Welcome to our immersive AI technology workshop series. During these sessions you will be introduced to new and established AI tools that will help you create and manipulate content in new and powerful ways. Each session is led by an industry expert who will guide you through the material and share its real-world implications.

Learning Outcomes 
By the end of the workshop, participants will be able to:

• Explain the core principles and motivations behind the Model Context Protocol (MCP), including its role in AI Agentic system communication and AI model integration.
• Identify the structure and components of an MCP message and understand how context is preserved and passed across tasks or AI agents.
• Implement simple MCP interactions in a controlled setting using real-world tools and libraries.
• Evaluate the strengths and limitations of MCP in current AI Agentic system architectures, including scalability and interoperability.

Topics Include

• MCP Basics: What is Model Context Protocol and why does it matter in AI pipelines and agent interoperability?
• Message Anatomy: Structure, metadata, tokens, and temporal context.
• Live Demo: Walking through an MCP message lifecycle-create, modify, pass, and interpret.
• Hands-On Lab: Building a mini MCP-based interaction (e.g., agent-to-agent communication or contextual memory pass).
• Challenges & Use Cases: Real-world applications, common pitfalls, and current limitations.

Prerequisites: Knowledge of LLM and AI Agents.

Note: Please bring a laptop and have Google, GitHub and Hugging Face accounts to participate in hands-on exercises.