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Context Engineering with MCP

Published by Pearson

Intermediate content levelIntermediate

From Prompts to Persistent AI Memory with Model Context Protocol (MCP)

Course Outcomes:

  • Master MCP + Azure for persistent AI memory--build the same context systems used by Anthropic and Microsoft in production.
  • Transform your GitHub repos into long-term memory for Claude, Copilot, and ChatGPT.
  • Watch live MCP deployments in Azure, integrated with VS Code for seamless context persistence.
  • Solutions are demonstrated in Azure but apply to all cloud services, including AWS and Google.

You mastered prompting—now stop your AI from forgetting everything. This hands-on course teaches you Context Engineering using MCP—the production-ready protocol adopted by Microsoft and Anthropic. You’ll build persistent AI memory using MCP servers, Azure AI Service, GitHub, and VS Code, eliminating tedious context resets forever.

Leave with working code, templates, and the exact memory patterns the leading companies use today.

What you’ll learn and how you can apply it

  • Deploy MCP servers on Azure, connecting Claude, Copilot, and ChatGPT directly to your GitHub repos and databases.
  • Enable your AI (ChatGPT, Claude, Copilot) to access long-term GitHub memory.
  • Implement enterprise-grade memory systems (episodic, semantic) that scale
  • Design multi-agent workflows leveraging MCP for seamless context sharing across tools.
  • Implement real-world MCP solutions, exactly how Anthropic and Microsoft operate in production today.

This live event is for you because...

  • You're a developer, AI practitioner, or data engineer who already uses ChatGPT, Claude, or GitHub Copilot.
  • You need your AI tools to retain context reliably across sessions and workflows.
  • You're seeking practical, Azure-integrated solutions for context persistence, compatible with your daily VS Code/GitHub workflow.
  • You want to master MCP early to lead adoption in your enterprise.

Prerequisites

  • Active AI tool usage - Current experience with ChatGPT Plus/Team, Claude Pro, or GitHub Copilot
  • GitHub proficiency - Comfortable with repos, commits, and basic Git workflows (we'll use GitHub as context storage)
  • Azure familiarity - Basic understanding of Azure services or willingness to create free account (for deploying MCP servers)

Course Setup

  • GitHub account with ability to create repos and personal access tokens
  • ChatGPT Plus or Team for plugin/action capabilities
  • GitHub Copilot active subscription in VS Code
  • Claude Pro account - Gets MCP features built-in. Available on Windows and Mac.
  • VS Code - Free, available on Windows and Mac
  • Course Repository: github.com/timothywarner-org/context-engineering

Recommended Preparation

Recommended Follow-up

Schedule

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

Segment 1: From Prompts to Persistent Context – Why Your AI Has Amnesia (55 minutes)

  • Live demo: Watch ChatGPT forget, Claude remember - the MCP difference in action
  • The anatomy of context loss: tokens, windows, and why copy-paste isn't sustainable
  • Introduction to MCP: How Anthropic solved this with a universal protocol
  • Your first MCP server: Deploy "hello world" with memory in under 10 minutes
  • Exercise: Map your biggest context frustration to an MCP solution (5 min)
  • Q&A (5 min)

Break (10 minutes)

Segment 2: Building Your Context Stack - GitHub + MCP + Azure (55 minutes)

  • GitHub as long-term memory: repos, gists, and version-controlled context
  • Live coding: MCP server that gives Claude access to your entire GitHub history
  • Deploy to Azure: From local MCP to cloud-scale memory service
  • Connect everything: VS Code → GitHub Copilot → MCP → Azure AI Service
  • Exercise: Modify the MCP server to access your own GitHub repo (5 min)
  • Q&A (5 min)

Break (10 minutes)

Segment 3: Advanced Patterns - Multi-Agent Memory Systems (55 minutes)

  • Memory architectures: Episodic (what happened) vs Semantic (what it means)
  • Vector databases on Azure: When context windows aren't enough
  • Multi-agent orchestration: ChatGPT talks to Claude through shared MCP context
  • Live build: Customer service bot that remembers across channels
  • Exercise: Design memory architecture for your use case (5 min)
  • Q&A (5 min)

Break (10 minutes)

Segment 4: Production Reality - Security, Scale, and What's Next (45 minutes)

  • Authentication and secrets: Keeping your MCP servers secure on Azure
  • Cost optimization: Smart context pruning and caching strategies
  • The future: MCP in Windows, expanding platform support, AGI implications
  • Your toolkit: Take home working MCP servers, patterns, and Azure templates
  • Final Q&A and course wrap-up (10 minutes)

Your Instructor

  • Tim Warner

    Tim Warner has been a Microsoft MVP in Azure AI and Cloud/Datacenter Management for 6 years and a Microsoft Certified Trainer for more than 25 years. His O'Reilly Live Training classes on generative AI, GitHub, DevOps, data engineering, cloud computing, and Microsoft certification reach hundreds of thousands of students around the world. He's written for Microsoft Press, presented at Microsoft Ignite, and contributed to several Microsoft open-source projects. You can connect with Tim on LinkedIn: timw.info/li.

Skill covered

Microsoft Azure