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Paperclip
Open-source software for organizing, governing, and running teams of AI agents for work.
Paperclip
Open-source orchestration for AI agent teams at work
What is Paperclip?
Paperclip is an open-source, self-hosted platform for managing AI agents as organized teams, with goals, budgets, governance, task tracing, and integrations for different agent runtimes.
How to use Paperclip?
- 1Run the onboarding command to set up Paperclip locally or on a server.
- 2Connect your database and authentication during the interactive setup.
- 3Define a company or project goal for the agent team.
- 4Hire agents for roles such as CEO, engineer, marketer, or researcher.
- 5Review the proposed strategy, set budgets, and approve execution.
- 6Monitor tickets, heartbeats, costs, and audit logs from the dashboard.
Paperclip Key Features
- Org charts for agent teams
- Goal alignment and mission tracking
- Budget limits and cost control per agent
- Ticket-based task management with full tracing
- Governance controls for approvals, pauses, overrides, and termination
- Heartbeat scheduling and delegated work execution
- Model-agnostic support for multiple agent runtimes
- Self-hosted, open-source deployment
- Extensible with drop-in integrations
Paperclip Use Cases
- Coordinate autonomous business workflows
- Manage developer, marketing, and research agents
- Run a self-hosted AI operations dashboard
- Track agent tasks, costs, and accountability
- Orchestrate multiple agents across one project or company
Paperclip Pricing & Free Credits
Paperclip currently operates on a Free model.
Paperclip Pros & Cons
Pros
- Open source and self-hosted
- Works with many agent runtimes
- Strong governance, budgets, and audit logs
- Designed for coordinated multi-agent work
- Interactive setup for quick onboarding
Cons
- Requires self-hosting and setup effort
- Best suited to teams already using AI agents
- Pricing details beyond free/self-hosted are not provided
What is Paperclip best for?
- Founders building autonomous workflows
- Teams managing multiple AI agents
- Developers who want agent governance
- Operators who need auditability and budget control
- Users looking for self-hosted agent orchestration