ServiceStack MCP Server

The ServiceStack MCP Server is a lightweight, TypeScript‑based implementation that turns a simple notes application into a fully‑featured Model Context Protocol (MCP) service. It bridges the gap between traditional RESTful APIs and AI assistants by exposing notes as first‑class resources, providing tool primitives for mutating those resources, and offering prompt templates that let LLMs perform higher‑level operations such as summarization. This approach demonstrates the core MCP concepts—resources, tools, and prompts—in a concrete, production‑ready example.

At its heart, the server models each note as an opaque resource with a URI. The URI scheme lets AI clients address individual notes directly, while the accompanying metadata (title, content, and simple text MIME type) gives assistants context about each item. Developers can list all notes or fetch a specific one with a standard GET request, enabling seamless navigation through the note collection without exposing internal data structures.

Mutation is handled by a single tool, . When invoked, the assistant supplies a title and content payload; the server persists this new note in its internal state and returns the newly minted URI. This tool pattern illustrates how MCP can expose procedural capabilities in a declarative way, allowing assistants to extend the data store on demand. Because the tool is stateless from the client’s perspective, it can be reused across sessions and integrated into complex workflows.

For higher‑level reasoning, the server offers a prompt. This template aggregates all stored notes as embedded resources and produces a structured prompt that an LLM can consume to generate a concise summary. By embedding the notes directly into the prompt, the server eliminates the need for external data fetching during summarization, reducing latency and simplifying client logic.

In real‑world scenarios, this MCP server can power note‑taking assistants, knowledge bases, or collaborative document editors. A developer could wire the server into a chatbot that allows users to create, retrieve, and summarize notes with natural language commands. Because the server adheres strictly to MCP conventions, it integrates smoothly with any AI workflow that supports the protocol—whether that’s Claude Desktop, a custom LLM wrapper, or an orchestration platform. The clear separation of resources, tools, and prompts also makes the system highly testable and maintainable.

What sets ServiceStack MCP apart is its simplicity coupled with a full MCP feature set. By providing a tangible example that covers resource discovery, tool invocation, and prompt generation, it serves as both a learning aid for newcomers to MCP and a drop‑in component for developers seeking to expose existing APIs to AI assistants without rewriting their backend logic.