<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Build Your Own MCP Server on Nitin Kumar Singh</title><link>https://nitinksingh.com/series/build-your-own-mcp-server/</link><description>Recent content in Build Your Own MCP Server on Nitin Kumar Singh</description><generator>Hugo -- gohugo.io</generator><language>en</language><copyright>© 2026 Nitin Kumar Singh. All rights reserved.</copyright><lastBuildDate>Thu, 16 Jul 2026 09:00:00 +0530</lastBuildDate><atom:link href="https://nitinksingh.com/series/build-your-own-mcp-server/index.xml" rel="self" type="application/rss+xml"/><item><title>MCP: What It Is and Why It Changes How You Build AI Tools</title><link>https://nitinksingh.com/posts/mcp-what-it-is-and-why-it-changes-how-you-build-ai-tools/</link><pubDate>Tue, 21 Apr 2026 10:00:00 +0530</pubDate><guid>https://nitinksingh.com/posts/mcp-what-it-is-and-why-it-changes-how-you-build-ai-tools/</guid><description>&lt;p&gt;Before MCP existed, adding tools to an AI application meant writing the same glue code over and over. You had OpenAI&amp;rsquo;s function calling syntax. Anthropic had tool use with a slightly different schema. LangChain abstracted over both, but now you depended on LangChain&amp;rsquo;s versioning decisions. Every new model provider meant rewriting your tool definitions. Every new tool meant re-registering it across every AI integration you maintained.&lt;/p&gt;</description></item></channel></rss>