The industry is talking in circles here. All you need is "composability".

UNIX solved this with files and pipes for data, and processes for compute.

AI agents are solving this this with sub-agents for data, and "code execution" for compute.

The UNIX approach is both technically correct and elegant, and what I strongly favor too.

The agent + MCP approach is getting there. But not every harness has sub-agents, or their invocation is non-deterministic, which is where "MCP context bloat" happens.

Source: building an small business agent at https://housecat.com/.

We do have APIs wrapped in MCP. But we only give the agent BASH, an CLI wrapper for the MCPs, and the ability to write code, and works great.

"It's a UNIX system! I know this!"