Fashion MCP Server

Fashion vertical MCP server. Connect your AI agent (Claude Code, Cursor, Codex) to specialized fashion tools: product SEO audits, trend analysis, competitor monitoring, and seasonal content generation.

Built by alexgenovese.com — fashion vertical MCP for brands, agencies, and creators.

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Tools

Tool	Description
product_seo_audit	Full SEO audit of a fashion product page: meta title/description, Product JSON-LD schema, image alt text, URL structure, fashion-specific keywords (size, fit, material, color), and seasonal context. Score 0-100 with actionable recommendations.
fashion_trend_analysis	Trend analysis by category (denim, sneakers, bags, dresses). Returns trending keywords, colors with hex codes, silhouette trends, price tier demand, and strategic insights.

Quickstart

npm install
npm run build
node dist/index.js

Use with Claude Code

claude mcp add fashion -- node /path/to/fashion-mcp-server/dist/index.js

Then in chat:

Run a product SEO audit on "Black Leather Jacket" — url: https://mystore.com/products/black-leather-jacket, category: Outerwear, brand: Acne Studios

Use with Cursor

Add to .cursor/mcp.json:

{
  "mcpServers": {
    "fashion": {
      "command": "node",
      "args": ["/path/to/fashion-mcp-server/dist/index.js"]
    }
  }
}

Examples

1. Product SEO Audit for a New Collection

Ask your AI agent:

Audit "Linen Blend Midi Dress" — price: $189, category: Dresses, brand: Mango, material: linen, color: cream. We're launching this for Summer 2025. Check if the title and description are SEO-optimized.

What happens: The tool checks meta title length (30-60 chars), meta description (120-158 chars), product schema completeness, fashion keyword coverage (size, fit, material, color), and seasonal alignment. Returns a score and prioritized fixes.

2. Trend Research for Seasonal Buying

Ask your AI agent:

What denim trends should I stock for this Fall? I run a contemporary denim brand and need to decide between wide-leg, barrel, and skinny fits.

What happens: The trend analysis tool returns trending keywords ("wide leg jeans" ↑, "barrel jeans" rapidly growing), trending colors (Indigo, Stone Wash, Black), silhouette shifts, price tier demand, and strategic insights (e.g., "Barrel/wide leg is the most important denim silhouette shift since 2015").

3. Full Competitive Intelligence Workflow

Ask your AI agent:

I'm launching a sneaker brand. Analyze the current sneaker market trends and audit our first product page for SEO.

What happens: Two tools fire in sequence — first fashion_trend_analysis maps the sneaker market (retro runners rising, chunky peaking, gorpcore growing, price sweet spot $100-200), then product_seo_audit checks your launch page for optimization gaps. Combined output gives you market positioning + page-level fixes.

Configuration

Copy .env.example to .env and configure optional API keys:

Variable	Required	Description
SHOPIFY_STORE	No	Shopify store domain
SHOPIFY_ACCESS_TOKEN	No	Admin API access token
GSC_CLIENT_EMAIL	No	Search Console service account email
GSC_PRIVATE_KEY_PATH	No	Path to JSON private key
GSC_SITE_URL	No	Search Console property URL

Development

npm run dev          # Dev mode with hot reload
npm run typecheck    # Type checking
npm run build        # Production build

Skill Pack (Playbooks)

This repo also includes 12 markdown playbooks in fashion-mcp-skills/skills/ that orchestrate existing MCP servers (Shopify, Meta Ads, GA4, Search Console, etc.) into fashion-specific workflows:

Playbook	What it does
seo-audit-fashion	Full SEO audit for fashion e-commerce
competitor-intelligence	Competitor analysis in 10 minutes
trend-report	Trend research for seasonal collections
ad-copy-fashion	Fashion ad copy generation
full-store-audit	360° fashion store audit
inventory-health-check	Sell-through, stockout risk, markdown alerts
competitor-pricing-audit	Competitor price comparison
seasonal-drop-planner	Seasonal drop planning
email-campaign-fashion	Fashion email campaigns
social-content-calendar	Fashion social content planning
product-launch-checklist	Fashion product launch checklist
brand-visibility-llm	GEO/AI search visibility score

Marketplace

Published on:

• Smithery
• Glama
• Pulse

See docs/MARKETPLACE_DEPLOYMENT.md for deployment instructions.

Structure

src/                           # MCP server (Node/TypeScript)
├── index.ts                   # MCP server entry point
├── types/fashion.ts           # Type definitions
├── tools/
│   ├── index.ts               # Tool registry
│   ├── product-seo-audit.ts   # Product SEO audit
│   └── fashion-trend-analysis.ts  # Trend analysis
└── integrations/
    └── shopify.ts             # Shopify API client
fashion-mcp-skills/            # Skill pack (12 playbook markdowns)
├── skills/                    # 12 playbook .md files
├── docs/                      # MCP directory, architecture
├── README.md
└── CLAUDE.md
docs/                          # Project docs
├── ROADMAP.md                 # Pain-shaped roadmap
├── PAIN-MATRIX.md             # Pain analysis matrix
├── ARCHITECTURE.md            # MCP server architecture
└── MARKETPLACE_DEPLOYMENT.md  # Publishing guide

License

MIT