What Is MCP? And Why It Changes How AI Works With Your Business

If you've heard the term "MCP" or "Model Context Protocol" and wondered what it actually means—or why it matters for your organization—you're not alone. MCP is one of the most significant (and newest) developments in how generative AI connects to the real world. Here's what you need to know.

The core idea: giving AI access to your systems

Traditionally, generative AI has been limited to what it was trained on. You ask a question, it answers from its knowledge. That's useful, but it can't query your databases, trigger your workflows, or act on your behalf. MCP changes that. Model Context Protocol is a specification that lets AI models connect directly to your business information, tools, and APIs. Once connected, the AI can discover what's available, reason about when to use it, and invoke those tools on its own—without you manually wiring every interaction.

The power is in the delegation. Instead of AI being a passive assistant that only responds to prompts, it becomes an autonomous agent that can use your systems as extended capabilities. It can pull data from your CRM, run reports, update records, or trigger downstream processes. The AI decides when and how to call your tools based on the task at hand.

A new technology, evolving fast

MCP is remarkably new. The ecosystem is still forming, standards are still being refined, and best practices are being written in real time. That makes it both exciting and a bit uncertain—but it also means organizations that engage with it now have a head start in shaping how it gets used.

The technology is evolving rapidly. What exists today will likely look different in a year. That's typical for infrastructure that sits at the intersection of AI and enterprise systems. The organizations that invest in understanding and piloting MCP now will be better positioned when it becomes mainstream.

It's really an advancement on backend APIs

If MCP sounds familiar, that's because it builds on concepts you already know. For decades, businesses have integrated systems via APIs—REST, GraphQL, internal services. The pattern is the same: one system exposes capabilities, another calls them. MCP is essentially that same paradigm, but the "client" is no longer a fixed script or app; it's an intelligent agent that can discover, reason about, and invoke tools dynamically.

So it's not a replacement for your existing API architecture. It's a tighter integration between AI and those APIs. Instead of rigid, hand-coded connections between systems, the AI can adapt—choosing which tools to use, in what order, based on context. That's the evolution: backend APIs integrated more tightly with AI, with the AI in the driver's seat.

Why it matters for your business

For organizations that adopt MCP early, the payoff is a new class of applications: AI that doesn't just answer questions, but acts on them. That could mean automations that were previously too complex to build, or interfaces that feel more like working with a colleague than a search box. The organizations that figure out how to deploy MCP safely and effectively will have a real advantage.

The Business Informatics Group helps enterprises design, build, and deploy generative AI infrastructure—including MCP and tool use—so that AI creates measurable business value. Get in touch if you'd like to explore what's possible.