Welcome to the training hub for mastering Context Engineering with Model Context Protocol (MCP). Whether you're building AI applications or deepening your understanding of persistent AI memory, this guide provides everything you need to implement production-ready context systems.
New to this course? Start here:
- Student Setup Guide - Prepare your environment before class (30-60 min)
- Validate Environment - Run
node scripts/validate-environment.jsto check your setup - Troubleshooting FAQ - Quick fixes for common issues
- Hands-On Labs - Progressive exercises from beginner to advanced
- Post-Course Resources - Continue learning after the training
During class: Keep the Troubleshooting FAQ open for quick reference.
context-engineering/
│
├── instructor/ # Instructor materials
│ ├── course-plan.md # Full course plan
│ ├── DEMO_SCRIPT.md # Complete demo walkthrough
│ ├── RUNBOOK.md # Execution procedures
│ └── *.pptx # Presentation deck
│
├── student/ # Student materials
│ ├── STUDENT_SETUP_GUIDE.md # Pre-course setup
│ ├── TROUBLESHOOTING_FAQ.md # Common issues & fixes
│ └── POST_COURSE_RESOURCES.md # After-class learning
│
├── reference/ # Reference documentation
│ ├── IMPLEMENTATION_GUIDE.md # Choose the right pattern
│ ├── MCP_TUTORIALS.md # MCP tutorials & guides
│ ├── CONFIG_GUIDE.md # Configuration reference
│ └── POPULAR_REMOTE_MCP_SERVERS.md
│
├── mcp-servers/ # MCP server implementations
│ ├── coretext-mcp/ # Main teaching example (JavaScript)
│ ├── stoic-mcp/ # TypeScript production example
│ ├── context_journal_mcp_local/ # Python implementation
│ ├── context_journal_mcp_azure/ # Azure deployment
│ └── deepseek-context-demo/ # DeepSeek integration
│
├── labs/ # Hands-on exercises
│ └── lab-01-hello-mcp/ # Your first MCP server
│
├── examples/ # Reference implementations
│ └── filesystem-mcp/ # File operations server
│
├── diagrams/ # Architecture diagrams
├── images/ # Course images
├── scripts/ # Utility scripts
├── config/ # Sample configuration files
└── docs/ # Internal documentation
Level: Intermediate Duration: 2-4 hours (flexible format) Format: Hands-on live training
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.
By the end of this course, you will have:
- Built a working MCP server that gives AI access to your GitHub repositories
- Deployed production MCP infrastructure to Azure with authentication and monitoring
- Implemented multi-agent memory systems that persist across sessions
- Configured Claude Desktop, VS Code Copilot, and ChatGPT with persistent context
- MCP Specification - Official protocol specification
- MCP Documentation - Protocol overview
- MCP TypeScript SDK - Official SDK
- Official MCP Servers - Production-ready servers
- Claude MCP Documentation - Claude integration guide
AI Platform Access
- Claude Desktop (Windows/Mac) - Native MCP support
- VS Code with GitHub Copilot
Development Environment
- Node.js 20 LTS or Python 3.10+
- Git
- Azure CLI (for deployment labs)
MCP Development Tools
# Install MCP Inspector globally
npm install -g @modelcontextprotocol/inspector
# Install TypeScript SDK
npm install @modelcontextprotocol/sdkMicrosoft MVP - Azure AI and Cloud/Datacenter Management (6+ years) Microsoft Certified Trainer (25+ years)
- Website: techtrainertim.com
- LinkedIn: linkedin.com/in/timothywarner
- YouTube: youtube.com/timothywarner
- Bluesky: @techtrainertim.bsky.social
© 2025 Timothy Warner. Course materials provided for educational purposes.
Model Context Protocol is an open standard - free to implement in commercial and open-source projects.
Found an issue or have a suggestion? Open an issue or submit a pull request.