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SilverElfinyesterday at 8:54 PM1 replyview on HN

This came up in recent discussions about the Google apps CLI that was recently released. Google initially included an MCP server but then removed it silently - and some people believe this is because of how many different things the Google Workspace CLI exposes, which would flood the context. And it seemed like in social media, suddenly a lot of people were talking about how MCP is dead.

But fundamentally that doesn’t make sense. If an AI needs to be fed instructions or schemas (context) to understand how to use something via MCP, wouldn’t it need the same things via CLI? How could it not? This article points that out, to be clear. But what I’m calling out is how simple it is to determine for yourself that this isn’t an MCP versus CLI battle. However, most people seem to be falling for this narrative just because it’s the new hot thing to claim (“MCP is dead, Long Live CLI”).

As for Google - they previously said they are going to support MCP. And they’ve rolled out that support even recently (example from a quick search: https://cloud.google.com/blog/products/ai-machine-learning/a...). But now with the Google Workspace CLI and the existence of “Gemini CLI Extensions” (https://geminicli.com/extensions/about/), it seems like they may be trying to diminish MCP and push their own CLI-centric extension strategy. The fact that Gemini CLI Extensions can also reference MCP feels a lot like Microsoft’s Embrace, Extend, Extinguish play.


Replies

jswnyyesterday at 9:15 PM

MCP loads all tools immediately. CLI does not because it’s not auto exposed to the agent, got have more control of how the context of which tools exist, and how to deliver that context.

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