alt Hacker NewsYou're interacting with an LLM, so correctness is already out the window. So model-makers train LLMs to work better with MCP to increase correctness. So the only reason correctness is increased with MCP is because LLMs are specifically trained against it.
So why MCP? Are there other protocols that will provide more correctness when trained? Have we tried? Maybe a protocol that offers more compression of commands will overall take up more context, thus offering better correctness.
MCP seems arbitrary as a protocol, because it kinda is. It doesn't >>cause<< the increase in correctness in of itself, the fact that it >>is<< a protocol is the reason it may increase correctness. Thus, any other protocol would do the same thing.
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> So why MCP? ... MCP seems arbitrary as a protocol
See the screencaps at the end of the post that show why this protocol. Maybe one day, we will get a better protocol. But that day is not today; today we have MCP.
> You're interacting with an LLM, so correctness is already out the window.
With all due respect if you are prompting correctly and following approaches such as TDD / extensive testing then correctness is not out the window. That is a misunderstanding likely caused by older versions of these models.
Correctness can be as complete as any other new code, I've used the AI to port algorithms from Python to Rust which I've then tested against math oracles and published examples. Not only can I check my code mathematically but in several instances I've found and fixed subtle bugs upstream. Even in well reviewed code that has been around for many years and is well used. It is simply a tool.