data in JSON, rules) and mentions transformation use. Could briefly mention expected JSON structure or limitations, but overall sufficient.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with clear descriptions of fileId and layerId. The description only reiterates the requirement to provide both, adding no new meaning beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool retrieves DSL data from MasterGo design files and the rules for code generation, with specific use cases. It distinguishes from sibling tool getComponentLink by focusing on design structure analysis.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides clear context for when to use the tool (analyze structure, hierarchy, properties) but does not explicitly mention when not to use it or compare to the sibling tool.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. 2 tool updatesv0.0.4-beta.3
    • First observedmcp__getComponentLink
    • First observedmcp__getDsl
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TDQS

A3.9/5.0
Disambiguation5/5

The two tools have clearly distinct purposes: one retrieves the overall DSL data and code generation rules, the other retrieves component documentation from links found in the DSL. No overlap or ambiguity.

Naming Consistency5/5

Both tools follow a consistent verb_noun pattern with the 'mcp__' prefix (getDsl, getComponentLink), maintaining naming uniformity.

Tool Count2/5

With only 2 tools, the server feels undersized for a design-to-code workflow. Typically, a design tool MCP would require 3-15 tools to cover essential operations like listing files, managing components, or triggering generation.

Completeness3/5

The tools cover data retrieval (DSL and component documentation) but lack operations for actually generating code, managing files, or updating designs. Notable gaps exist for a complete code generation pipeline.

Maintenance

ActivityInactive
ResponsivenessNo issues

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