API or MCP? What's the difference?

If you have spent any time around AI tools this year, you have seen both of these terms. Someone says "we integrate through the API." Someone else says "we support MCP." They sound interchangeable. They are not, and the difference matters for what your agent can actually do for you.

No jargon required. Here is the whole thing.

Start with what they have in common

Your AI agent is smart, but it lives in a room by itself. Your calendar, your accounting, your CRM, your files, all of that lives outside the room. Both an API and MCP are ways of getting information and actions through the wall.

The difference is not what gets through. The difference is who builds the opening, how much work it takes, and what happens when you want to add the next one.

What an API is

An API is a private doorway that one company builds into its own product. QuickBooks has one. Slack has one. Google has several. Each one is different: different rules, different paperwork, different keys, different quirks.

APIs are not an AI thing. They have been around for decades, and they are how most software talks to other software. They work. Your bank uses them every day.

But here is the catch for AI: an API does not explain itself to your agent. Someone has to sit down and write custom code that says "here is how to ask QuickBooks for an invoice, here is what comes back, here is what to do when it fails." Then they have to do it all over again for Slack. And again for your CRM. Every connection is its own little construction project, built by hand, maintained by hand.

Think of it like plumbing. Every building has water, but every hookup is custom work by someone who knows that building.

What MCP is

MCP stands for Model Context Protocol. It is a standard, created by Anthropic, that lets a tool describe itself to an AI agent in a language every agent can read.

A tool that speaks MCP essentially hands your agent a card that says: here is my name, here is what I can do, here is what I need from you, here is what I give back. Your agent reads the card and starts working. Nobody wrote custom code for that specific pairing.

The comparison everyone uses is USB, and it is the right one. Before USB, every device had its own plug. USB said: one port, one standard, everything connects. MCP is that port, for AI.

The difference, side by side

So is MCP just better?

For AI agents, mostly yes. That is why the whole industry is moving toward it. But the honest answer has two caveats.

First, MCP is younger. The big platforms are still rolling out their official MCP servers, and some tools you rely on may only have an API today. A well-built API connection beats a missing MCP one.

Second, a connection is only as trustworthy as the door policy behind it. MCP makes connecting easy. It does not decide what the agent is allowed to touch once connected. That part is on the workspace you use, and it is where you should be paying attention.

How Virgil handles it

Virgil Terminal does both, deliberately.

The everyday spine, your Microsoft 365, Google Workspace, Slack, QuickBooks, and Procore, runs on solid, tested connections we built and maintain. Those are live today.

For everything else, we made a decision: instead of hand-building a bridge to every product on earth, Virgil speaks MCP natively. If a tool you use publishes an MCP server, you can connect it to a project by URL, approve what it is allowed to do, and your agent gets to work. As the catalog of MCP tools grows, and it is growing fast, your Terminal grows with it without waiting on us.

And in Virgil, every connection, API or MCP, attaches to a single project, not your whole account. The QuickBooks connection on your books project does not exist as far as your marketing project is concerned. Easy to connect is only good news when it is also easy to contain.

The bottom line

An API is a custom doorway; MCP is a common language. APIs got software this far, and MCP is what lets AI agents use thousands of tools without a thousand construction projects.

You do not need to remember any of this. You just need to know what to ask when someone sells you an AI product: can it reach the tools I already use, and who decides what it touches once it is in? If the answers are "yes" and "you," you are in good shape.