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@vizejs/musea-mcp-server

v0.166.0

Published

MCP server for building Vue.js design systems - component analysis, documentation, variant generation, and design tokens

Downloads

11,090

Readme

@vizejs/musea-mcp-server

MCP (Model Context Protocol) server for Musea design system integration.

Features

  • AI Integration - Connect Musea to AI assistants
  • Component Discovery - Query available components
  • Design Token Access - Retrieve design system tokens
  • Documentation - Access component docs via MCP

Installation

Install vp once from the Vite+ install guide, then add the server to your project:

vp install -D @vizejs/musea-mcp-server

Usage

With Claude Desktop

Add to claude_desktop_config.json:

{
  "mcpServers": {
    "musea": {
      "command": "vp",
      "args": ["dlx", "@vizejs/musea-mcp-server", "--project", "/path/to/project"]
    }
  }
}

Standalone

vp dlx @vizejs/musea-mcp-server --project ./my-vue-app

MCP Tools

  • analyze_component - Extract props and emits from a Vue SFC or linked art component
  • get_palette - Derive an interactive props palette from an art file
  • list_components - List registered components with status, variants, and resource URIs
  • get_component - Get full component details, analysis, palette, and docs
  • get_variant - Get one specific variant
  • search_components - Search components by title, tags, category, component name, and variants
  • recommend_components - Rank components by user intent or UI task
  • generate_variants - Generate an .art.vue draft from a component
  • generate_csf - Convert an art file to Storybook CSF
  • generate_docs - Generate Markdown docs for a component
  • generate_catalog - Generate a catalog for the whole design system
  • get_tokens - Read design tokens
  • search_tokens - Search tokens without loading the full token tree

Reproducible Prompting

Musea helps AI assistants stay grounded in real component data, but reusable prompts still need to be tuned for reproducibility.

A practical loop is:

  1. Fix a few evaluation scenarios first.
  2. Run the prompt in fresh assistant sessions.
  3. Collect both self-reported ambiguity and tool/checklist traces.
  4. Fix one ambiguity per iteration.

For Musea-specific workflows, check whether the assistant:

  • used real components from the registry
  • matched prop and variant names to MCP output
  • read tokens before suggesting visual values
  • reported missing metadata instead of guessing

The full MCP guide includes a longer reproducibility workflow and prompt template: docs/content/integrations/mcp.md

License

MIT