How to build production-ready AI agents with Google-managed MCP servers

As ​​developers build AI agents with more sophisticated reasoning systems, they require higher-quality fuel–in the form of enterprise data and specialized tools–to drive real business value. To get the most out of that octane-rich mix, we offer Google-managed model context protocol (MCP) servers:  an engine purpose-built for AI agents to interact securely with Google and Google Cloud services.

These Google-hosted, fully-managed endpoints allow AI agents to communicate with Google Maps, BigQuery, Google Kubernetes Engine, Cloud Run, and many other Google services. As we boldly build AI agents, ensuring that we’re also building responsibly is critical.

In this guide, we demonstrate how to build agents securely on our managed MCP servers.

Why you should use Google-managed MCP servers

Transitioning from local experimentation to enterprise-grade AI requires adopting a robust, managed infrastructure that prioritizes scale and oversight. These are the key benefits that we offer: 

• Production readiness: While open-source ...