FastMCP: A Simplified Framework for Model Context Protocol

Emily Xie

Keywords: FastMCP, Model Context Protocol, MCP, API, Python, LLMs, Large Language Models, medical imaging, TorchXrayVision, protocol abstraction

Abstract: This blog post introduces FastMCP, a lightweight Python framework that streamlines the development of Model Context Protocol (MCP) servers and clients. MCP is an open standard that enables Large Language Models (LLMs) to interact with external tools, data sources, and services through a standardized interface. While MCP provides significant advantages, developing compliant servers requires substantial implementation effort. FastMCP addresses this complexity by abstracting protocol-level details, enabling developers to focus on core functionality rather than implementation specifics. This post demonstrates the utility of FastMCP through a practical medical imaging application, presenting a chest X-ray classification and segmentation server implementation that illustrates the framework’s development efficiency and scalability from prototype to production deployment.

Submission Number: 3