Grpc MCP Gateway, from Machanirobotics, acts as a definition and framework for an MCP server/gateway. It defines its functionality using Protocol Buffers as a set of annotations. This platform allows existing gRPC services to be exposed as Model Context Protocol servers, enabling integration with AI agent and Large Language Model workflows. Its design is language-agnostic, supporting gRPC code generation across many languages. Distributed as a Buf module, it helps developers bridge traditional microservices with emerging AI ecosystems.

What does Grpc MCP Gateway connect to?

Grpc MCP Gateway connects to existing gRPC services, enabling their exposure as Model Context Protocol (MCP) servers. MCP is an open protocol that standardizes how AI applications provide context to Large Language Models (LLMs) and interact with external tools. This gateway acts as a definition or framework for an MCP server/gateway, allowing gRPC services to be invoked directly by AI models. It supports models like Claude, Codex, and Cursor, which are confirmed compatible with MCP servers.

Core features and tools

Grpc MCP Gateway exposes configuration options through Protobuf annotations. Key annotations include mcp.protobuf.service for configuring MCP application metadata on gRPC services, and mcp.protobuf.tool for overriding auto-generated MCP tool names or descriptions on individual RPCs. The gateway also provides options for prompt, elicitation, enum, and progress for server streaming. The actual callable tools are the gRPC methods themselves, dynamically converted into MCP tools with corresponding JSON schemas.

Who is it for?

This program is for developers and organizations with existing gRPC-based microservices who aim to integrate them into AI agent and LLM workflows. It serves those needing to expose high-performance enterprise gRPC services to AI agents or to dynamically generate tools for AI applications. Skip this if your existing service infrastructure does not rely on gRPC for its microservices.

How to get started

Authentication relies on gRPC's native security features, including support for Mutual TLS and industry-standard token-based authentication (JWT/OAuth). The transport protocol is HTTP/2.

Use cases

• Exposing existing gRPC services to AI agents, allowing direct invocation without modifying original gRPC implementations.
• Dynamic tool generation for AI applications, converting gRPC methods and Protobuf schemas into MCP tools with JSON schemas.
• Bridging traditional microservices with AI ecosystems, integrating enterprise gRPC services into the MCP ecosystem for AI agent workflows.

Grpc MCP Gateway offers a method for integrating gRPC services into AI agent and LLM environments. By using Protobuf annotations, it helps developers convert gRPC methods into MCP tools, supporting advanced interactions with AI models. This approach allows organizations to utilize their current gRPC infrastructure within the growing MCP ecosystem.