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paperclip ai: How to Set Up the Free, Open-Source App for Managing AI Agents

#ai #opensource #productivity #automation

paperclip ai is trending again on GitHub this week, and a lot of people are searching for a "paperclip ai tutorial" or "paperclip ai setup". If you run a small business or a small dev team and you already use one or more AI coding agents, here's a plain, research-based walkthrough of what Paperclip is, how to install it, and what to watch before you let agents run on their own.

What Paperclip is

According to its GitHub README, Paperclip is "open-source orchestration for teams of AI agents". In practice it's a Node.js server with a React dashboard where you:

  • set a goal for the work,
  • "hire" agents into roles on an org chart ("any bot, any provider", in the README's words),
  • assign tasks, approve plans, set budgets, and watch progress from one place.

It's MIT-licensed and self-hosted, and the README says no Paperclip account is needed. The repo had just over 110,000 stars when we checked the GitHub API today.

It works with agents you may already use. The README lists OpenClaw, Claude Code, Codex, Cursor, Gemini CLI, OpenCode, Pi, Hermes and Kimi Code, among others, plus custom processes and HTTP endpoints.

Quick setup

The README's quickstart needs Node.js 24.11 or newer. Then one command:

npx paperclipai@latest onboard --yes
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The CLI runs from npm's cache, and your instance settings and data stay on your machine. For a local run, the README's FAQ says a single Node.js process manages an embedded PostgreSQL database and local file storage, so there's no separate database to set up. For production you can point it at your own Postgres.

If you'd rather build from source, the README's development steps are pnpm install then pnpm dev, which starts the UI and API at http://localhost:3100 (it needs pnpm 9.15+).

The full installation guide covers pinned versions, updates, rollback and uninstalling.

A simple first project for a small team

Keep the first run small and boring:

  1. One goal, one or two agents. For example, "Clean up our website's FAQ page and open a pull request." Don't start with a company-wide goal.
  2. Turn on review gates. Paperclip has configurable approval stages, so a human checks a plan before work starts.
  3. Set a budget. The README says you can set company, agent and project budgets, get threshold alerts and pause work at a limit. Paperclip itself is free, but the AI models your agents call are not, so set the cap before you hit "go".
  4. Read the task threads. Plans, blockers, files and run history stay attached to each task, which makes it easier to see what an agent actually did.

Things to check before going autonomous

  • Scope the secrets. The README mentions scoped secrets and permissions. Give each agent only the keys and repos it needs.
  • Start in a test repo. Let agents work on a copy before they touch anything customers see.
  • Keep a human on merges. "Approve and run" is the README's own workflow. Keep the approve part.

Is it worth trying?

If you're juggling several agent terminals and losing track of who's doing what, Paperclip is a free way to put that work on one board with budgets and approvals. If you only use one assistant now and then, it's probably more structure than you need today.

This is a research-based overview from the project's own README and docs. We haven't tested Paperclip hands-on yet.

More plain-English AI tool guides for small businesses and creators: ainews.useaifix.com. If you'd like help setting up AI automation for your business, see useaifix.com.

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