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Do you want to turn your Claude Desktop into a Full-Stack AI Co-Founder — without changing context or paying a single rupee?
Here’s how.
As developers, we lose hours every day switching tabs between terminal, VS Code, GitHub, Supabase, and Vercel. What if ONE local server handled all of that inside your chat?
Presenting Causly Server 🛠️ — A dedicated server built for full-stack developers, students, and solo founders.
It connects your local chat directly to your core dev stack so you can prompt your way from idea to live deployment:
📁 Files & Folders: Read, edit, create, or delete local code
💻 Shell Execution: Run tests, install npm packages, execute terminal commands
🐙 Git & GitHub: Commit, push code, manage issues, and create PRs
🗄️ Supabase: Provision databases & handle backend setups
🚀 Vercel: Deploy your frontend live on custom domains
Everything runs 100% locally on your machine. Zero subscription fees, zero third-party latency, and complete control over your code and credentials.
All you need to do is run one quick setup command, follow the step-by-step README, and let your AI co-founder start shipping with you.
📂 GitHub Repo & Setup: github.com/KNIHAL/causly-server
Drop a ⭐️ if you're ready to stop context-switching and start shipping faster!
The network for creativity
Join 1.25M professional creatives like you
Connect with clients, get discovered, and run your business 100% commission-free
Creatives on Contra have earned over $150M and we are just getting started
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Hey Contra 👋
Two months ago I posted Promptly here as a work-in-progress and said I'd launch in about three weeks.
Then a health issue knocked me flat, and the three-week plan was gone.
I'm good now — and as of today, the build is done. I just published the full case study as well.
Quick recap: after shipping 20+ projects as a tech lead, I kept watching the same thing break. A founder says one thing, the developer hears another, and a month in, the whole build is based on a misunderstanding nobody caught early.
Promptly closes that gap. You describe your idea in plain English; the AI interviews you, pushes back on the vague parts, and writes a developer-ready spec while you chat.
But the chat is the easy part. The real engineering is everything that stops the AI from being trusted too much:
→ It never touches the database. 16 agents can only propose changes through typed tool calls; backend code checks each one, and invalid calls get rejected and logged.
→ Nothing ever gets lost. It snapshots before anything risky, so you can roll back a single module or the whole project.
→ Spend is capped, always. Every AI call passes four checks before it fires, and each one is logged with its exact cost.
One line sums up the architecture:
The AI proposes. The code decides.
The model gets to be creative. It never gets to be in charge.
Full case study is on my profile, and the product is live if you want to poke at it.
One question:
Shipped anything with LLMs in production? What guardrail saved you — or what missing one burned you?
Every comment on the last post shaped what got built. Thank you for that 🙏
building solo, in public
Congrats on shipping! Love the emphasis on hard guardrails and deterministic validation. That’s exactly how you build trust with LLMs. Excited to poke around the build.
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