We provide virtual course about Model Context Protocol (MCP) - Multi-language in english. Stop building brittle, one-off integrations. Whether you´re connecting a legacy Java database to Copilot ororchestrating complex C# agents, the Model Context Protocol (MCP) is the universal standard.
Content:
Write your integration once, and let every AI assistant use it. Do you have an existing application, API, or service that you want to make accessible to AI assistants? Add an MCP endpoint and tools like VS Code Copilot, Claude Desktop, or custom AI agents can instantly use your capabilities - without building custom integrations for each one. Are you orchestrating AI agents that need to discover and invoke tools at runtime? Looking for a standardized way to connect your agents to the world? Let's standardize with MCP!
Anthropic created the Model Context Protocol (MCP) as an open standard to solve the fragmentation problem in AI integrations. Since its release in November 2024, MCP has been adopted by Microsoft, JetBrains, and the broader AI ecosystem. It provides a universal way to connect AI assistants to the tools and data they need. This course uses the official MCP SDKs maintained by Anthropic and partners (Microsoft for C#, JetBrains for Kotlin, Spring AI for Java).
What you'll build:
In this course, you'll create MCP servers that expose your functionality to AI assistants, and MCP clients that orchestrate multiple servers. By the end, you'll have a working server connected to VS Code Copilot and understand how to secure it for production use. Students choose their preferred language: TypeScript, C#, Python, or Java/Kotlin. All concepts are demonstrated across languages with complete solutions provided. The course is continuously updated to reflect the latest MCP specification and SDK releases.
Course objectives:
• Expose your applications to AI - Turn any API or service into an MCP server that AI assistants can use
• Build AI applications - Create clients that connect to MCP servers and orchestrate multiple tools
• Understand the protocol - Learn how MCP works under the hood so you can debug and extend it
• Secure your servers - Implement authentication and authorization for production deployments
• Integrate with IDEs - Connect your servers to VS Code Copilot and other AI tools
Course outline:
Module 1 - Introduction to MCP:
• What is MCP and what problems does it solve
• The MCP architecture: Hosts, Clients, and Servers
• Transports: Stdio (local / desktop) vs. SSE (remote / production)
• Hands-on: Explore MCP messages with MCP Inspector
Module 2 - Building Your First Server:
• Setting up your development environment
• Creating tools that AI assistants can call
• Input validation and error handling
• Hands-on: Build a multi-tool utility server
Module 3 - Exposing Data with Resources:
• Making files, databases, and APIs available to AI
• Static and dynamic resources
• Change notifications
• Hands-on: Build a document server
Module 4 - Creating Reusable Prompts:
• Prompt templates with parameters
• When to use prompts vs. tools
Module 5 - Sampling: Server-Initiated LLM Requests:
• Enabling "human in the loop" workflows
• When and how servers can request LLM completions
Module 6 - Building MCP Clients:
• Connecting to MCP servers programmatically
• Discovering and invoking tools
• Working with multiple servers
• Hands-on: Build an interactive MCP client
Module 7 - Logging and Progress:
• Protocol-level logging from your server
• Progress reporting for long operations
Module 8 - Security Architecture:
• Authentication for remote (SSE) servers
• Gateway patterns and token validation
• Input validation and sanitization
• Hands-on: Secure your remote MCP server
Module 9 - IDE and Agent Integration:
• Connecting servers to VS Code Copilot
• Testing and debugging workflows
• Microsoft Semantic Kernel integration (C#/Python)
• IntelliJ integration (Java/Kotlin)
• Hands-on: Connect your server to VS Code Copilot
Appendix
Module 10 - Appendix A: Debugging MCP Servers:
• Using MCP Inspector for troubleshooting
• Common issues and solutions
• IDE debugging techniques
Module 11 - Appendix B: Testing MCP Servers:
• Unit and integration testing strategies
• Language-specific testing frameworks
• Contract testing for JSON-RPC
Instructor: Rick Beerendonk
Rick Beerendonk have 30+ years software development experience, senior consultant at Oblicum, Microsoft MVP. Has trained thousands of developers across Europe in .NET, modern web development, API design, and software architecture.
Target audience:
This course is suitable for:
• Developers working with AI integrations
• Software developers building APIs and platform services
• Architects looking for a standardized way to connect AI to systems
• Technologists working with agent-based and AI-driven solutions
Prerequisites:
• Professional developers familiar with at least one supported language (TypeScript, C#, Python, Java, or Kotlin) and comfortable with JSON, HTTP APIs, and basic asynchronous programming patterns.
Language:
• English course documentation, english speaking instructor
Course material:
The course fee includes digital course documentation and hands-on labs