The era of isolated LLMs is over. To become truly productive, modern AI agents must securely access real-time data and execute actions on external systems. This 1-hour session provides a complete guide to building and deploying this advanced pattern: connecting an ADK Agent to external capabilities via the MCP Server, all running on the highly scalable and serverless platform, Google Cloud Run.
We'll take you through the entire lifecycle, from setting up the environment to containerizing both the ADK Agent (the client) and the MCP Server (the tool provider). You'll learn how to leverage MCP to standardize how your agent requests external tools and data, transforming it from a simple chatbot into a powerful, action-taking entity.
Key Takeaways
Attendees will walk away with the practical ability to:
- Understand the MCP Architecture: Grasp the roles of the ADK Agent (client) and the MCP Server (tool/context provider) in enabling agentic AI.
- Containerize for Serverless: Prepare and containerize complex, multi-component systems (the ADK Agent and MCP Server) for deployment on Cloud Run.
- Ensure Secure Communication: Configure service-to-service communication on Cloud Run, ensuring the ADK Agent securely connects to the MCP Server.
- Implement Serverless Scaling: Utilize Cloud Run's autoscaling to handle variable load on your agent architecture, minimizing idle costs while ensuring high availability.
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