Build an LLM-powered app that processes invoice files, and extracts fields such as client name, total amount and purchased products, and generates a summary report for each client.
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Instructor: Ben Kus
Build an LLM-powered app that processes invoice files, and extracts fields such as client name, total amount and purchased products, and generates a summary report for each client.
Connect the app to the Box MCP server to access tools such as folder and files listing, and text extraction, to avoid manual downloads and remove custom text extraction.
Orchestrate a three-agent system consisting of files agent, extraction agent and an orchestrator, built using Googleâs ADK and communicating using the A2A (Agent2Agent) protocol.
Join Build AI Apps with MCP servers: Working with Box files, built in partnership with Box, and taught by Ben Kus, its Chief Technology Officer.
Youâll begin with an AI application that processes files manually downloaded from a Box folder and locally stored. Youâll then refactor the application to make it MCP-compliant and connect it to the Box MCP server. The server will provide the application with the required tools to process the files directly in Box. Youâll finally evolve your solution into a multi-agent system that coordinates via the A2A protocol.
MCP or Model Context Protocol standardizes how context, in terms of tools and resources, is provided to LLMs. Instead of writing custom code inside your application for file search, file downloads, and text extraction, you can offload these tasks to an MCP server. An MCP client within your application can communicate with the MCP server to discover the tools and send requests to execute a certain tool. In this course, youâll use the Box MCP server and learn how to connect it to your application to process files from a Box folder. Youâll also build a multi-agent system using Googleâs Agent Development Kit. The agents will use A2A to communicate with each other, and the Box MCP server to access file and text extraction tools.
In detail, youâll:
By the end, youâll know how to build an AI application and AI agents that use the MCP server to process Box content securely, without manual downloads, and that support several file types and scale better with the number of files.
This course is great for AI builders who work with documents and want a practical way to extract fields and build small agent-based workflows. Basic Python knowledge is recommended. No prior MCP, A2A, or Box API experience required.
Introduction
Simple Invoice Processing App
Introduction to Box MCP Server
Processing Invoices Using Box MCP Server
From a Single-Agent to a Multi-Agent Architecture
Processing Invoices Using A Multi-Agent System
Conclusion
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