
Building Your Own MCP Servers: A Step-by-Step Guide using MultiServerMCPClient
Last Updated on August 29, 2025 by Editorial Team
Author(s): Sai Bhargav Rallapalli
Originally published on Towards AI.
Unlock the Power of Model Context Protocol (MCP) for AI Applications
Have you ever wanted to integrate custom tools β like weather APIs, or third-party services β into your AI applications seamlessly? The Model Context Protocol (MCP) makes this possible by allowing developers to create modular, scalable, and easily maintainable AI tool integrations.
This article provides a comprehensive guide on how to build your own Model Context Protocol (MCP) servers and integrate them with AI applications, focusing on communication flow, environment setup, and the role of various MCP components such as clients and servers. It covers detailed examples, including setting up a math server using standard input/output and a weather server using HTTP transport, while also exploring the advantages and potential of MCP for improving AI integration.
Read the full blog for free on Medium.
Join thousands of data leaders on the AI newsletter. Join over 80,000 subscribers and keep up to date with the latest developments in AI. From research to projects and ideas. If you are building an AI startup, an AI-related product, or a service, we invite you to consider becoming aΒ sponsor.
Published via Towards AI