# Day 1 Lab: Using MCP to build more powerful agents

> In this lab, Zach walks through the MCP lab where he explores building AI agents using LangChain and FastAPI. He covers the necessary Python versions, dependencies like LangChain and Pydantic, and how to set up the environment. Zach demonstrates how to interact with the MCP server, including creati…

- Web page: https://www.dataexpert.io/lesson/building-end-to-end-ai-application-day1-lab-july25-p737-l1188
- Program: [AIExpert](https://www.dataexpert.io/program/ai-expert)
- Module: Week 5: End-to-End AI Applications
- Access: Requires enrollment in AIExpert
- Length: 1 h 5 min video
- Skills: Python, NLP, LLMs, APIs
- Academy: DataExpert.io Academy

## About this lesson

In this lab, Zach walks through the MCP lab where he explores building AI agents using LangChain and FastAPI. He covers the necessary Python versions, dependencies like LangChain and Pydantic, and how to set up the environment. Zach demonstrates how to interact with the MCP server, including creating and managing endpoints, as well as using the GitHub MCP server for various tasks.

## Navigation

- Previous lesson: [Day 1 Lecture: Leveraging MCP and tools to integrate effectively](https://www.dataexpert.io/lesson/building-end-to-end-ai-application-day1-lecture-july25-p737-l1187.md)
- Next lesson: [Day 2 Lecture: How to link your AI agent to value ](https://www.dataexpert.io/lesson/building-end-to-end-ai-application-day2-lecture-july25-p737-l1190.md)