When a human is coding against a traditional API, it might be a bit annoying if the API has four or five similar-sounding endpoints that each have a dozen parameters, but it's ultimately not a showstopper. You just spend a little extra time in the API docs, do some Googling to see what people are using for similar use cases, decide which one to use (or try a couple and see which actually gets you what you want), commit it, and your script lives happily ever after.

When an AI is trying to make that decision at runtime, having a set of confusing tools can easily derail it. The MCP protocol doesn't have a step that allows it to say "wait, this MCP server is badly designed, let me do some Googling to figure out which tool people are using for similar use cases". So it'll just pick whichever ones seems most likely to be correct, and if it's wrong, then it's just wasted time and tokens and it needs to try the next option. Scaled up to thousands or millions of times a day, it's pretty significant.

There's a lot of MCP servers out there that are just lazy mappings from OpenAPI/Swagger specs, and it often (not always, to be fair) results in a clunky, confusing mess of tools.