AI agents are being sold as the solution for planning trips, answering business questions, and solving problems of all kinds, but getting them to work with tools and data outside their chat interfaces has been tricky. Developers have to patch together various connectors and keep them running, but that’s a fragile approach that’s hard to scale and creates governance headaches.
Google claims it’s trying to solve that by launching its own fully managed, remote MCP servers that would make its Google and Cloud services — like Maps and BigQuery — easier for agents to plug into.
The move follows the launch of Google’s latest Gemini 3 model, and the company is looking to pair stronger reasoning with more dependable connections to real-world tools and data.
“We are making Google agent-ready by design,” Steren Giannini, product management director at Google Cloud, told TechCrunch.
Instead of spending a week or two setting up connectors, developers can now essentially paste in a URL to a managed endpoint, Giannini said.
At launch, Google is starting with MCP servers for Maps, BigQuery, Compute Engine, and Kubernetes Engine. In practice, this might look like an analytics assistant querying BigQuery directly, or an ops agent interacting with infrastructure services.
In the case of Maps, Giannini said, without the MCP, developers would rely on the model’s built-in knowledge. “But by giving your agent […] a tool like the Google Maps MCP server, then it gets grounded on actual, up-to-date location information for places or trips planning,” he added.
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While the MCP servers will eventually be offered across all of Google’s tools, they are initially launching under public preview, meaning they’re not yet fully covered by Google Cloud terms of service. They are, however, being offered to enterprise customers that already pay for Google services at no extra cost.
“We expect to bring them to general availability very soon in the new year,” Giannini said, adding that he expects more MCP servers to trickle in every week.
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