What surprised me here is how hard the author leans on a very unglamorous claim: the real win is not “using MCP,” it’s just getting out of the shared-process mess. That feels right. A lot of infrastructure writeups dress up basic process isolation as protocol sophistication, and this piece mostly refuses to do that. Good. The protocol is the wrapper; the blast-radius reduction is the actual value.
I’m a little less convinced by the way MCP is presented as the natural next step once you have “a growing number of services.” Maybe. But if I were building this, I’d first ask whether I even want an orchestrator that knows about multiple tools in the first place, or whether some of this should still be a plain service boundary with boring HTTP. The author says that too, which I appreciated. That honesty matters because MCP can become the kind of extra layer people add just because the ecosystem has a name for it.
The part I do buy completely is the warning about accidental re-coupling. Two servers on two ports do not automatically mean two independent services if they quietly share helper modules, validation code, or a dependency assumption that only one side can satisfy. That’s the real trap in these setups. You can split the process and still end up with one logical blob wearing two costumes. The article is strongest when it treats isolation as a discipline rather than a framework feature.
I also think the orchestrator example is telling in a good way. It’s not trying to be clever. Just fetch tools, call one, pass output onward. That restraint is refreshing. A lot of agent-stack writing jumps straight to conditional graphs, routing, memory, retries, and all the rest, when the plain sequential case is already where most teams will break things. The author is right to say “start here.”
Where I’d want more is on the messy edges the piece only gestures at: what happens when network boundaries turn simple exceptions into partial failures, how observability changes, and whether the operational overhead of separate services is worth it for the scale of the pipeline described. I don’t think that question gets answered by architecture diagrams. It gets answered when someone on call has to debug a 2 a.m. failure with three services and one broken assumption.
Still, the core argument lands: if the pain is dependency conflict, shared runtime risk, and forced redeploys, then the fix is separation first and protocol second. MCP is just one way to make that separation callable.
Reference: When One Process Becomes Too Much: Splitting a Pipeline into MCP Services | Towards Data Science
