> The main reason is that it adds another layer (and human) that can, and probably will, get out of sync with the real-world implementation, whether that implementation is an API, web, or a CLI.

The menial task of updating the interfaces when the code changes is something AI should be really good at, so it's essentially little to no actual programmer time waste

> So the current situation is basically that I used Claude to write an MCP server on top of our API. And then I need to occasionally tell it update it match the public doc.

> And my reaction is: really? It is not like our API docs are not public. Claude Code created our MCP server with zero instructions beyond what is publicly available. I just told it to read the docs from the net.

Updating MCP by AI is one time effort.

Having AI re-create what MCP would do for every piece of code that uses a service is massively wasted effort in comparison

It's not question of "model limitation" but of cost effectiveness.