Build an AI E-Commerce Agent: MCP, Amazon Bedrock & Claude (Full Tutorial)

The goal of this project is to build a fully autonomous E-Commerce Shopping Agent capable of navigating the live web to find, scrape, and compare products in real-time. By leveraging the Model Context Protocol (MCP), we bridge the gap between LLM reasoning and live data tools, allowing the agent to "see" and "retrieve" the best deals directly from the internet rather than relying on static training data. Core Tech Stack & Tools: MCP (Model Context Protocol): The backbone for connecting our AI agent to external search and scraping tools. Amazon Bedrock: Provides the scalable infrastructure to run high-performance foundation models. Claude: The "brain" of the agent, responsible for reasoning through user requests and evaluating product data. Serper: Used for high-speed Google Search API integration to find product listings. Firecrawl: Enables the agent to crawl and convert web pages into LLM-ready markdown format. Streamlit: Provides a clean, responsive frontend for the user interface. Get the Code - You can find the full codebase and deployment instructions on GitHub here: https://github.com/cloudspeed-channel/mcp-commerce What You Will Learn: How to set up an MCP server to connect multiple tools. Integrating Amazon Bedrock with Claude for agentic workflows. Using Firecrawl and Serper to retrieve live web data. Deploying the final application using Streamlit on AWS. #AI #MCP #AmazonBedrock #Claude3 #CloudEngineering #WebScraping #Python