What Is MCP in AI? Intro to the Model Context Protocol

Alright, time to bring a bit of perspective to a hot topic making waves lately: MCP.

First Things First: What is MCP really?

Let’s get one thing straight: MCP is a protocol, not a toolbox or suite of tools. So when you hear someone refer to “MCPs” in the plural, chances are they’re a little fuzzy on the concept.

That said, it is correct to talk about “MCP servers” – and a lot of the confusion out there stems from mixing up the protocol itself with its implementations.

So, What Does the Model Context Protocol Actually Do?

MCP (Model Context Protocol) is an open standard introduced by Anthropic (makers of Claude AI) in November 2024. Its purpose? To securely connect AI assistants like Claude to your external data and tools:

• Content repositories
• Enterprise systems
• Developer environments

Put simply, MCP is a standardized pipeline that lets AI models access your data and use your tools without having to reinvent the wheel every time.

In other words, if language models are the "brains", the Model Context Protocol gives them "hands".

MCP Servers & Tools: The Core of the System

What many refer to (incorrectly) as “MCPs” are actually MCP servers: implementations of the protocol that expose specific functionalities. Think of them as add-ons that extend what AI agents can do.

The MCP architecture includes:

• A host (like Claude Desktop or dev tools such as Cursor)
• An MCP client that creates secure connections
• One or more MCP servers acting as bridges to your apps (Google Drive, Slack, GitHub...) while giving relevant context to the client

No Need for FOMO

Here’s why you shouldn’t feel like you're missing out:

MCP is built for developers. It’s a tool meant for those creating AI agents or building extensions for platforms like Cursor, Windsurf, Replit, etc.

If you’re a regular AI tool user, here’s what will likely happen:

• You’ll use products that integrate MCP under the hood
• You’ll benefit from the power it unlocks, without needing to understand how it works
• You probably won’t even know MCP is running behind the scenes

But If You’re Curious to Get Hands-On…

Good news! You can experiment with MCP-powered workflows even if you’re not a developer.

Platforms like Zapier already offer accessible ways to tap into this ecosystem. That means you can connect your favorite automations (emails, spreadsheets, Slack alerts) directly to an AI agent.

Imagine asking Claude to:

• Create a Notion task from a support email
• Schedule meetings on your calendar with the right attendees
• Update Airtable records and post to Slack

Thanks to MCP connectors, your existing workflows become capabilities for your AI agents with no deep tech knowledge required.

These integrations let you benefit from MCP without needing to understand all the technical plumbing behind it.

In Summary

MCP is the next logical step after OpenAI’s "function calling". It’s a standardized framework for letting large language models interact directly with your tools and data.

Yes, it’s a big deal for the AI ecosystem. But no, you don’t need to master it yourself.

As with much in tech: let the pros handle the plumbing and enjoy the clean water that flows from the tap.

If you’re a developer, MCP is definitely worth exploring. For everyone else, just sit back and enjoy the new features your favorite tools are unlocking with it. No FOMO required!