"Google Cloud has announced fully managed remote Model Context Protocol (MCP) servers, enhancing its existing API infrastructure to support MCP and providing a unified layer across all Google and Google Cloud services. With the support for MCP servers, developers can point their AI agents or standard MCP clients, such as the Gemini CLI, to a globally consistent, enterprise-ready endpoint for Google and Google Cloud services."
"The new support is seen as a strong endorsement for MCP ( USB-C for AI) and a significant step toward wide-scale adoption beyond technically savvy users. However, the move has prompted discussion in a Reddit thread about whether "cloud MCP is solving a problem that running trusted MCPs already solves, and better," especially regarding the potential benefits of running trusted MCP code locally with full edge compute access to improve latency."
"To manage and secure MCP capabilities across services, Google introduces the new Cloud API Registry and Apigee API Hub, where developers can find trusted MCP tools from Google and their own organizations. Apigee can convert a standard enterprise API, such as a product catalog, into a discoverable MCP server, allowing organizations to expose their custom business logic to AI agents while maintaining existing governance and security."
Google Cloud announced fully managed remote Model Context Protocol (MCP) servers, expanding API infrastructure to support MCP and create a unified layer across Google and Google Cloud services. Developers can point AI agents or MCP clients like the Gemini CLI to a global, enterprise-ready endpoint. MCP support will roll out incrementally, starting with Google Maps, BigQuery, Google Compute Engine, and Google Kubernetes Engine. The change endorses MCP and aims to broaden adoption, though debates exist about latency and whether remote MCPs replicate HTTP-style remote APIs versus locally run trusted MCPs. Google introduced Cloud API Registry and Apigee API Hub to catalog and secure MCP tools, and Apigee can convert enterprise APIs into discoverable MCP servers that expose business logic to AI agents while preserving governance and security.
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