alt Hacker News> 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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This was my gut from the beginning. If they can't do "fully observable" or "deterministic" (for what is probably a loose definition of that word) -- then, what's the point?
I hate MCP servers
That said the core argument for MCP servers is providing an LLM a guard-railed API around some enterprise service. A gmail integration is a great example. Without MCP, you need a VM as scratch space, some way to refresh OAuth, and some way to prevent your LLM from doing insane things like deleting half of your emails. An MCP server built by trusted providers solves all of these problems.
But that's not what happened.
Developers and Anthropic got coked up about the whole thing and extended the concept to nuts and bolts. I always found the example servers useless and hilarious.[0] Unbelievably, they're still maintained.
[0]: https://github.com/modelcontextprotocol/servers/tree/main/sr...
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.
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.
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.
Tools eat up so much context space, too. By contrast the shell tool is trained into Claude.
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.