It's just function calling with a new name and a big push from the LLM provider, but this time it's in the right direction. Contrast with OpenAI's "GPTs", which are just function calling by another name, but pushed in the wrong direction - towards creating a "marketplace" controlled by OpenAI.
I'd say that thing you're feeling comes from witnessing an LLM vendor, for the first time in history, actually being serious about function calling and actually wanting people to use it.
But either way the interface is just providing a json schema of functions along with your chat completion request, and a server with ability to parse and execute the response. I’m not really seeing where a new layer of abstraction helps here (much less a new “protocol”, as though we need a new transport layer?
It smells like the thinking is that you (the developer) can grab from a collection of very broad data connectors, and the agent will be able to figure out what to do with them without much custom logic in between. Maybe I’m missing something
> It smells like the thinking is that you (the developer) can grab from a collection of very broad data connectors, and the agent will be able to figure out what to do with them without much custom logic in between.
This has always been the idea behind tools/function calling in LLMs.
What MCP tries to solve is the NxM problem - every LLM vendor has their own slightly different protocols for specifying and calling tools, and every tool supplier has to handle at least one of them, likely with custom code. MCP aims to eliminate custom logic at the protocol level.