Google has taken a major leap in supporting the Model Context Protocol (MCP) by launching fully managed remote MCP servers for its core cloud services. To ensure developers have the transparency they need to build production-grade agents, we are excited to announce that status tracking for these servers is now available on MCP Status.
The Shift to Managed Infrastructure
Until now, many developers had to host and manage their own MCP sidecars to connect AI agents to cloud data. This update transforms MCP into a native, unified layer within Google’s API infrastructure.
By pointing any standard MCP client toward Google’s managed endpoints, developers can now grant AI agents direct, secure access to cloud services without the overhead of managing additional infrastructure. This move simplifies the deployment of agentic workflows at an enterprise scale.
What’s Being Tracked?
The first wave of managed support covers four of Google’s most critical powerhouses. You can now monitor the real-time health and uptime of:
- Google Maps: Real-time geospatial data and location intelligence.
- BigQuery: Large-scale data analysis and governed datasets.
- Google Compute Engine (GCE): Direct infrastructure management and VM orchestration.
- Google Kubernetes Engine (GKE): Containerized workload management and cluster insights.
Reliability You Can Monitor
As AI agents move from experimental "sandboxes" to live production environments, uptime is everything. A minor blip in a remote MCP endpoint can break a complex reasoning chain.
Our new dedicated status pages provide live health checks and historical uptime data specifically for these Google-managed endpoints. Whether you are building an agent to query BigQuery or one to manage GKE clusters, you can now verify the stability of your stack in seconds.
Get Started
Transparency is the backbone of the open MCP ecosystem. You can view the current status of all Google Cloud MCP integrations right now on our dashboard:
