That's not what this is. MCP is still around and useful- skills are tailored prompt frameworks for specific tasks or contexts. They're useful for specialization, and in conjunction with post-training after some good data is acquired, will allow the next generation of models to be a lot better at whatever jobs produce good data for training.
I have seen ~10 IQ points drop with each MCP I added. I have replaced them all with either skill-like instructions or curl calls in AGENTS.md with much better "tool-calling" rate.
It isn't particularly useful. It uses a lot of context without a lot of value. Claude has written a blog post saying as much. Skills keep the context out unless it's needed.
It's a much better system in my experience.
Local tools/skills/function definitions can already invoke any API.
There's no real benefit to the MCP protocol over a regular API with a published "client" a local LLM can invoke. The only downside is you'd have to pull this client prior.
I am using local "skill" as reference to an executable function, not specifically Claude Skills.
If the LLM/Agent executes tools via code in a sandbox (which is what things are moving towards), all LLM tools can be simply defined as regular functions that have the flexibility to do anything.
I seriously doubt MCP will exist in any form a few years from now