In our last webinar, we uncovered why traditional architectures are failing in the age of AI. Now, we turn to what comes next.
Join us for a technical deep dive into the Model Context Protocol (MCP)—the emerging standard enabling LLMs to securely connect to data, tools, and real-time systems.
Traditional application architecture consisting of monoliths, brittle APIs, and hard-coded pipelines is struggling to meet the dynamic reasoning requirements of agentic AI. This session provides a concentrated technical walkthrough of the Model Context Protocol (MCP), the emerging standard for connecting LLMs to secure data sources.
Following a technical breakdown of the MCP "handshake" mechanics, we will explore the Client-Server architecture, JSON-RPC foundation, and transport layers. Through live demonstrations and architectural analysis, we move from the concept of "glue code" to a functional, plug-and-play ecosystem.
Join us to see how MCP is being implemented to create modern autonomous agents and real-time data integration.
In this session, you will:
- Demystify MCP Architecture: Evaluate the technical pillars of the protocol: Client-Server roles, JSON-RPC foundations, and transport layers.
- Map the Protocol Flow: Trace the Request-Response lifecycle to see exactly how tools and resources are dynamically discovered and invoked by a model.
- Debug with Developer Tools: Utilize the MCP Inspector to monitor server health, validate tool discovery, and troubleshoot connection issues.
- Review an MCP server that transforms a standard API call into a tool-ready resource for an agentic application.
Live event date: Tuesday, June 9, 2026 | 1:00 PM ET
On-demand event: Available for one year afterward
Presenters:
Bob Kozdemba
Principal Specialist Solution Architect, Red Hat
Bob Kozdemba is a Principal Specialist Solution Architect at Red Hat who helps customers and business partners build best of breed application developer solutions on enterprise platforms. He has a long standing career working with open source technologies including Linux, Kubernetes, programming languages and AI/ML frameworks. Bob holds an M.S. in Computer and Information Science and an M.B.A from the University of Maryland.
Chád Darby
Principal Specialist Solutions Architect, Red Hat
Chád Darby is a Principal Specialist Solutions Architect at Red Hat who partners with executive stakeholders to address the governance, data privacy, and compliance challenges of enterprise AI. A veteran of the industry with 30 years of experience, he provides the strategic and technical leadership necessary to build reliable, enterprise-grade AI systems on modern cloud platforms. Chád holds a B.S. in Computer Science from Carnegie Mellon University.
Chris Kang
Principal Specialist Solution Architect, Red Hat
Chris Kang is a Principal Specialist Solution Architect at Red Hat. His focus is helping customers build AI solutions using open source technologies. Prior to Red Hat, Chris worked with Fortune 500 companies to implement cloud native architectures using cloud computing, container platforms, data analytics, and AI/ML. Chris is a passionate learner and driven by customer success. He has a B.S. in Electrical Engineering from Northwestern University and a M.S. in Computer Science from The University of Chicago.
