Everyone talks about MCP in AI, but most explanations are confusing.
In this video, I explain what MCP really is, using an ELI5 approach.
You'll understand why it matters, what problem it solves, and how it helps AI use tools and context properly.
So what is an MCP? Let me break it down simply.
MCP stands for Model Context Protocol. It’s basically a bridge between an AI model and a third-party service, application, or database.
The USB & Power Outlet Analogy
Think about a USB stick. You can plug it into your iPhone, your Mac, your monitor. Why? Because it follows a universal standard that every device understands. No “wait, is this compatible?” Just plug and play.
Now think about power outlets in the EU (minus the UK). Wherever you are, France, Spain, Italy, same outlet, same plug, no adapter needed. South Korea? Same thing. You walk in, spot the outlet, plug your charger in, done.
This is exactly what MCP does.
An MCP server and an MCP client speak the same language. They follow the same protocol, expect the same format, and connect an application to an AI model without friction. No custom glue code for every integration. No reinventing the wheel every time your AI needs to talk to a new tool or service.
Why Does It Matter?
Before MCP, connecting an AI model to external tools was messy. Each integration was its own thing, with its own quirks and custom implementation.
MCP standardizes all of that. It’s the universal plug for AI integrations. Build once, connect everywhere. Simple as that.
I’ve built many projects on my GitHub over the years that you can check out for inspiration or contribution! I’ve got plenty more content coming your way on my LinkedIn! Hit the ‘follow’ button so you are sure to not miss out! Enjoy your day! 🏝️
