Soon, if you want the performance of your AI clients to improve (wrt. token count and understanding) you will start to customize the output of the MCP server for more synthetic data, different data types, more permissive inputs, etc. And since most your clients will be AI that might be your API that fall behind, and MCP that will be maintained.
That's at least my experience with my current project: the traditional json, coding oriented API feels out of place, I maintain it out of habit. The real API is the MCP server, which is not designed like a traditional API would; understandability of the output for an LLM prevails instead of searchng for exhaustiveness, orthogonality etc.