Over the last few months, I’ve noticed a shift in how builders and operators are thinking about the future of AI applications. At the center of many of these conversations is a seemingly technical term: MCP, or Model Context Protocol.

At a glance, MCP feels like one more piece of infrastructure. A convenience layer. A spec to help models, tools, and interfaces interoperate more seamlessly.

But look just a little deeper, and it becomes clear that MCP isn’t just a technical standard. It’s a strategic decision point. One that determines who gets to own the most valuable asset in this next wave of AI: the user relationship.

What MCP promises

MCP makes it easier to plug into and compose capabilities from various AI systems. The idea is appealing:

  • Build your AI service once, expose it via MCP
  • Get distribution through ChatGPT, Gemini, Copilot, or any other interface that supports the protocol
  • Users get a consistent experience across tools
  • Developers save time by not having to build multiple integrations

On paper, everyone wins. But underneath that simplicity is a bigger shift in how power is distributed across the AI stack.

What’s really going on

The move to MCP isn’t just about openness. It is about positioning.

By embracing MCP, the major players OpenAI, Google, Microsoft are positioning themselves not just as model providers, but as aggregators. They want to become the frontends where users spend time, where interactions are observed, and where feedback loops are captured.

In a world where models are increasingly commoditized, the value shifts to:

  • Who owns the interface
  • Who captures post-training data
  • Who gets to iterate based on user intent and usage patterns

When interfaces become sticky, the model itself becomes interchangeable. The context, the usage, the data, that’s where leverage lives.

The fork in the road for builders

For those of us building in AI, MCP introduces a clear strategic fork. There are two viable paths.

1. Become the destination

This means building a product or interface that users return to. You integrate other capabilities via MCP, but you remain in control of the user experience.

Benefits of this path:

  • Own the interaction and feedback loop
  • Shape the UX in ways that make your product more valuable over time
  • Retain control over user data and learning signals

2. Plug into someone else’s interface

Here, you expose your capabilities via an MCP server, allowing other platforms to call on your tool or agent.

Benefits of this path:

  • Broader reach through existing platforms
  • Less friction to get users in the door
  • Potential to focus deeply on a narrow capability

This path favors distribution over ownership. You might get usage, but you’re further from the user and the signals that improve the product.

Why this matters more than it seems

At first glance, this might feel like a developer convenience story. But it is much more than that.

Protocols like MCP don’t just change how software components talk to each other. They change how products are built, who gets visibility into usage, and who compounds value over time.

If you’re old enough to remember how browser defaults shaped the early web, or how app store dynamics shaped mobile, this should feel familiar.

  • Browsers became more than rendering engines; they became distribution gateways
  • Mobile home screens became the interface layer that determined which apps thrived
  • SaaS platforms captured workflows and created data moats

AI is following a similar pattern. Protocols are emerging. Interfaces are consolidating. And behind the scenes, value is starting to concentrate again.

What this means for me

Personally, I find myself thinking about the long-term implications more than the technical ones. I’m not building for the protocol. I’m building for leverage, for feedback, for meaningful interaction.

MCP is not just an interoperability layer. It is a lens through which to re-evaluate where your product sits in the emerging AI value chain.

The question is simple:

Do you want to be the product users return to, or a feature someone else wraps?

The answer, like most strategic choices, depends on what you want to own.