About the workshop

In this workshop, we’ll move beyond theoretical discussions about AI capabilities and dive into the practical challenge that holds back most production AI systems: context isolation.

You’ll learn why even the most advanced LLMs struggle to deliver real-world value when they can’t access the tools, databases, and systems your organization actually uses. Through hands-on exercises, we’ll build a complete MCP server from scratch, connecting it to AI clients and learning how to give your AI systems the contextual awareness they need to be truly useful. We’ll work with the MCP Inspector to debug and validate our implementations, ensuring you understand not just what to build, but how to troubleshoot when things don’t work as expected.

Key takeawys

By the end of this session, you’ll walk away with practical patterns for building secure, scalable context-aware AI systems that can integrate with your existing infrastructure. You’ll understand how MCP eliminates the complexity of point-to-point integrations (the M×N problem) and provides a standardized approach to tool use and data access.

Whether you’re looking to enhance your current AI implementations or starting fresh with context-aware systems, you’ll leave with working code, debugging strategies, and architectural patterns you can immediately apply in your projects. This is a beginner-friendly workshop, so no prior MCP experience is required, just bring your curiosity and willingness to build.

Building Context-Aware AI with MCP (Model Context Protocol)

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