Given some of the caveats I mentioned towards the end of the article I'd be a bit wary putting too much trust in LLMs for this use case at this stage. But the field is moving so fast that I don't doubt it will soon be less error prone than a human doing it.
Yeah it's not ideal, but it mostly works - at least in this case. I think each MCP tool works best when it can be kept lean and needs only a small number of arguments.
There's basically a couple of different ways to implement an MCP server - for this demo it's a local binary that communicates over stdio, so no OAuth process is taking place. It's only meant to run on your local machine.
To make the demo simpler to explore and understand, the binary loads it's configuration (SnapTrade API client id, secret, and username and secret) from a .env file that you populate with your credentials which allows it to fetch the right data.
I setup a project somewhat along these lines with a Raspberry Pi, a USB DAC, and spotifyd. Now I have a decent and convenient audio player hooked up to my sound system. May not pass all the bars for an audiophile but the sound quality is actually fairly decent - much better than my previous Alexa setup - which is all I needed.
I find it odd to brand it as "explicitly anti-Albanian" when the very article that was linked says
> With the end of the "Skopje 2014" project, not only the Macedonian nationalist hungry spirit was fed. Its counterpart, Albanian nationalism, got its part of the city to ill-treat, so the neighbouring Skanderbeg Square was turned into a nationalist showcase for another actor of the Macedonian ethnocratic elite.
I've used Ollama to run Llama 2 (all variants) on my 2020 Intel MacBook Pro - it's incredibly easy. You just install the app and run a couple of shell commands. I'm guessing soon-ish this model will be available too and then you'd be able to use it with the Continue VS Code extension.
Edited to add: Though somewhat slow, swap seems to have been a good enough replacement for not having the loads of RAM required. Ollama says "32 GB to run the 13B models", but I'm running the llama2:13b model on a 16 GB MBP.
I recently took to rewriting what should be a very simple app from Obj-C to Swift with SwiftUI - because it's the future. The CPU usage was at 5% while idle, just for having a simple tiny pie chart that updates. Not to mention that for some seemingly basic things I still had to use AppKit anyway.
Wrote basically the exact same thing 1 day later in Swift with AppKit and NO SwiftUI and it sits at 0% CPU usage with less code complexity. Maybe in a few years I will give SwiftUI another try.
I use VS Code's native integration with WSL. So VS Code runs as a native Windows app with nearly everything you'd expect, but the actual files being read/saved are inside WSL. Works great with Vagrant, Docker for Desktop, Git etc.