Fetches real-time Google Shopping data for brands, including product prices and ratings, to support brand comparison.
Uses Hugging Face-hosted LLMs to generate structured AI comparisons and explanations of brand value, price, and ratings.
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An AI-powered brand comparison application built using the Model Context Protocol (MCP).
The application fetches real-time shopping data for two brands using SerpAPI, calculates price and rating statistics, determines value for money, and uses an LLM hosted through Hugging Face to generate a structured comparison.
π Real-time Google Shopping data
π·οΈ Compare two different brands
π Supports multiple product categories:
Shoes
Watches
Bags
Clothing
π° Average price calculation
β Average rating calculation
π Product-level Value Score
π Brand-level value comparison
π€ AI-generated comparison and explanation
π MCP-based client-server architecture
π Streamlit user interface
β οΈ Error handling for missing data and API failures
π API keys stored securely using environment variables
Related MCP server: Amazon Product Search MCP
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βββββββββββββββββββββββThe application allows users to select two brands and a product category, then retrieves real-time shopping data for comparison.
The application calculates average price, average rating, and Value Score, then provides an AI-generated comparison and displays the retrieved products.
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Product search for AI shopping agents: prices and buy links from big retailers. No key needed.
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The E-commerce Marketplace For Every AI Agent. A Governed Catalog Of 600M+ US Products, Plus Four Agent Ready Capabilities Search, Price Comparison, Product-Vs-Product, And Detailed Q&A.
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