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Deploy a Secure MCP Server on Cloud Run

A workshop and codelab walking developers through the concepts of agentic AI, the Model Context Protocol (MCP), and how to deploy a secure MCP server on Cloud Run: making it easy to connect AI agents to external tools and databases at scale.


Type
Workshop
Category
AI
Level
Intermediate
Duration
40 mins
Language
English

Events

Name Organizer Date Location Attendees Links
DevFest Bacolod 2025 GDG Bacolod 2025-11-22 University of St. La Salle, Bacolod City, Philippines 109 📊 Slide Deck
mcp model-context-protocol cloud-run ai-agents agentic-ai gemini vertex-ai serverless function-calling security
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Abstract

As AI agents become a core part of how modern software operates, the challenge shifts from building a single capable model to connecting many agents reliably to the external world: databases, APIs, and services. The Model Context Protocol (MCP) addresses this directly: it standardizes how AI agents discover and call tools, reducing the boilerplate of tool-calling code and improving the reliability and reusability of agent integrations.

This workshop starts with the fundamentals of agentic AI: what agents are, how tools and function-calling work, and how the ecosystem has evolved from simple LLM prompts to multi-agent systems. It then introduces MCP: what it is, why it matters, and how Google's open-source MCP Toolbox for Databases fits into the picture. The second half of the workshop dives into Cloud Run as the ideal serverless runtime for hosting MCP servers: covering its architecture, benefits for AI workloads, and design patterns for GenAI apps and agents. The workshop concludes with a live codelab where attendees deploy their own secure MCP server on Cloud Run.

Agenda

  • Agentic AI fundamentals: agents, tools, and how function calling works
  • The integration problem: reliably connecting agents to databases, APIs, and services
  • What is MCP? Protocol overview and why standardization matters
  • Google's MCP Toolbox for Databases: simplifying agent-to-database connections
  • Cloud Run as the ideal serverless runtime for MCP servers
  • Design patterns for GenAI apps and multi-agent systems
  • Codelab: Deploying your own secure MCP server on Cloud Run

Key Takeaways

  • MCP standardizes tool discovery and calling - eliminating custom glue code across every agent project
  • A well-designed MCP server is reusable across multiple agents and use cases simultaneously
  • Cloud Run's serverless model is a natural fit for MCP servers: scalable, secure, and pay-per-use
  • Google's MCP Toolbox removes the hardest part of connecting agents to production databases
  • Security is built into Cloud Run by design - auth, HTTPS, and IAM are handled for you