MCP SSE Server

Overview

The Mcp SSE server is a lightweight implementation of the Model Context Protocol (MCP) designed to bridge AI assistants—such as Claude Desktop—with external tooling over a secure, real‑time channel. By leveraging Server‑Sent Events (SSE) for one‑way streaming and Bearer token authentication, the server provides a low‑overhead, bidirectional communication layer that is both easy to deploy and straightforward for developers to extend.

At its core, the server exposes a set of tools that can be invoked by an AI client through MCP. Each tool is a self‑contained TypeScript module that performs a specific operation—in this example, four simple arithmetic functions. The MCP module registers these tools at startup, while the Express router exposes two endpoints: for establishing an SSE stream that pushes messages back to the client, and for receiving inbound requests. The authentication middleware validates every request against a configurable Bearer token, ensuring that only trusted clients can interact with the server.

For developers building AI‑powered applications, this architecture offers several tangible benefits. First, SSE eliminates the need for WebSocket handshakes or polling loops; the server can push results to the client as soon as they are ready, which is ideal for latency‑sensitive tasks like real‑time data analysis or live feedback. Second, the modular design—separating middleware, routing, and tool registration—follows SOLID principles, making it trivial to add new tools or replace authentication strategies without touching the core logic. Third, because the server is written in TypeScript and can run directly with , developers can iterate quickly during prototyping, then compile to JavaScript for production deployments.

Real‑world use cases include integrating domain‑specific APIs (weather, finance, or custom business logic) into an LLM’s workflow, enabling the assistant to fetch fresh data or trigger external processes on demand. The SSE stream can carry incremental results, allowing the assistant to display partial computations or progress updates in a user interface. In a production environment, the Bearer token can be rotated automatically, and the server can be wrapped behind an API gateway or service mesh to enforce rate limits and observability.

Overall, the Mcp SSE server exemplifies how MCP can be combined with modern web transport protocols to create secure, efficient, and extensible toolchains for AI assistants. Its straightforward API, coupled with real‑time streaming and token‑based security, makes it an attractive choice for developers who need to expose custom logic to conversational agents without reinventing the networking layer.