Model Context Protocol addresses a critical industry challenge: AI models are typically isolated from live data or business systems, requiring custom integrations for each new tool and MCP solves it for us. But solving this problem introduces new ones: authentication complexity, transport protocol decisions, and the fundamental shift from designing APIs for humans to designing tools for AI agents.
After months of watching AI agents interact with MCP servers, patterns have emerged that weren’t obvious from the specification. This session explores those patterns and their implications for how we design MCP systems in an AI-first world.
Key Takeaways:
Understand the inner workings of MCP and dive deeper into what’s happening behind the scenes of your favorite MCPs
Gain insights from building real-world MCP servers that solve actual problems, not theoretical examples
Learn how to build your own MCPs with proven best practices from hands-on implementation experience
Discover the practical patterns and design decisions that make MCP servers effective for AI agents
Who Should Attend:
Anyone who wants to ride on top of the agentic trend, build MCPs for their specific use cases, explore and identify opportunities to include MCPs in their workflow, or is simply curious to know how MCPs work behind the scenes.
