MCP Servers

ShopGraph

Structured product data from the open web — where platform APIs don't reach. Schema.org + AI extraction. Pay per call via Stripe MPP.

README

@laundromatic/shopgraph

MCP server for product data enrichment with Stripe MPP (Machine Payments Protocol) payment gating.

What it does

Agents connect via Model Context Protocol and call enrichment tools to extract structured product data from URLs. Requests are payment-gated via Stripe: unauthenticated calls receive a 402 challenge, authenticated calls with a payment_method_id are processed and billed.

Architecture

Agent → MCP (stdio) → enrich_product / enrich_basic
  → Cache hit? Return immediately (free)
  → No payment_method_id? Return 402 + MPP challenge
  → Payment confirmed → schema.org extraction (fast, 0.95 confidence)
  → No structured data? → Gemini LLM fallback (0.6-0.8 confidence)
  → Return ProductData + PaymentReceipt

Setup

npm install

Required environment variables in .env:

Variable	Purpose
`STRIPE_TEST_SECRET_KEY`	Stripe test mode secret key
`GOOGLE_API_KEY`	Gemini API key for LLM fallback

Note: Check .env for duplicate key definitions — dotenv uses the last occurrence.

Build & Run

npm run build          # Compile TypeScript
npm start              # Run MCP server (stdio transport)
npm run dev            # Run with tsx (no build needed)

Test

npm run test:run       # Run all tests once
npm test               # Run tests in watch mode

Tools

Tool	Price	Description
`enrich_product`	$0.02	Full product data extraction
`enrich_basic`	$0.01	Basic attributes only (no images)

Cached results are returned free of charge (24-hour TTL).

MCP Configuration

Add to your MCP client config:

{
  "mcpServers": {
    "shopgraph": {
      "command": "node",
      "args": ["/path/to/shopgraph/dist/index.js"]
    }
  }
}

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