> I tried to avoid writing this for a long time, but I'm convinced MCP provides no real-world benefit

IMO this is 100% correct and I'm glad someone finally said it. I run AI agents that control my entire dev workflow through shell commands and they are shockingly good at it. the agent figures out CLI flags it has never seen before just from --help output. meanwhile every MCP server i've used has been a flaky process that needs babysitting.

the composability argument is the one that should end this debate tbh. you can pipe CLI output through jq, grep it, redirect to files - try doing that with MCP. you can't. you're stuck with whatever the MCP server decided to return and if it's too verbose you're burning tokens for nothing.

> companies scrambled to ship MCP servers as proof they were "AI first"

FWIW this is the real story. MCP adoption is a marketing signal not a technical one. 242% growth in MCP servers means nothing if most of them are worse than the CLI that already existed

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binsquare 2 hours ago | parent | next [-]

Fully agree.

MCP servers were also created at a time where ai and llms were less developed and capable in many ways.

It always seemed weird we'd want to post train on MCP servers when I'm sure we have a lot of data with using cli and shell commands to improve tool calling.

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kaydub an hour ago | parent | prev | next [-]

I avoid most MCPs. They tend to take more context than getting the LLM to script and ingest ouputs. Trying to use JIRA MCP was a mess, way better to have the LLM hit the API, figure out our custom schemas, then write a couple scripts to do exactly what I need to do. Now those scripts are reusable, way less context used.

I don't know, to me it seems like the LLM cli tools are the current pinnacle. All the LLM companies are throwing a ton of shit at the wall to see what else they can get to stick.

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femiagbabiaka an hour ago | parent | prev | next [-]

How do you segregate the CLI interface the LLM sees versus a human? For example if you’d like the LLM to only have access to read but not write data. One obvious fix is to put this at the authz layer. But it can be ergonomic to use MCP in this case.

	▲	jyaohao 11 minutes ago \| parent [-]
		I’ve been testing with an ENV variable for a cli tool for LLMs that I’m making. Basically, I have a script that sets an ENV variable to launch the TUI that I want and that ENV variable changes the behavior for LLMs if they run it (changes the -h output, changes the default output format to json to make it easier to grep)

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ejholmes 2 hours ago | parent | prev | next [-]

Thanks for reading! And yes, if anyone takes anything away from this, it's around composition of tools. The other arguments in the post are debatable, but not that one.

	▲	p_ing 2 hours ago \| parent [-]
		MCP provides a real-world benefit. Namely anyone of any skill level who can create agents is able to use them. CLI? Nope.

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juped 36 minutes ago | parent | prev [-]

Tools eat up so much context space, too. By contrast the shell tool is trained into Claude.