SitePoint has published a tutorial on building a Model Context Protocol server in Go, and it takes the reader from an empty module to a server that shuts down cleanly.
The Model Context Protocol, or MCP, is a standard interface for connecting AI models to outside tools and data sources. Before it existed, every pairing of a model and a service needed its own connector. The tutorial calls that an M×N problem: M models times N tools. MCP is open-source and replaces the pile of custom connectors with one protocol. Claude Desktop, VS Code with GitHub Copilot and Cursor are among the clients that support it.
Why Go
The guide makes a case for the language. A Go goroutine starts with a stack of roughly 2 to 8 KB. An operating system thread typically starts at 1 to 8 MB. That gap lets one server keep thousands of handlers running without much memory pressure, which matters when several AI sessions hit it at once.
Go also compiles to a single executable with no runtime dependencies. Shipping it, containerizing it or pointing a client’s config file at it is simple. The tutorial asks for Go 1.21 or later.
From first server to real tool
Readers build on the mcp-go SDK from Mark3Labs. The guide insists on pinning the SDK version with go get, because grabbing the latest release can bring breaking changes after the tutorial was written. Its example pins v0.26.0 and tells readers to swap in the current stable release.
The first server runs over stdio, the channel a client uses when it launches the server as a subprocess. It exposes one small tool that greets a user by name. To test it, the reader compiles the binary, adds an entry to the Claude Desktop config file and restarts the app. Asking Claude to “say hello to Alice” should trigger the tool. If it does not appear, the tutorial points to Claude Desktop’s MCP log.
Next come the other two building blocks. Resources hold read-only data, are identified by URIs and work like GET endpoints. Prompts are reusable message templates that take arguments. Tools, by comparison, are roughly the POST endpoints.
The GitHub example
The worked example is a tool called github_issue_lookup. It takes a repository owner, a repository name and an issue number. Before it builds any request, it checks the owner and repo names against an allowlist pattern: letters, digits, hyphens, underscores and dots, no more than 100 characters.
The handler reads a GITHUB_TOKEN from the environment when one is set, to avoid rate limits. It also treats GitHub’s two kinds of throttling differently. A 403 means the primary limit was hit, and the tool tells the user to set a token. A 429 signals the secondary limit, and the message says to wait before retrying.
Production details
The hardening steps are logging to stderr in structured form, input validation, and shutdown that catches OS signals and cancels a context instead of calling os.Exit. For remote use, the server switches from stdio to HTTP with Server-Sent Events. The guide also mentions the newer Streamable HTTP transport, which suits stateless remote deployments.
