Beyond Chat: Building Smart Workflows with Gemini & Model Context Protocol (MCP)
Artificial Intelligence is rapidly evolving beyond simple chat-based applications. Modern AI systems can interact with external tools, files, databases, APIs, cloud platforms, and other services to perform more useful real-world tasks.
Beyond Chat: Building Smart Workflows with Gemini & Model Context Protocol (MCP) is a free live online AI workshop designed to introduce participants to this new generation of AI-powered workflows.
The workshop begins with the fundamentals of modern Large Language Models (LLMs), including context windows, structured outputs, and function calling. Participants will understand how these concepts enable AI models to perform structured tasks and interact with external systems.
The session then introduces practical prompt engineering techniques using Google Gemini and Google AI Studio. Participants will learn how system instructions, clear prompts, context, and examples can improve the reliability and quality of AI-generated responses.
A major focus of the workshop is Model Context Protocol (MCP). Participants will learn what MCP is, why it is becoming important for AI integrations, and how it provides a standardized way for AI applications to communicate with external tools and data sources.
The workshop will explain the fundamental MCP architecture, including MCP Hosts, Clients, and Servers, with easy-to-understand examples.
Participants will also explore Gemini CLI and see how Gemini can be extended beyond conversational AI to interact with development environments, tools, and external resources.
A live demonstration will connect the concepts discussed during the workshop and show how Gemini and MCP can be used to build smarter AI workflows.
This workshop is suitable for students, developers, working professionals, AI enthusiasts, and beginners interested in Generative AI, AI Agents, Agentic AI, Gemini, and Model Context Protocol.
The session is beginner-friendly, while basic familiarity with a computer terminal or command-line interface will be helpful for understanding the practical demonstration.
Topics covered
- Large Language Model (LLM) Fundamentals
- Context Windows in Generative AI
- Structured Outputs
- AI Function Calling
- Prompt Engineering Best Practices
- Google Gemini
- Google AI Studio
- Gemini CLI
- Introduction to Model Context Protocol (MCP)
- MCP Hosts, Clients and Servers
- How MCP Connects AI with External Tools
- AI Tool and Data Integrations
- Real-World AI Workflows
- Gemini and MCP Live Demonstration
- Introduction to Agentic AI Workflows
Workshop benefits
- Understand how modern Generative AI works beyond chat
- Learn practical prompt engineering techniques
- Explore Google Gemini and Google AI Studio
- Understand Gemini CLI and its practical applications
- Learn the fundamentals of Model Context Protocol (MCP)
- Understand MCP Hosts, Clients and Servers
- Learn how AI connects with external tools and data
- Explore real-world AI integration concepts
- Experience a practical Gemini and MCP demonstration
- Build a foundation for AI Agents and Agentic AI