Shopgraph

Name: Shopgraph
Author: laundromatic

bylaundromatic

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Ciencia de Datos y ML

Web Scraping y Recopilación de Datos

Soluciones de Comercio Electrónico

Provides structured product data extraction from any URL, serving AI agents and integrating Stripe Machine Payments Protocol for secure transactions.

Shopgraph functions as a Model Context Protocol (MCP) server designed for enriching product data. It allows AI agents to connect and utilize specialized tools to extract structured product information from various URLs. Requests are payment-gated through Stripe's Machine Payments Protocol, ensuring that only authenticated and paid calls are processed, while unauthenticated calls receive a 402 challenge. The architecture prioritizes efficiency with a 24-hour cache for free results, employs schema.org extraction for high confidence data, and falls back to a Gemini LLM for unstructured cases, returning comprehensive product data and a payment receipt.

Características Principales

010 GitHub stars

02Combines schema.org extraction with Gemini LLM fallback for robust data retrieval

03Free caching for previously enriched results with a 24-hour TTL

04Stripe Machine Payments Protocol (MPP) payment gating

05Offers distinct tools for full product data (`enrich_product`) or basic attributes (`enrich_basic`)

06Structured product data extraction from any URL

Casos de Uso

01Empowering AI agents with accurate and structured product information

02Integrating paid, on-demand data extraction services into MCP client applications

03Automating product data gathering and enrichment for e-commerce or research