Welcome to the complete Model Context Protocol (MCP) course! This course will take you from basic concepts to building sophisticated AI agent integrations and understanding the future of AI-human collaboration.
- What is MCP?
- Why MCP matters
- Setting up your development environment
- Your first MCP server
- Understanding the protocol
- Core MCP concepts
- Server and client architecture
- Basic tool definitions
- Resource management
- Error handling
- Custom tool development
- Resource providers
- Prompt templates
- Streaming responses
- Authentication and security
- Building functional MCP servers
- Tool implementation strategies
- Basic configuration management
- Error handling patterns
- Testing your servers
- MCP client development
- Tool discovery and usage
- Resource consumption
- Error handling
- Performance optimization
- Database integrations
- API integrations
- File system operations
- Web scraping tools
- Custom business logic
- Progressive projects
- Real-world implementations
- Best practices
- Project deployment
- Production-ready server architectures
- Advanced server features and middleware
- Docker and Kubernetes deployment
- Monitoring and logging systems
- Security best practices
- Performance optimization
Each module has a pre-configured container environment:
# Build all containers
cd containers && ./build-all.sh
# Run a specific module container
podman run -it --rm -v $(pwd):/workspace mcp-course-module4- Read each module in order - The course is designed to be progressive
- Practice each example - Run all code examples and understand them
- Build the projects - Hands-on experience is crucial
- Experiment - Don't be afraid to try variations and build your own tools
- Join the community - Connect with other MCP developers
- Basic programming knowledge (Python, JavaScript, or similar)
- Understanding of APIs and JSON
- Familiarity with command line/terminal
- Basic knowledge of AI/LLM concepts
- Willingness to learn 😊
Upon completing this course, you will be able to:
- ✅ Understand MCP architecture and concepts
- ✅ Build custom MCP servers
- ✅ Integrate MCP clients with AI applications
- ✅ Create powerful AI tools and resources
- ✅ Deploy MCP solutions in production
- ✅ Apply MCP best practices
- ✅ Contribute to the MCP ecosystem
👉 Go to Module 1: Introduction to MCP
- START-HERE.md - Complete start guide with study plans
- QUICK-GUIDE.md - MCP syntax and command cheat sheet
- ADDITIONAL-RESOURCES.md - Links, documentation, community
The examples/ directory contains reference projects and exercise templates:
- File Manager MCP Server (
examples/01-file-manager/) - Database Query Tool (
examples/02-database-tool/) - Web Scraping Service (
examples/03-web-scraper/) - Business Tools Server (
examples/04-business-tools/) - Complete production example
- Module 4 Exercises (
examples/module4-exercises/) - Templates for hands-on practice - Task Management Server - Template for building task management tools
- Calculator Server - Template for advanced calculator implementation
- File Manager Server - Template for file system operations
Remember that practice is the key to learning! Don't hesitate to experiment and build innovative AI tools.
# Install MCP SDK (Python)
pip install mcp
# Install MCP SDK (Node.js)
npm install @modelcontextprotocol/sdk
# Run an MCP server
python server.py
# Test MCP client connection
mcp-client connect server.py- MCP Specification: Official protocol documentation
- MCP GitHub: Source code and examples
- Community Discord: Real-time help and discussions
- MCP Registry: Discover existing servers and tools
Course created with ❤️ for aspiring MCP developers