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▲ zzbzq 4 hours ago

Last I checked it still doesn't. A skill that tells your client to call a CLI, and uses the help menus for progressive disclosure, benchmarks better. Developers noticed this immediately and there is sort of an anti-MCP sentiment. The protocol was probably largely conceived for non-coding agents run by non-coders.

In theory the agents could just natively know how to do this better, to get exactly the composability you want. In fact, you could probably just write a CLI mcp-caller and tell the agent to only call MCPs via that, and boom you're done.

Where MCP does come back into the picture even for coders is a more controlled way to break a sandbox.

What I will also say is it matters less and less. It's the usual bitter lesson. The models are just getting so much better all attempts to optimize everything are a drop in the bucket.

▲jameshart 2 hours ago | parent [-]

Too much exposure to local coding assistants seems to lead developers to assume that all agents typically operate in an environment where they have a full shell, with the ability to write arbitrary python scripts and curl commands and execute them.

Consider an agent which doesn’t have those tools though. MCPs are a great way to give them constrained access to remote resources.

▲ndriscoll 2 hours ago | parent [-]

It's more that I'd immediately ask why they don't. Obviously having some interpreter is going to make the model much more capable of context management and just analysis, so at the very least, it should be able to pipe MCP calls into e.g. a python interpreter with no IO other than stdin/stdout.