Mcp Streamable Http Server

Overview

The mcp-streamable-http-server is a ready‑to‑use framework for building Model Context Protocol (MCP) services that communicate over HTTP with streaming support. It addresses the common pain point of wiring up MCP endpoints by providing a lightweight, highly configurable base that can be dropped into existing Python projects. Developers no longer need to write boilerplate code for service registration, authentication, or middleware handling; instead they can focus on the business logic that the AI assistant will invoke.

At its core, the server exposes a dynamic service registry. Services are declared in YAML files, where each entry specifies an endpoint path, allowed HTTP methods, and optional middleware chains. The server loads these definitions on startup and can add or remove routes at runtime, making it ideal for modular applications that evolve over time. Because the configuration is declarative, new services can be added without modifying the codebase—simply drop a new YAML section and restart or trigger a hot‑reload.

Authentication is another key strength. The framework supports multiple strategies out of the box, from simple token checks to full session management. By configuring authentication in YAML, developers can enforce security policies per service or globally, ensuring that only authorized AI agents can invoke sensitive endpoints. The middleware system complements this by allowing custom request/response processing, logging, or rate limiting to be applied uniformly across services.

Real‑world use cases include building a suite of microservices that power a conversational AI platform: one service might handle user profile queries, another might trigger external APIs for weather data, and yet another could stream real‑time analytics back to the assistant. Because the server is built on Starlette, it inherits high performance and asynchronous capabilities, enabling low‑latency responses even under heavy load. Developers integrating with Claude or other MCP‑compatible assistants can simply point the assistant to the server’s URL, and the streamable HTTP layer will handle continuous data streams without additional plumbing.

Unique advantages of this MCP server are its blend of flexibility and simplicity. Dynamic registration means services can be rolled out or retired without downtime, while YAML configuration keeps the setup human‑readable. The modular middleware architecture lets teams enforce cross‑cutting concerns centrally, and the built‑in authentication hooks protect sensitive operations. Together, these features make the mcp-streamable-http-server a practical foundation for any AI‑driven application that requires reliable, scalable, and secure HTTP endpoints.