Overview of Go MCP

Go MCP is a purpose‑built SDK that lets developers create Model Context Protocol (MCP) servers in Go with minimal friction. By providing a type‑safe, code‑generated interface, it eliminates the guesswork that often accompanies MCP development. Instead of manually wiring JSON schemas and RPC handlers, developers define their server’s capabilities once—such as tools, logging, or custom prompts—and the SDK produces fully typed request and response structs that compile straight away. This guarantees that any mismatch between a tool’s expected input or output is caught at build time, dramatically reducing runtime errors.

The core value of Go MCP lies in its developer‑centric design. The API follows idiomatic Go patterns, so seasoned Go programmers can pick it up instantly without learning a new domain‑specific language. The SDK’s code generation step handles all the heavy lifting: it creates request/response types, registers tool handlers, and scaffolds a minimal server skeleton. This means teams can focus on implementing business logic rather than boilerplate networking or schema validation code.

Key capabilities include type‑safe tool definitions, logging integration, and support for the full MCP specification. Developers can declare tools with Go structs that embed JSON‑Schema metadata; the generator turns these into strongly typed request handlers. The logging capability allows MCP clients to query server logs, which is essential for debugging complex AI workflows. Because the SDK respects the MCP contract, any client that follows the protocol can interact with the server out of the box.

In real‑world scenarios, Go MCP shines when building custom AI assistants that need to call external services—such as converting units, querying databases, or invoking REST APIs—within a single conversational flow. For example, an internal chatbot that converts temperatures, calculates taxes, or retrieves inventory data can expose each operation as a separate tool. The server’s type safety guarantees that the assistant receives the exact parameters it expects, while the logging feature provides traceability for audit trails or performance monitoring.

Integrating Go MCP into existing AI pipelines is straightforward. Once the server is running, any MCP‑compatible client (Claude, Claude 3, or other future assistants) can discover the server’s tools via the standard capability discovery mechanism. The client then calls the desired tool, passing a JSON payload that matches the generated request type; the server processes it and returns a typed response. Because the SDK is open source, teams can extend or customize the generated code to add authentication, rate limiting, or other middleware without breaking the MCP contract. This modularity makes Go MCP a powerful foundation for building reliable, maintainable AI‑powered services.