[brookst]

MCP is a higher layer than your existing API.

It’s like saying APIs are dead because you can just use HTTP. They’re not the same thing, though of course you can hand-roll the higher layer in the lower one. It’s just more work, less standard, less valuable.

I don’t think models will ever prefer a low level API to a decorated index of API features and how to use them, same way developers will never prefer a list of HTTP endpoints and bespoke headers + query strings + POST bodies over a structured API.

[IggleSniggle]

Right; isn't this already captured by an openapi spec with RBACs? Plus the benefit that your ai agent can keep using all the pre-AI tools that already interface with those specs. What is MCP bringing that an openapi spec doesn't?

[ok_dad]

You can build an MCP client really really easy today with libraries and it integrates with inference calls very well. If you want to give a cloud agent access to another api, you need to bills a connector or give it shell access or some sort of sandbox with tools to access that stuff. That’s fine, but how do you then give it auth access? How do you ensure security boundaries? MCP builds those in and the shape (prompts, resources, tools, etc) are good for agentic work.

It’s like asking why we needed browsers when we had BBSes; they serve a different but similar purpose and are build on different abstraction levels.