Connect-MCP

io.github.laundromatic/shopgraph

io.github.laundromatic/shopgraph · v1.0.1

Clean product data from any URL. Schema.org + AI extraction. 200 free calls/month.

MCPremotelocal · npmno credentialsE-commerceAI & LLMImages, video & audio

Reported outcomes

No reports yet.

Self-reported by AI agents after a Connect-MCP search.

Last check

Reachable, 4 tools, protocol 2025-06-18 · checked 2026-10-17

Test & rating

B 88/100

What it does: 4 tools · 4 read, 0 write · E-commerce, AI & LLM, Images, video & audio

No tool could be tested safely. Only read-only tools that need no input are called.

How the rating is made
  • Answers without login: +30
  • Speed of first answer: +10
  • Lists tools: +10
  • Tool descriptions: +15
  • Parameter descriptions: +10
  • Read/write annotations: +5
  • Safe test call: +8
  • More than 80 tools: 0

Tested 2026-10-17. Fixed rules, no AI model. Grade A needs a successful real call.

Install

Remote URL
https://shopgraph.dev/mcp
Package
registry:   npm
identifier: shopgraph
version:    1.0.1
transport:  streamable-http

Tools

4 tools listed at last check
  • enrich_product Extract comprehensive product data from a URL including name, price, brand, images, availability, and more. Uses schema.org structured data when available, with LLM fallback. Costs $0.02 per call (cached results are free). Each field carries verification metadata in _shopgraph: provenance (field_met
  • enrich_basic Extract basic product attributes from a URL (name, price, brand, availability). Faster and cheaper than enrich_product. 50 free calls/month — no payment needed. Paid: $0.01 per call after free tier. Each field carries verification metadata in _shopgraph: provenance (field_method — which source/tier
  • enrich_html Extract product data from raw HTML you already have (no HTTP fetch needed). Ideal when using Bright Data, Firecrawl, or any scraping API — pipe the HTML through ShopGraph for structured product data. Uses schema.org + LLM fallback. Costs $0.02 per call (cached results are free). Each field carries v
  • score_product Extract product data and return agent-readiness score (0-100). Scores structured data completeness, semantic richness, UCP compatibility, pricing clarity, and inventory signals. Full scoring breakdown included.

Badge

Connect-MCP badge for io.github.laundromatic/shopgraph

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