Overview of protoc-gen-go-mcp

is a Protocol Buffers compiler plugin that automatically generates Model Context Protocol (MCP) servers for your gRPC or ConnectRPC APIs written in Go. By converting each protobuf service into a set of MCP tools, it bridges the gap between traditional RPC services and modern AI assistants that consume tools via JSON‑schema‑defined inputs. This integration allows developers to expose existing service logic to LLMs without rewriting business code, thereby accelerating the creation of intelligent assistants that can orchestrate complex workflows.

The plugin produces a dedicated file for every protobuf service. Inside these files, each RPC method is turned into an MCP tool with a corresponding JSON Schema derived directly from the protobuf message descriptors. The generated handlers delegate calls straight to your existing gRPC or ConnectRPC server implementations, meaning there is no runtime overhead beyond the usual network stack. Because MCP relies on JSON Schemas for input validation, developers can rely on a single source of truth—the protobuf definitions—to guarantee type safety across the entire stack.

Key capabilities include:

• Automatic MCP handler generation from files, eliminating manual boilerplate.
• JSON Schema output for every method input, ensuring that AI assistants can validate arguments before invocation.
• Dual runtime support: choose between the standard MCP schema or an OpenAI‑compatible variant at runtime, without needing to regenerate code.
• Seamless integration with pipelines and ConnectRPC, enabling a smooth workflow for teams already using these tools.
• Bidirectional wiring: register handlers on a server or forward calls to an existing gRPC/ConnectRPC client, giving flexibility in how services are exposed.

Real‑world scenarios where this tool shines include:

• Enterprise chatbot development: expose internal microservices (e.g., inventory, billing) as tools that a conversational AI can invoke on demand.
• Automated workflow orchestration: let an LLM coordinate multiple RPC calls by treating each as a discrete tool, simplifying complex business logic.
• Rapid prototyping: developers can quickly surface a new service to an AI assistant by adding a file and running , without touching the core logic.
• Hybrid cloud deployments: forward MCP tool calls to remote gRPC services, allowing AI assistants running in one environment to control resources elsewhere.

By converting your existing Go RPC services into MCP‑ready endpoints, empowers developers to harness the full potential of AI assistants while preserving the robustness, type safety, and performance of conventional gRPC infrastructure.