Will Anthropic’s MCP Become the Backbone of Agentic AI ?

The AI world is evolving faster than ever. And one new standard is quietly setting the stage for the next big leap: Anthropic’s Model Context Protocol (MCP).

If you haven’t heard of MCP yet, you will soon. Major players like OpenAI and Google are already adopting it — not just because it makes AI models smarter, but because it lays the foundation for something even bigger: Agentic AI, where models can reason, plan, and act dynamically across environments.

What is MCP?

In late 2024 [it feels like so long ago... ], Anthropic introduced the Model Context Protocol — or MCP — to solve a growing problem. Until now, AI models needed custom-built integrations for every external tool or dataset they wanted to use. It was messy, slow, and often unreliable.

MCP flips that on its head by introducing a universal, open standard that any model and any tool can use to communicate. You can think of it like USB, but for connecting models to digital systems instead of plugging in your phone charger. Now, instead of bespoke patches and clunky bridges, AI models can easily “talk” to tools and APIs through a single, streamlined protocol.

In practical terms, MCP lets AI systems expand their knowledge and capabilities dynamically — without needing to be retrained or manually tweaked every time a new tool shows up.

Why OpenAI and Google Are Backing It

It didn’t take long for the heavyweights to see the value. OpenAI quickly started integrating MCP into its Agents SDK and even the upcoming ChatGPT desktop app. They’re clearly thinking ahead — making it easy for users to connect AI models to live data, APIs, and proprietary tools without reinventing the wheel every time.

Not to be outdone, Google DeepMind has been rolling MCP into its Gemini models as well. They’re betting that a standard like MCP will make their AI systems more modular, dynamic, and ready for the complex, ever-changing digital ecosystems of the future.

When you see companies like OpenAI and Google moving together in the same direction, you know something big is happening. They’re signaling that the future of AI isn’t siloed — it’s interoperable — and standards like MCP are what will make that future possible.

MCP and the Rise of Agentic AI

The real magic of MCP isn’t just in cleaner integrations or developer convenience. It’s in what it unlocks: Agentic AI.

Agentic AI isn’t just about answering questions — it’s about models dynamically pulling in new information, choosing and using tools intelligently, and planning and executing complex workflows across different systems. It’s about AI that can think, act, and adapt almost like an autonomous agent.

MCP is critical here because it gives AI agents a consistent, reliable way to interact with the outside world. Without a standard like this, every tool an agent might use would need custom logic. Every system it might touch would need special handling. With MCP, agents can navigate seamlessly, reason about their options, and act securely — all through a common interface. In short, MCP turns fragmented AI ecosystems into unified playgrounds for autonomous agents.

So what ...

Anthropic’s MCP isn’t just a neat technical trick — it’s a foundational shift. It’s setting the stage for a future where AI models aren’t frozen in their pre-trained knowledge, but can dynamically expand, adapt, and interact with live environments.

And now, with OpenAI, Google, and likely more to follow, it’s clear that MCP is on track to become the TCP/IP of AI’s next era — the invisible but critical infrastructure that powers a whole new generation of intelligent systems.

The future of AI isn’t just smarter. Thanks to MCP, it’s about to get a whole lot more connected — and a whole lot more agentic.