gRPC as a native transport for MCP

AI agents are moving from test environments to the core of enterprise operations, where they must interact reliably with external tools and systems to execute complex, multi-step goals. The Model Context Protocol (MCP) is the standard that makes this agent to tool communication possible. In fact, just last month we announced the release of fully-managed, remote MCP servers. Developers can now simply point their AI agents or standard MCP clients like Gemini CLI to a globally-consistent and enterprise-ready endpoint for Google and Google Cloud services.

MCP uses JSON-RPC as its standard transport. This brings many benefits as it combines an action-oriented approach with natural language payloads that can be directly relayed by agents in their communication with foundational models. Yet many organizations rely on gRPC, a high-performance, open source implementation of the remote procedure call (RPC) model. Enterprises that have adopted the gRPC framework must adapt their tooling to be ...