Comment by egeozcan
7 days ago
What are the advantages of using an environment that doesn't have access to a CLI, only having to run/maintain your own server, or pay someone else to maintain that server, so AI has access to tools? Can't you just use AI in the said server?
The advantage is that I can have it in my pocket.
gateway agent is a thing for many months now (and I don't mean openclaw, that's grown into a disaster security wise). There are good, minimal gateway agents today that can fit in your pocket.
Why can't you have the agent running on its own server/vm in your pocket?
Obvious example is a corporate chatbot (if it's using tools, probably for internal use). Non-technical users might be accessing it from a phone or locked-down corporate device, and you probably don't want to run a CLI in a sandbox somewhere for every session, so you'd like the LLM to interface with some kind of API instead.
Although, I think MCP is not really appropriate for this either. (And frankly I don't think chatbots make for good UX, but management sure likes them.)
Why are they not calling APIs directly with strictly defined inputs and outputs like every other internal application?
The story for MCP just makes no sense, especially in an enterprise.
MCP is an API with strictly defined inputs and outputs.
10 replies →
MCP really only makes sense for chatbots that don’t want to have per session runtime environments. In that context, MCP makes perfect sense. It’s just an adapter between an LLM and an API. If you have access to an execution engine, then yes CLI + skills is superior.
3 replies →
> and you probably don't want to run a CLI in a sandbox somewhere for every session
You absolutely DO want to run everything related to LLMs in a sandbox, that's basic hygiene
You're missing their point, they're saying that you'd need a sandbox -> it'd be a pain -> you don't want to run a CLI _at all_
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