I think that the github repo's README may be more useful: https://github.com/webmachinelearning/webmcp?tab=readme-ov-f...
Also, the prior implementations may be useful to look at: https://github.com/MiguelsPizza/WebMCP and https://github.com/jasonjmcghee/WebMCP
> Integrating agents into it prevents fragmentation of their service and allows them to keep ownership of their interface, branding and connection with their users
Looking at the contrived examples given, I just don't see how they're achieving this. In fact it looks like creating MCP specific tools will achieve exactly the opposite. There will immediately be two ways to accomplish a thing and this will result in a drift over time as developers need to take into account two ways of interacting with a component on screen. There should be no difference, but there will be.
Having the LLM interpret and understand a page context would be much more in line with assistive technologies. It would require site owners to provide a more useful interface for people in need of assistance.
The problem is fundamentally that it's difficult to create structured data that's easily presentable to both humans and machines. Consider: ARIA doesn't really help llms. What you're suggesting is much more in line with microformats and schema.org, both of which were essentially complete failures.
LLMs can already read web pages, just not efficiently. It's not an understanding problem, it's a usability problem. You can give a computer a schema and ask it to make valid API calls and it'll do a pretty decent job. You can't tell a blind person or their screen reader to do that. It's a different problem space entirely.