Skip to content

Latest commit

 

History

History
87 lines (60 loc) · 4.14 KB

File metadata and controls

87 lines (60 loc) · 4.14 KB

Paperclip Introduction

What is Paperclip?

Paperclip is an open-source AI agent orchestration platform that models your AI operations as a company. Instead of managing a pile of disconnected scripts and terminal tabs, you define an org chart with roles, reporting lines, budgets, and governance policies, then let your agents work autonomously within that structure.

Created by @dotta and launched in March 2026, Paperclip crossed 30,000 GitHub stars within three weeks, making it one of the fastest-growing open-source agent projects of the year.

Core Philosophy

Agents as a Company

Most multi-agent frameworks ask you to think about agents as pipelines: nodes in a graph, workers in a queue. Paperclip takes a different angle. Your agents are a company. There is a CEO agent that receives goals and delegates, Engineers that execute tasks, and QA agents that review outputs. The coordination happens through projects and issues, just like a real development team.

Governance by Default

Every agent has a role, a budget, and a manager. Actions are bounded by governance policies. You get audit trails, cost tracking, and state recovery out of the box.

Heartbeat Execution

Agents are not always-on processes. They wake up on a schedule, check for work, execute actions, and report back. Delegation flows up and down the org chart. This makes costs predictable and behavior observable.

Core Features

Organizational Structure

  • Org Charts: Define reporting structures and authority levels.
  • Role-Based Agents: CEO, CTO, Engineer, QA, Researcher — each with clear responsibilities.
  • Goal Alignment: Every task traces back to a company mission. Agents know not just what to do, but why.

Budget & Cost Control

  • Per-Agent Budgets: Set monthly spending limits per agent or team.
  • Automatic Throttling: Agents stop when they hit budget caps. No runaway token consumption.
  • Cost Analytics: Track API costs across the entire organization.

Multi-Agent Coordination

  • Inter-Agent Communication: Structured messaging between agents.
  • Manager Agents: Supervisory agents that review and approve sub-agent work.
  • Shared Context: Agents understand what others are doing to avoid duplicate work.

Broad Agent Backend Support

  • Supported Runtimes: OpenClaw, Claude Code, Codex, and custom agents.
  • Extensible Architecture: Bring your own agent implementation.

Quick Start

Self-Hosted Installation

git clone https://github.com/paperclipai/paperclip.git
cd paperclip
docker compose up -d

Basic Usage

  1. Access Dashboard: Open the web UI in your browser.
  2. Define Company: Create an org chart with roles and reporting lines.
  3. Set Budgets: Assign monthly budgets to each agent or team.
  4. Create Goal: Define a high-level company goal.
  5. Let Agents Work: The CEO agent decomposes the goal and delegates to sub-agents.

Common Use Cases

Automated Software Development

Set up an AI company with a CTO agent, multiple Engineer agents, and a QA agent. Assign a product goal and let them design, implement, test, and review code autonomously.

Research & Analysis Teams

Deploy a Research Director agent with specialized researcher agents. They divide topics, gather information, cross-check findings, and compile reports.

Content Production Pipelines

Create a content team with Writer agents, Editor agents, and SEO agents. They collaborate on drafts, revisions, and publication-ready content.

Comparison with Similar Tools

Tool Focus Key Difference
Paperclip AI agents as a company Org charts, budgets, governance, heartbeat execution
Multica AI agents as teammates Task assignment, progress tracking, skill reuse
OpenClaw Single autonomous agent Depth: memory, planning, messaging platforms
LangGraph Agent workflow graphs Code-level DAG orchestration

Related Resources

License

Paperclip is open-source under the MIT License.