This course provides a thorough and hands-on introduction to the Model Context Protocol (MCP), an open standard for connecting AI assistants to applications, services, and data in a consistent and reusable way. The course is designed for professional developers who want to build robust AI integrations without relying on brittle, one-off solutions.
During the course, you will learn how MCP works in practice and how to expose your own applications as MCP servers that AI assistants can use directly. You will work with both servers and clients and gain insight into how AI agents can discover and invoke capabilities dynamically. The course covers the full lifecycle from architecture and development to security, debugging, and production deployment, giving you a solid foundation for using MCP in real-world projects.
Course objectivesAfter completing the course, you will:
PrerequisitesParticipants should be professional developers and be comfortable with at least one supported programming language. Basic knowledge of JSON, HTTP-based APIs, and asynchronous programming patterns is expected.
Target audienceThis course is suitable for:
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.
You will gain a clear understanding of what MCP is, why it was created, and the challenges it addresses in today’s AI ecosystem. The course explains how MCP acts as a universal bridge between AI assistants and external systems.
The course explores the MCP architecture, focusing on the interaction between hosts, clients, and servers. You will learn how different transport mechanisms are used in local and remote scenarios and how to choose the right approach for different use cases.
You will work hands-on with building MCP servers that expose functionality to AI assistants. The focus is on defining tools, validating input, and handling errors in a robust and predictable way.
The course demonstrates how files, databases, and APIs can be exposed as resources for AI assistants. You will learn the difference between static and dynamic resources and how to handle change notifications effectively.
You will learn how reusable prompt templates can be used with MCP and when prompts are preferable to tools. The course also covers scenarios where servers initiate requests to language models as part of a workflow.
You will learn how to build MCP clients that connect to one or more servers, discover available tools, and orchestrate complex workflows across multiple services.
The course covers protocol-level logging, debugging strategies for MCP integrations, and how to report progress for long-running operations.
You will learn how authentication and authorization are implemented for remote MCP servers, along with best practices for input validation and securing solutions before production deployment.
The course concludes with integrating MCP servers with developer tools and AI assistants such as VS Code Copilot, and explores integrations with popular development frameworks across languages.
Duration: 3 days
Price: 20.900 kr
Language: English
Format: Can be delivered as an open course or as an in-house course
Hvilke programmeringsspråk kan jeg bruke på kurset?
Du kan velge mellom TypeScript, C#, Python eller Java og Kotlin, og alle konsepter demonstreres på tvers av språk.
Er dette et sertifiseringskurs?
Nei, kurset gir ingen formell sertifisering, men gir solid praktisk kompetanse på MCP.
Hvor praktisk er kurset?
Kurset er workshop-basert med hands-on øvelser, eksempler og komplette løsningsforslag.
Må jeg ha erfaring med AI fra før?
Det er en fordel, men ikke et krav. Kurset forklarer hvordan MCP brukes i AI-kontekst fra grunnen av.
Er innholdet oppdatert på nyeste MCP-spesifikasjon?
Ja, kurset oppdateres fortløpende i takt med endringer i MCP-spesifikasjonen og SDK-ene.
