Mcp Swift Example Server

MCP Swift Example Server

The Mcp Swift Example Server is a lightweight, stdio‑based Model Context Protocol (MCP) implementation written in Swift. It is designed to illustrate how an external tool can expose a simple, reusable capability—an echo service—to AI assistants such as Claude Desktop. By running the server as a child process, developers can quickly integrate custom Swift logic into their AI workflows without the overhead of setting up a full HTTP API or cloud service.

The server’s core value lies in its minimalism and clarity. It demonstrates the full MCP lifecycle: initializing a server, registering a custom tool (), and handling the two primary MCP requests—, which informs the client of available tools, and , which executes the echo logic. All communication is performed over standard input/output streams, making it trivial to spawn from any host application that supports MCP. Detailed logging to standard error ensures that developers can diagnose issues in real time without cluttering the client’s output.

Key features include:

• Custom tool registration: The tool accepts a string argument and returns it unchanged, serving as an identity function that confirms the communication pipeline.
• Stdio transport: By leveraging , the server can be invoked from desktop applications like Claude Desktop, which expect a command‑line executable that reads and writes JSON over stdin/stdout.
• Extensibility: The server’s structure—, , and a clear entry point—provides an excellent scaffold for adding more sophisticated tools, such as file I/O or network requests, while keeping the MCP contract intact.
• Comprehensive logging: All server events are streamed to , allowing developers to monitor request handling without interfering with the MCP payload.

Typical use cases include rapid prototyping of AI‑enabled tooling, educational demonstrations of the MCP specification, and integration into local development environments where a lightweight, self‑contained server is preferable to external services. For instance, a Swift developer can expose local code analysis or build scripts as MCP tools and invoke them directly from an AI assistant, enabling a seamless blend of code generation and execution.

Because the server operates over stdio, it integrates effortlessly into existing AI workflows. A developer can add the executable path to the file, after which Claude Desktop automatically discovers and lists the tool. Subsequent calls to this tool are translated into standard MCP messages, ensuring consistent behavior across different languages and platforms. The server’s simplicity also makes it an ideal starting point for exploring advanced MCP features such as tool chaining, prompt injection, or resource management—all while remaining grounded in a familiar Swift ecosystem.