The future of Cloud AI: Mastering MCP servers, Gemini, and agentic workflows

This content covers the future of cloud AI, focusing on mastering Model Context Protocol (MCP) servers, Google Gemini, and agentic workflows. It provides resources including a GitHub repository and a codelab for building ADK (Agent Development Kit) agents with skills and tools. The session explores how to leverage these technologies to create sophisticated AI agents capable of autonomous decision-making and task execution.

Key Points

• •MCP (Model Context Protocol) servers enable standardized communication between AI models and external tools/data sources
• •Google Gemini provides advanced language capabilities for powering intelligent agent reasoning and decision-making
• •ADK (Agent Development Kit) offers a framework for building agents with extensible skills and tools
• •Agentic workflows allow AI systems to autonomously plan, execute, and iterate on complex multi-step tasks
• •Integration of MCP servers with Gemini creates a scalable architecture for enterprise AI applications
• •Skills and tools are modular components that extend agent capabilities beyond base model knowledge
• •Cloud-native deployment enables agents to access real-time data and external services seamlessly
• •Hands-on codelab provides practical implementation patterns for building production-ready agents

Workflow Diagram

Concepts

Artifacts (2)

https://goo.gle/3Pn0Z01

https://goo.gle/4wB4515