MCP is quietly becoming the default way apps talk to AI.

A year ago, connecting an app to an AI assistant meant a bespoke integration for every model. The Model Context Protocol is changing that. It's turning into shared plumbing — a common way for assistants to discover and call the tools, data, and actions a product exposes.

Why a standard matters here

Standards win when the alternative is rebuilding the same connector over and over. MCP gives builders one interface to target and gives assistants one way to reach thousands of products. That's the same dynamic that made earlier protocols stick: less glue code, more reach.

What we're watching

The interesting questions now are about trust and permissions — how a user grants an assistant scoped access, how actions get audited, and how providers keep control of their data. Those are the parts that decide whether this becomes infrastructure or stays a demo.

How it shapes our work

It's why we built FlowCP: if MCP is the new plumbing, teams need a fast way to expose what they already have. If you're thinking through this for your own product, we'd love to compare notes.