Edit: this of course says nothing about MCP vs API/CLI in general. It’s just a bad implementation by Linear.

1: https://thebiglog.com/links/linear-cli-instead-of-linear-mcp

Comments URL: https://news.ycombinator.com/item?id=49785657

Points: 1

# Comments: 0

It’s more inhibiting to me than bad code, missing tests, or an obvious or non-obvious suboptimal solution.

I don’t think it’s easy on native speakers when it happens, but it’s even harder when you’re not.

Edit: just noticed this is not retroactive. Still concerning looking forward.

> I have never been a big fan of pull requests.

I guess this partly explains why Zed (still) lacks a PR review flow, let alone a coherent one, despite some interest [1]. Pretty much the only reason I’m still with JetBrains.

[1]: https://github.com/zed-industries/zed/discussions/34759

If tomorrow I decide not to share with anyone, I don’t want to have to reconfigure stuff. I simply edit the Tailscale policy file, and (maybe) spin down my server.

With Tailscale, you can basically point a domain to the FQDN of a machine you’re sharing with people and the domain will simply work for them (and only them)[1]. But for it to work without them having to know or specify the specific application port, you have to grant them access to 443 (and 80) in your Tailscale ACL for that specific host.

So yeah, now immich.familydomain.com works without family members having to remember the specific port. BUT, serveradmin.familydomain.com (another app on the same host) will ALSO be accessible to them (from a networking POV). We opened port 443/80 for that host after all.

I took a few hours with Claude back in January (?) and we wrote a tiny Go authorization gateway which basically consults both Tailscale’s public API and Tailscale’s `localapi` and returns the appropriate response to Caddy based on the requesting user’s actual allowed ports.

So now I can share different apps (subdomains) with different people without forfeiting access controls, all driven by Tailscale’s policy file.

(I hope I didn’t mess up the crux of it, pretty late here)

Edit: why not (something like) Authentik? Quoting from the draft:

  I contemplated this for a bit but one thing I kept thinking about is:

  _They're already logged in to Tailscale_

  Why do I need to install and configure another full-blown app dedicated to doing something Tailscale already did? Why have the users go through two hops of authentication?”

I tried talking to him multiple times to no avail. He’d basically say “yeah I’ll pay attention no problem” but nothing changed for weeks.

Coincidentally at that time I was working morning shifts at a radio station. Those start really early so you gotta wake up at around 4am.

I decided one day to change my alarm (triggered on my Sony Vaio) from the peaceful iPhone-like tunes to System of a Down’s “Chop Suey”. I also decided to forget it on, on repeat, full volume, while leaving the apartment.

I don’t think 3 days passed before he knocked loudly at my door, moaning and complaining.

I told him: “you gotta understand, your TV was so loud I couldn’t sleep for nights on end, the old tune wouldn’t wake me up anymore. I had to change it. I’m so tired that I even forget to turn it off.

But yeah, I’ll try to pay attention to it”

I’ve been doing tedious manual entry for a bit over two years now and after having missed three consecutive months, the only other option was to bail.

As a start it should help with 3 main things:

- Translation, categorization: my source documents aren’t in English but my GnuCash entries are. This is one of the reasons I don’t use the built-in imports. (This should shave off at least 90% of time spent entering data)

- Human-error prevention: there were at least 5 times where it took me over 15 minutes to reconcile a discrepancy because I entered some number or some account wrong somewhere.

Their V1 API (not Paddle “Billing”) is…not the best I’ve used.

[1] I didn't know about the 3-sales precondition either. I guess some people bought albums on Amazon on my other music-related app.

TVs are much less of a “commodity” of course, but it’s a nice experiment that I’ll iterate on a bit more with time. Also, first deploy on Railway (was nice enough, definitely compared to Heroku, but they have a way to go), and using other libraries I wanted to learn.

Will probably start grouping models better soon, and offer other filters.

BTW: If you plan to do something like this with PAAPI (Product Advertising API), know that Amazon has the constant axe of banning you if you don’t generate “qualified” sales for 30 days straight.