The project aims to build an agentic application that utilizes multiple APIs, teaches users how to use the Agent Connect Protocol (ACP), and evaluates workflows using Galileo. The application will predict weather, provide fashion recommendations, and recommend YouTube videos based on the user's location and preferences. The ACP protocol is used to connect different agents to each other, allowing for seamless integration in multi-agent systems. The project uses a server-based architecture, with endpoints for configuring agents, invoking them with specific inputs, retrieving outputs, and managing agent capabilities and schemas. The Galileo Python SDK is used to monitor the application's performance in real-time, helping developers build confidence in what the agent is doing. The application is built using Python and utilizes various APIs such as OpenAI, OpenWeatherMap, and YouTube. The project demonstrates how to create a composable, evaluatable, ACP-speaking agent that can perform multiple tasks, including weather forecasting, fashion advice, and video recommendation.