Building a Simple MCP Server in Python - MachineLearningMastery.com

Machine Learning Mastery

by Bala Priya C

February 19, 2026

AI-Generated Deep Dive Summary

Building a Simple MCP Server in Python Using FastMCP Model Context Protocol (MCP) is an open-source framework that standardizes communication between AI applications and external systems. This article guides readers through building a practical MCP server in Python, utilizing the FastMCP framework to create a task-tracker application. The tutorial explains MCP's core components—hosts, clients, and servers—and demonstrates how to implement tools, resources, and prompts for seamless AI interactions. The MCP protocol operates by enabling hosts (AI-driven applications) to connect with servers through client instances. These servers provide functionalities like database access or file operations, while tools execute specific actions, resources offer data access, and prompts guide AI workflows. The article walks readers through setting up the environment, initializing the server, and creating an in-memory task storage system. By following the step-by-step instructions, developers can build a functional MCP server that manages tasks, complete with unique IDs and timestamps. This hands-on approach highlights how FastMCP simplifies integrating AI capabilities into applications, avoiding repetitive connection logic. The article also emphasizes the importance of MCP in standardizing AI interactions, making it easier to connect language models with external systems. For those interested in AI development, understanding MCP is crucial as it streamlines integration processes and enhances modularity across applications. This tutorial serves as a valuable resource for developers looking to leverage AI tools and protocols effectively.

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Originally published on Machine Learning Mastery on 2/19/2026