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Building AI Agents with Model Context Protocol (MCP)

Published by O'Reilly Media, Inc.

Intermediate content levelIntermediate

Connecting LLMs to real-world data through standardized interfaces

Course outcomes

  • Create simple agents that can leverage tools powered by MCP
  • Build fully functional MCP servers that connect LLMs to external data sources and tools
  • Design and implement AI workflows that use MCP to provide context-aware responses
  • Create agents with OpenAI Agents SDK that can use MCP tools to perform tasks

Course description

The Model Context Protocol (MCP) is an open protocol that standardizes how AI applications connect to data sources and tools. Think of it as a USB-C port for AI—a universal connector that lets large language models seamlessly integrate with external systems.

Join expert Lucas Soares to learn how to build MCP servers that expose tools, resources, and prompts to LLMs like Claude. You’ll explore how to create AI workflows that leverage external context and tools through MCP, enabling more powerful and context-aware AI assistants. Through practical examples, you’ll build agents that can leverage MCP servers for file systems and have the ability to leverage APIs using the OpenAI Agents SDK. By the end of the course, you’ll have the skills to build sophisticated AI-augmented workflows that connect LLMs to the data and tools they need to be truly useful.

What you’ll learn and how you can apply it

  • Design and implement composable agent architectures using MCP
  • Understand the MCP architecture and how it enables AI applications to access external context
  • Build MCP servers that expose tools, resources, and prompts to LLMs

This live event is for you because...

  • You’re a software engineer, AI engineer, data scientist, or technical product manager.
  • You work with large language models and AI-powered applications.
  • You want to build AI workflows that connect LLMs to real-world data and tools.

Prerequisites

  • A computer with Python 3.10+ and the MCP SDK installed (optionally, Node.js for JavaScript examples)
  • Access to Claude API (free tier sufficient) for testing MCP integrations, or access to Claude Desktop
  • Basic Python or JavaScript programming experience
  • Familiarity with REST APIs and web services
  • Understanding of basic LLM concepts
  • No prior experience with MCP required

Recommended preparation:

Recommended follow-up:

Schedule

The time frames are only estimates and may vary according to how the class is progressing.

Introduction to Agents & MCP (40 minutes)

  • Presentation: Agent Basics
  • Hands-on: Introduction to agents from scratch
  • Presentation: Where does MCP fit into the Agentic picture?
  • Demo: Examples of Agents with MCP (Claude Code)

Introduction to MCP for Agent Builders (30 minutes)

  • Presentation: Introduction to MCP architecture and core concepts—tools, resources, prompts; MCP clients versus servers; the MCP ecosystem
  • Presentation: MCP concepts for building Agents—clients versus servers; capabilities (tools, resources, prompts); schemas and validation; local dev workflow
  • Q&A

Break

MCP Quickstart: Build Your First Server(50 minutes)

  • Presentation: Setting up the dev environment; MCP SDK project skeleton; defining a minimal tool and prompt; running and inspecting requests/responses
  • Hands-on exercise: Create a simple “Utilities” MCP server and a starter prompt
  • Demo: Use your MCP server with pre-built tools (Claude Code, Cursor)
  • Q&A

Break

Setup & First Working Agent with OpenAI Agents SDK (60 minutes)

  • Presentation: Dev setup in Python—install openai-agents and MCP Python SDK; run a ready-made MCP server (Filesystem) via stdio; attach it to an agent with MCPServerStdio; list tools and run the agent loop.
  • Hands-on exercise: Build a “File Reader” agent that uses the MCP Filesystem server to read and summarize local files end-to-end.
  • Q&A

Break

Building an Automation Agent with OpenAI Agents SDK + MCP (60 minutes)

  • Presentation: Automating automations with agents + MCP + google sheets + OpenAI Agents SDK
  • Hands-on: Building a real-world example of an agent that automates setting up automation scripts from a google sheets table entry.
  • Q&A

Break

MCP Hacks & Tips for Devs (60 minutes)

  • Hands-on: MCP for everything using Claude Code! Hacks and tips for a centralized dashboard hub with Claude Code + MCP
  • Q&A

Your Instructor

  • Lucas Soares

    Lucas Soares is a machine learning engineer who has worked at K1 Digital and Biometrid, where he developed computer vision and NLP models for applications such as document verification, OCR-based applications, and recommender systems. Lucas has also developed various ML models, including neural networks, Siamese networks, convolutional neural networks, LSTMs, and genetic algorithms.

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Skills covered

  • AI Agents
  • MLOps