You're right, that snippet was ai-generated and I forgot to action one of my todos to fix that snippet. This was negligent on my part, and I hope you'll forgive me.
We're fixing that right now, thank you for the correction!
This is pretty fair: in claude code, I have the github mcp server installed, but the agent actually prefers to use the CLI. There's also other advantages too, such as incremental discovery of subcommands for more complex CLIs. Certainly agents already don't have a problem using CLIs.
That said, this doesn't fully work in environments on websites like claude.ai. Perhaps you could have an org-wide Dockerfile or something that opens every time you start a chat which gives it MCP-like capabilities, but that sounds more complicated in many ways than what MCP does. There's also more problems that MCP solves, like with Prompts and Sampling (which are pretty under-used at the moment), and there aren't great analogs for that in the CLI world.
Also developers like you and I might find it trivial to install CLIs, set up auth, and open an agent locally, but this isn't widely true. As an example, at Stainless we have non-engineer folks who ask questions like "who are the most interesting people who have signed up yesterday", and with the right MCP tools wired to claude.ai, claude actually does an excellent job of answer these kinds of questions, all in the browser. This was all without a doubt possible before MCP, but MCP reduces the friction enough, such that it becomes worth-it/easy-enough to develop these tools.
> Maybe it was because OpenAI announced they would start to support MCP in their tools ? [0]
Author here, I assumed this would be the reason too, but the timelines don't really match up. Momentum was already strong by the time that OpenAI adopted it. And it's an educated guess on my part, but that's also probably why they adopted it in the first place.
Some sources point to the MCP talk at AI Engineer being the turning point (and the timelines match up), but like with all viral studies the answer is pretty complicated and multi-faceted, rather than having a single cause.
> Perhaps I'm being too harsh with the author, but this article definitely gives me vibes of "AI slop".
I think it's fine to be harsh! I don't like AI slop either but unfortunately this article was mostly handwritten, so it's just a skill-issue on my part. I'll try to do better next time
While true, I think people underestimate the bad network effects of being the top search engines causing adversarial development with people optimizing for your specific search engine algorithm ultimately making results worse.
That's a pretty severe mischaracterization of intersectionality in general. Intersectionality refers to the fact that you can't analyze human experiences as linear terms (being black, being a woman) and that you must consider the effects of being some combination of categories. As an example, intersectionality claims that being both black and a woman brings separate challenges than the additive combination of being black and being a woman.
That's all there is to intersectionality, any conclusions you make beyond that are your interpretation of intersectionality, not the general consensus of the "far left".