How to make vibe coding not suck…

Key Takeaways

Last week, I was looking for some software to solve a very specific problem. Lo and behold, I found this great app for 10 bucks. But as a Vibe engineer, I didn't pay for it. Instead, I spent 3 days, $500 in claude credits, and missed my kids' baseball game over the weekend to build a crappier version from scratch. Developers are living in weird times as some of us are becoming less productive and ditching AI altogether. Like the streamer coding garden just completely destroyed the grift in this video. >> And it's not fun. It's not fun at all. But many others are going allin and seeing productivity gains like never before. Every employee at multi-trillion dollar company Nvidia is now AI enabled. >> Every one of our engineers 100% is now assisted by AI coders and our productivity has gone up incredibly. >> The truth is that AI does suck. It's like gambling. When you prompt it and the code actually works, you feel that indescribable rush of dopamine. >> I'm coming day and night. I mean, it's terrific. But eventually your prompt won't work and this leads to a vicious cycle that I like to call the prompt treadmill of hell where you keep burning through credits but never actually get what you need. Despite that drawback, there are ways to make AI coding more reliable and quasi deterministic thanks to the power of model context protocol servers. In today's video, we'll look at seven MCP servers every dev needs to know about to make AI coding suck less. It is October 14th, 2025, and you're watching the code report. I think it's safe to say that the majority of programmers are now using AI in some capacity, but very few are using it to its full potential. If you don't already have a couple of MCP servers hooked up to claude code, cursor, open code, or whatever you prefer, you're falling behind and you're not going to make it. But what even is a model context protocol server? Well, in one sentence, it's a standardized way for your coding agent to talk to external systems. That could be an app running on your local machine. It could be a remote server that runs your code. or it could be a thirdparty API. To understand its full potential, let's look at some examples. On this channel, I've complained endlessly about AI not being able to generate proper spelt 5 code. Well, luckily, just a few days ago, that problem has been solved thanks to the release of the spelt MCP server. All you have to do is install this bad boy in your favorite coding tool, like I'm using Claude Code here. And now, instead of going in blind, you can start a prompt with /spelt. This will automatically tell Claude how to get the right spelt documentation. And more importantly, use the spelt autofixer. It'll perform a static analysis on the code and delopify it when the LLM hallucinates random ReactJS code in your project. But if you're a front-end developer, the most time-conuming task is implementing your designer's Figma files into actual code. Well, not anymore. The Figma MCP server allows you to connect your local Figma app on the desktop or in the cloud. It'll pull a design file and automatically implement it in HTML and CSS. You can even generate React components, use Tailwind, or build iOS UI elements using Figma's more reliable tooling. Pretty cool. But what if you're building something like a payment system with a third-party API? If this is something you really can't afford to screw up, well, Stripe and many other APIs now have an MCP server that can fetch documentation for the exact API version you're using. Not only that, but it has a long list of tools you can use to access live data in Stripe, opening the door to all sorts of possibilities, like accidentally refunding 10,000 customers with a single prompt. Now, even if you leverage these tools, your code is still probably going to break in unexpected ways at runtime. If you use a monitoring tool like Sentry, you can access all of the issues and errors your AI assistant missed before deploying. Instead of trying to understand the slop you rolled out a few minutes ago, you just tell it to query the Sentry issues and fix them on the fly. That's helpful, but not all runtime issues can be caught. At other times, it might be the QA guy who worked at Blizzard for 7 years who assigns you a Jira ticket to fix some pointless edge case he found, in which case you'll want to have the Atlassian or GitHub MCP server installed. You can use it to automatically pull issues and tickets without ever needing to read them yourself. Just run a prompt that tells the AI to fix the issue and close the ticket while you sit on the train reading your favorite book. That's awesome. And if you follow this guide, you'll eventually have a billion-dollar app that requires more infrastructure to scale. There are now MCP servers for AWS, Cloudflare, Verscell, and many others that can let AI provision the actual resources you use in the cloud. In theory, the great thing about robots is that they won't forget to shut down an EC2 instance that will destroy your finances, but don't quote me on that. So far, all the examples we've looked at require the trust of a third party developer. So, you have to trust us. Just relax and fall. One, two, three. No. >> What's cool about this protocol, though, is that it's essentially standardized now. And you can use it to build your own highly specialized server. Like maybe you want a server that can look up custom data sources, manage your smartome, or really anything you can imagine. And they're easy to build because there's now an MCP framework for every major programming language out there. But after you build one, you'll need a place to deploy it. And an awesome platform you need to know about is Savala, the sponsor of today's video. It's a modern successor to Heroku that combines Google Kubernetes Engine with Cloudflare to give you a simple way to deploy full stack applications, databases, and static sites without drowning in YAML configs. We can easily ship our app by connecting a Git repo in the Savala dashboard or by selecting one of their pre-built templates. Once it's live, you get app analytics, environment variables, and everything else you need to scale your app. You also get real environment pipelines for preview, staging, and production, so your team can promote changes safely instead of just praying to the prod gods. So try out Savala for free with $50 in free credits using the link below. This has been the Code Report. Thanks for watching and I will see you in the next