How I Built an AI Agent Store on a Raspberry Pi (And You Can Too)
A few months ago, I found myself drowning in repetitive tasks. Between running bug bounty reconnaissance, managing automation scripts, and keeping up with AI tooling, my workflow was a mess. I needed a central hub—a place where I could deploy, manage, and monetize the tools I was building anyway.
That's when I decided to build something different: an AI Agent Store running entirely on a Raspberry Pi.
The Problem with Scattered Tools
Like many developers, I had scripts scattered across GitHub repos, local machines, and cloud instances. Some were Python automations, others were shell scripts for security testing, and a few were AI-powered agents. Each tool worked in isolation, but managing them was a nightmare.
I wanted a unified platform where:
- Tools could be discovered and purchased easily
- Customers got instant access after payment
- I could focus on building, not billing infrastructure
Why Raspberry Pi?
The Raspberry Pi 5 is surprisingly capable. With 8GB RAM, it handles multiple Python processes, web servers, and API endpoints without breaking a sweat. More importantly, it forces you to write efficient code. If it runs well on a Pi, it runs well anywhere.
Plus, there's something satisfying about a production store running on hardware that fits in your palm and costs less than a dinner out.
The Architecture
The stack is deliberately simple:
- Backend: Python (FastAPI for APIs, Celery for background jobs)
- Frontend: Static HTML/CSS with minimal JavaScript
- Payments: LemonSqueezy (handles taxes, VAT, and global compliance)
- Hosting: Raspberry Pi 5 with Cloudflare Tunnel for HTTPS
- Database: SQLite (migrated to PostgreSQL when needed)
The key insight was that I didn't need Kubernetes or AWS for an MVP. A single board computer, a tunnel, and a payment processor were enough to validate the idea.
Building the First Product
The first product I built was an AI Agent Toolkit—a collection of reusable Python modules for building autonomous agents. It includes:
- Web scraping with rate limiting
- LLM integration with multiple providers
- Task scheduling and retry logic
- Logging and monitoring utilities
Instead of open-sourcing everything, I packaged it as a paid product. This might sound counterintuitive, but paid products attract users who are serious about implementation. They're more likely to provide feedback, report bugs, and suggest features.
You can check it out here: AI Agent Toolkit on LemonSqueezy
Lessons Learned
1. Start with Payment Infrastructure
I integrated LemonSqueezy on day one. Knowing that customers could pay and instantly receive access changed how I thought about product development. Every feature became a potential revenue driver.
2. Document Ruthlessly
The biggest complaint I received early on wasn't about bugs—it was about missing documentation. Now every product ships with a README, a quickstart guide, and a troubleshooting section. Documentation is a product feature.
3. Automate Everything
From deployment to customer onboarding, if I did it twice, I automated it. The Raspberry Pi runs cron jobs for backups, health checks, and even social media posting. Automation isn't just for products—it's for operations too.
4. Embrace Constraints
Running on a Pi forced me to optimize. Database queries got faster. Memory leaks got fixed. The entire codebase became leaner because there was no room for bloat.
What's Next
The store now hosts multiple products, from bug bounty automation kits to AI productivity tools. Each one follows the same philosophy: solve a real problem, package it well, and price it fairly.
The Raspberry Pi is still the primary server. It's been running for months without issues, proving that you don't need expensive infrastructure to build a real business.
Your Turn
If you're a developer with side projects sitting in private repos, consider packaging them. You don't need a startup incubator or venture funding. You need:
- A problem you've solved for yourself
- A payment processor (LemonSqueezy, Stripe, etc.)
- A place to host it (a $75 Raspberry Pi works fine)
- The courage to charge for your work
The tools you build for yourself are often exactly what others need. The difference between a side project and a product is simply asking people to pay for it.
Want to see the store in action? Visit https://github.com/ulnit/agent-store for more details.
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