A plain-language guide to the Model Context Protocol for DevOps engineers: what MCP is, how an agent like Claude Code reaches your infrastructure through it, and why the server you expose is the boundary that keeps that access safe.
An AI coding agent that can only read your local files is a better autocomplete. The moment you want it to answer “why is this pod crashing?” it has to reach a live system it does not control. That raises a governance question before a technical one.
The value: an agent that can see your cluster, CI, or database can investigate real problems.
The risk: the same connection that lets it read could let it delete, scale, or reconfigure.
The wrong fix: hand-rolling a one-off bridge per tool, each with its own ad-hoc access and no shared rules.
The question this track answers: how does an agent reach infrastructure through a governed, standard interface?
Before MCP, every AI application invented its own way to plug into every external system, so access and permissions were bespoke and inconsistent.
A shared protocol lets you reason about that access once — what the agent can call, and what identity it calls with — instead of re-deciding it for each integration.
You can state the real problem in one sentence: an agent needs to reach live infrastructure, and the connection that grants sight can also grant change unless something constrains it.