Google recently released its own managed Model Connector Protocol (MCP) servers. These servers are meant to improve integration of AI agents to Google’s growing suite of products. This launch is a small piece of a larger movement to create standardized AI agent infrastructure. Anthropic is even directly donating MCP to a new Linux Foundation fund dedicated to open-sourcing this technology. The launch of these servers is an exciting new step to help empower developers to build more advanced and efficient AI-driven applications.
The Google Maps MCP server helps AI agents by providing real time location data. This increases their capacity to trip-plan and way-find within spaces confidently. Before this expansion, developers had to lean on the model’s ingrained knowledge too much – knowledge that could be outdated or constrained. This surge in MCP adoption across the agent tooling landscape is indicative of a larger trend. AI needs greater data integration, as the demand outpaces current capabilities.
Google Cloud today introduced these MCP servers in a public preview. They’re still not guaranteed by the boilerplate terms of service just yet. This preview phase provides developers with an opportunity to play around with the technology, while Google continues to dial in its offerings. “We are making Google agent-ready by design,” said Steren Giannini, the product manager at Google Cloud.
Google’s MCP servers provide a powerful incentive by making development easy. They take away the pain of configuring complicated APIs from developers. Instead, developers have a much easier time pasting a URL into a managed endpoint, making it simpler than ever to integrate the tools and data. The first launch will initially grow support service area by service area over the next few months. Stay tuned for more improvements in storage, database, logging & monitoring and security!
Giannini expressed optimism about the future of MCP servers, stating, “I’m looking forward to seeing how many more clients will emerge.” To really bolster the program, he focused on advancing agents’ tools, such as the Google Maps MCP server. Through this new technology, users are provided even more information, including real-time location data, helping them better plan their trip.
To help underpin that infrastructure, Google has implemented strict security and governance controls over the MCP servers. In addition, these servers are protected by Google Cloud Model Armor, a new model-aware firewall for agentic workloads. This dual-layered security approach ensures that developers can deploy their applications with confidence, knowing that data integrity and user privacy are safeguarded.
Apigee, Google’s API management platform, is the beating heart of MCP servers, managing how they work and ensuring that requests are routed and returned properly. And perhaps most importantly, it has the potential to “translate” commonly used, standard APIs into state-approved MCP servers. APIC can gateway and/or transform endpoints from an API of a product catalog. This makes it easy for an AI agent to find and use the tools. This last piece of interoperability is tremendously important. It enables a dynamic marketplace of AI innovations that can leverage real-time data in myriad ways.
With an eye toward what’s to come, Giannini is hoping that increasing numbers of MCP servers will be rolled out weekly. Google is looking to take these services from public preview to general availability early next year. This transition is a clear harbinger of the explosive pace of AI innovation that is coming to its ecosystem.