In 1991, Tim Berners-Lee hit “publish” on the world’s first website. Back then, the internet was a mess of disconnected systems, each speaking its own language. What unlocked its explosive growth wasn’t just the magic of hypertext—it was standardization. Protocols like HTTP and TCP/IP gave developers a common foundation, and suddenly, the web wasn’t just a tech experiment—it became the backbone of modern life.

Fast-forward three decades, and AI agents are standing in the same place the internet once stood. They’re powerful, fast-evolving, and… deeply fragmented. Every company is building its own flavour of agents, but they don’t really talk to each other. Enter the Model Context Protocol (MCP)—a proposed standard that could be to AI agents what HTTP was to the web.

What is MCP?

At its core, the Model Context Protocol is an open standard that helps AI agents interact with tools, data, and even other agents. Think of it as giving them a shared language so they can stop playing in silos.

Here’s what it means in practice:

• An AI agent can plug into any tool that supports MCP—without months of custom coding.
• Developers only have to build integrations once, and every MCP-compliant agent can use them.
• Businesses know that context, security, and data handling are consistent no matter which agent they choose.

It’s not about making models “smarter.” It’s about building the plumbing that lets them work together.

Why Standardization Matters

1. Interoperability
   Picture email if Gmail couldn’t message Outlook, or if Yahoo Mail lived in its own walled garden. That’s where AI is today. MCP fixes this by making agents and tools speak the same language.
2. Developer Efficiency
   Right now, developers are reinventing the wheel every time they connect an agent to a tool. With MCP, they build once, and it works everywhere—like how a website just works across Chrome, Firefox, and Safari.
3. Scalability
   As AI agents expand from chat into full workflows and decision-making, they’ll need to connect with dozens (or hundreds) of systems. MCP makes that growth possible without endless rework.
4. Security & Trust
   When agents can schedule meetings, pull reports, or even approve payments, security isn’t optional. MCP bakes in consistent authentication, permissions, and auditing.

“Without shared standards, the future of AI agents is fragmented. With them, it’s exponential.”

Why Now?

The timing couldn’t be more urgent:

• Explosion of AI Tools: From 2023 to 2025, thousands of AI-powered apps hit the market. Without standards, we’re left with a patchwork of disconnected silos.
• Market Growth: The global AI market is on track to hit $1.3 trillion by 2030 (Grand View Research). Standards like MCP make sure that growth actually works together.
• Developer Demand: In a 2024 Stack Overflow survey, 70% of developers said they’re experimenting with AI tools. A protocol like MCP lowers the barrier so they can move faster.

We’ve seen this story before. USB, HTML, Wi-Fi—they all won because they standardized. MCP has the same potential.

What MCP Could Unlock

• Customer Support: Instead of a bot that only works with Zendesk or Intercom, imagine one MCP-compliant support agent that plugs into any ticketing system.
• Enterprise Workflows: Picture an AI assistant that can schedule meetings, pull reports, and update tasks across multiple tools—not because it was custom-built for each one, but because they all speak MCP.
• Multi-Agent Collaboration: Envision a finance AI agent negotiating with a procurement AI agent. Seamless, because they share the same standard.

A Lesson From the Web

When the web first launched, companies tried to lock users into proprietary ecosystems. But the open protocols won. Why? Because open standards scale faster than closed systems.

AI agents today feel like the early internet—full of promise, but fragmented. The difference is, this time we’ve seen the movie before. We know how it ends.

The real question isn’t if AI agents need a standard. It’s which one. And MCP is shaping up to be that candidate.

Final Reflection

The future of AI isn’t just about making smarter models—it’s about making them work together.

MCP could be the connective tissue of the AI era, doing for agents what TCP/IP did for the internet.

The choice is simple: keep building in silos and repeat the mistakes of the past, or standardize and unlock exponential growth.

So here’s the question: If AI really is the new electricity, will we wire it with extension cords—or with a power grid?