Yeah, I'm still confused as to why so many people in "AI engineering" seem to think that MCPs are the key to everything.
They are great if you have a UI that you want and it needs a plugin system, obviously.
But the benefits become much more marginal for a developer of enterprise AI systems with predefined tool selections. They are actually getting overused in this space, if anything, sometimes with security as a primary casualty.
If you are writing a bespoke Agent with a constrained set of tools known in advance, MCP is a detriment. All it will do is introduce complexity, fragility, and latency.
If you have that nice Agent and suddenly marketing "needs" it to talk to Super Service A, you either go back into a dev cycle to create a new set of curated tools that live inside the Agent around SSA *or* you make the Agent capable of acting as an MCP Host and configure a new MCP Client connection to an MCP Server offered by the SSA team. If SSA doesn't have their own MCP Server you could potentially leverage a 3rd-party one or write your own as a fully encapsulated project that doesn't live inside the Agent.
MCP isn't meant to be *the* way you provide tools for your Agent, it's meant to prove a *standard* that allows you to easily add off-the-shelf tool sets via simply configuring the Agent.
They are great if you have a UI that you want and it needs a plugin system, obviously.
But the benefits become much more marginal for a developer of enterprise AI systems with predefined tool selections. They are actually getting overused in this space, if anything, sometimes with security as a primary casualty.