Paperclip Agent Setup in 3 Minutes: AI Team for $7/mo

I have a team of AI agents running on Paperclip for $7 a month. A CEO breaks down every task and hires the rest of the team. A backend engineer writes code, a frontend engineer builds the UI, and a QA agent reviews everything before it ships. No terminal. No config files. One Docker click and a pasted API key.

The tool is called Paperclip. It's free, open source, and about to cross 59,000 GitHub stars in under three months. I went in expecting a weekend of YAML and yak-shaving. I got a working dashboard in three minutes.

Here's the full setup, the one input that decides whether your team ships anything useful, and the model swap that took my Claude Opus bill from $236 a month down to $11.

What makes Paperclip different#

You don't build the team. You build the CEO.

Every other agent framework I've tried makes you wire up each role: the researcher, the writer, the reviewer, the orchestrator, the memory layer. Paperclip flips it. You set up one agent, the CEO, and you tell it the company's mission. The CEO hires whoever is needed for the task you give it, delegates the work, and reports back when it's done.

In a few minutes I had a software team shipping landing pages, a content pipeline, a lead generation team, and a competitive intelligence team running side by side. Same setup, five different teams, one dashboard.

The 3-minute deploy on Hostinger#

You can run Paperclip on your own machine, but I'd put it on a VPS. It's safer, it's isolated from your local files, and the same VPS can host OpenClaw, n8n, or anything else you want to run later. One server, every tool.

If the coupon doesn't apply on an existing Hostinger account, open the link in an incognito window and it works.

A few things to know:

• Pick your server location, log in or create your account, pay with card or PayPal.
• For the Paperclip config, leave admin name as admin, set your email, and save your admin password.
• For the API key, you can use Anthropic, OpenAI, Gemini, or Cursor. I used OpenAI 5.5 because it just released and it's one of the strongest agentic models right now.
• Click deploy. Watch the Docker container spin up. Sign in. You're done.

That's the whole setup. The dashboard is live and the CEO is waiting for instructions.

The one input that matters: the mission statement#

Paperclip marks the mission statement as optional. It's the most important field on the page.

Every agent the CEO hires refers back to this mission to decide what to do, what to ignore, and how to prioritize. A generic mission ("be a great company") gets you generic output. A specific one gets you a team that actually behaves like a team.

Bad: "Build great products." Better: "Ship a profitable micro-SaaS within 90 days. Prioritize speed of iteration over feature completeness. Default to free-tier infrastructure. Validate with real users before scaling any system."

The second mission tells every future agent what trade-offs to make. The first one tells them nothing.

After the mission, pick your model (Codex/5.5 by default, or Claude Code, Gemini, or Hermes), then write your first task. The default suggestion is "hire an engineer." Skip it. Write something specific like "hire a chief of staff and hand off the 90-day roadmap." Specific tasks produce specific hires.

How the team actually builds itself#

Once the CEO accepts the first task, the dashboard shows it as in-progress. Click the CEO and you see the run activity, the issue priority, and the live status. On the left there's an inbox of items waiting for your approval.

Approve the first chief of staff hire, and the CEO moves on. The chief of staff gets their own task list. They might recommend three passive income streams to test. You read the output, hit "implement the top recommendation as a new issue," and the chain continues.

The dashboard shows every agent, what they're working on, what's been approved, what's been spent, and which tasks succeeded or failed. You're not babysitting individual agents. You're managing a company.

For complex work, the team grows. A SaaS dev shop gets a CTO, a product manager, and a QA engineer. A content agency gets writers, editors, and a publisher. For lighter work, you keep it tight. A competitive intelligence team only needs three agents: a researcher, an analyst, and a report writer. Don't hire what the task doesn't need.

Cutting the API bill from $236 to $11#

This is the part nobody talks about. Agentic frameworks are cheap to set up and expensive to run, because every CEO call, every sub-agent action, and every approval cycle hits the API.

If you're running Claude Opus 4.7 at $25 per million output tokens, a busy team will burn through credits faster than you expect. Mine did.

The fix is OpenRouter. Route the agents through cheaper models that handle agentic work almost as well:

• DeepSeek 4: just launched, very competitive on coding tasks
• Minimax 2.7: strong at agent orchestration specifically
• Kimi K and GLM: both solid alternatives at a fraction of the cost

You can connect OpenRouter directly or hit each model's native API. Either way, you manage them in the same Paperclip dashboard and track total monthly spend in one place. Same team, same outputs, roughly 95% lower cost.

If you want to test the setup first, the free starter guide has the deploy links and a few starter prompts.

What to do first#

Deploy the VPS. Write a specific mission. Hire a chief of staff. Approve the first three outputs by hand so the team learns your standards. Then turn on a cheaper model and let it run.

The point of an agent team isn't to remove yourself from the work. It's to remove yourself from the parts of the work that don't need you.

Watch the full walkthrough on YouTube: https://www.youtube.com/watch?v=JxOPl-b04ZE