alt Hacker News"MCP is less discoverable than a CLI" - that doesn't make any sense in terms of agent context. Once an MCP is connected the agent should have full understanding of the tools and their use, before even attempting to use them. In order for the agent to even know about a CLI you need to guide the agent towards it - manually, every single session, or through a "skill" injection - and it needs to run the CLI commands to check them.
"MCPs needs to implement stateful behavior" - also doesn't make any sense. Why would an MCP need to implement stateful behavior? It is essentially just an API for agents to use.
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>"MCP is less discoverable than a CLI" - that doesn't make any sense in terms of agent context. Once an MCP is connected the agent should have full understanding of the tools and their use, before even attempting to use them. In order for the agent to even know about a CLI you need to guide the agent towards it - manually, every single session, or through a "skill" injection - and it needs to run the CLI commands to check them.
Knowledge about any MCP is not something special inherent in the LLM, it's just an agent side thing. When it comes to the LLM, it's just some text injected to its prompting, just like a CLI would be.
If you have an API with thousands of endpoints, that MCP description is going to totally rot your context and make your model dumb, and there's no mechanism for progressive disclosure of parts of the tool's abilities, like there is for CLIs where you can do something like:
tool --help
tool subcommand1 --help
tool subcommand2 --help
man tool | grep "thing I care about"
As for stateful behavior, say you have the google docs or email mcp. You want to search org-wide for docs or emails that match some filter, make it a data set, then do analysis. To do this with MCP, the model has to write the files manually after reading however many KB of input from the MCP. With a cli it's just "tool >> starting_data_set.csv"