Paperclip vs Orca: 2026 comparison

Paperclip and Orca in brief

Paperclip and Orca both help you coordinate multiple agents and keep track of their work. Their emphasis differs from the outset. Paperclip focuses on assigning tasks and monitoring activity within an organizational application. Orca specifically targets coding agents, which you can launch and supervise on a computer, on mobile, or through remote execution. Both projects support self-hosting, use TypeScript, and carry the MIT license. The practical choice therefore starts with the work you need to coordinate and the interfaces you expect to use.

Paperclip : An open source application for organizing agents at work, assigning tasks, and tracking their ongoing activity.

Orca : A workspace for running and supervising multiple coding agents across desktop, mobile, and remote execution environments.

They are often weighed against each other by people who hesitate. This page lines up their features point by point (11 criteria), with no partnership with either publisher.

Comparison table

Criterion by criterion

For each criterion: why it matters, each one's value and who has the edge. A criterion without data on both sides is not decided.

Popularity (GitHub stars)

Stars measure developer interest; a widely followed project has more tutorials, integrations and answers. Paperclip : 106.8K. Orca : 104.7K. Edge: Paperclip.

Activity over a year

Commits over 52 weeks show whether the project moves fast, fixes bugs and keeps up with new models. Paperclip : 5,225 commits. Orca : 20,232 commits. Edge: Orca.

Releases (6 months)

Regular releases signal a project that ships; very frequent releases can also mean frequent updates on your side. Paperclip : 24. Orca : 26. Edge: Orca.

Last commit

A repository with no commit for months may fall behind new APIs and security fixes. Paperclip : October 24, 2026. Orca : October 24, 2026. A tie on this point.

License

A clear open-source license (MIT, Apache…) allows commercial use and modification; without one, usage rights are unclear. Paperclip : MIT. Orca : MIT. A tie on this point.

Self-hosting

Running the agent on your machine or server keeps your files and keys with you. Paperclip : yes. Orca : yes. A tie on this point.

Supported models

An agent that accepts several model families lets you pick the best value, or a local model. Paperclip : not disclosed. Orca : 3. Cannot be decided: data missing on one side.

Interfaces

Terminal, code editor, web app or chat: more interfaces mean more ways to fit it into your work. Paperclip : 2. Orca : 2. A tie on this point.

Risk level

Our risk level considers the access granted (terminal, files, network) and default human approval. Paperclip : low. Orca : low. A tie on this point.

Community (forks)

Forks count developers who copied the project to adapt it: a sign of a living ecosystem. Paperclip : 17.7K. Orca : 6.6K. Edge: Paperclip.

Track record

An older project has had time to fix early flaws; a recent one often brings the latest ideas. Paperclip : March 2026. Orca : March 2026. Edge: Paperclip.

In charts

Our analysis

Paperclip approaches multiple agents as a work organization problem. Its description emphasizes assigning responsibilities and observing activity, without specifying a particular professional field. This makes its stated scope broader than coding alone, although the supplied information does not establish individual workflows. Orca has a more explicit audience: people running and supervising several coding agents. Desktop, mobile, and remote execution are central to that description. These differences clarify the intended use of each project. They do not establish which one completes tasks more successfully, since no task results, execution times, or user feedback are included in the supplied data.

Both repositories show substantial attention and recent development activity. Paperclip has 106,840 stars and 17,745 forks, while Orca has 104,691 stars and 6,612 forks. Their twelve-month commit counters are 5,225 and 20,232 respectively, with 24 and 26 releases over six months. Both list their latest commit as October 24, 2026. Since both projects were created in March 2026, their histories remain relatively short at the comparison date. Their scores of 86 and 91 out of 100 describe popularity, activity, and project framework. Neither score measures software quality or predicts how well an agent will perform your tasks.

The shared MIT license and self-hosting option provide a clear starting point for inspecting the software and choosing its deployment location. However, deployment control does not establish every data flow during use. Neither record explains external transfers or retention practices. Orca explicitly lists Claude, GPT, and Grok as associated models. Paperclip has no models listed, which should be treated as missing information rather than evidence of incompatibility. Human approval mechanisms are undocumented for both projects. Each has a low risk classification with no specific reasons recorded, but that classification does not supply the missing operational or privacy details.

Paperclip offers web and API interfaces, which align with browser access and potential programmatic integration. The available record does not describe the API's scope. Orca lists desktop and mobile interfaces, while its description also mentions remote execution. Your preferred way of supervising agents therefore provides a concrete selection criterion. An API is not listed for Orca in the supplied information, so equivalent integration options cannot be assumed. Neither project has a published price in these records. Total operating costs, deployment requirements, and any additional expenses remain unavailable, preventing a reliable budget comparison based solely on this material.

Depending on your situation

The right choice depends on use. For a few common situations, here are the criteria that matter and who wins (Paperclip value / Orca value).

Trying it out quickly

Here, Paperclip has the edge: it wins 1 of the 3 criteria that matter in this situation, namely interfaces (2 / 2), supported models (not disclosed / 3), and popularity (github stars) (106.8K / 104.7K).

Production use

Here, Orca has the edge: it wins 2 of the 4 criteria that matter in this situation, namely activity over a year (5,225 commits / 20,232 commits), last commit (October 24, 2026 / October 24, 2026), license (MIT / MIT), and releases (6 months) (24 / 26).

Security and control

Neither stands out on the criteria for this situation (risk level (low / low) and self-hosting (yes / yes)): decide with a trial.

Which one to choose?

Choose Paperclip if…

• you value popularity (github stars) (106.8K)
• you value community (forks) (17.7K)
• you value track record (March 2026)

Paperclip is a logical fit when your priority is assigning work across agents and monitoring activity through a web interface. Its listed API also makes it relevant when programmatic integration is part of your plans. MIT licensing and self-hosting provide clear reference points. You will still need more information about supported models and human approval before defining a complete workflow.

Choose Orca if…

• you value activity over a year (20,232 commits)
• you value releases (6 months) (26)

Orca fits a workflow built around several coding agents, particularly when desktop or mobile supervision and remote execution matter to you. Claude, GPT, and Grok are explicitly listed. That makes its intended environment easier to identify if those models are already relevant to your work. Its substantial development activity remains a project signal, rather than evidence of task success.

Strengths and limits of each

Paperclip

• + Widely followed: 106.8K stars
• + Very active development
• + Frequent releases (30 in a year)
• − 3,281 open issues

Orca

• + Widely followed: 104.7K stars
• + Very active development
• + Frequent releases (26 in a year)
• − 4,428 open issues

The best test is still yours: take three real tasks from your day and give them to both for a week. Our “Which AI agent?” quiz can also guide you.

What about the others?

If neither suits you, look at CrewAI, Agno, AgentScope, OpenAI Agents SDK, Eigent, and Microsoft Agent Framework.

Related comparisons:

• LangChain vs Paperclip
• LangChain vs Orca

Conclusion

Choose according to how you intend to organize the work. Paperclip emphasizes task allocation, activity tracking, and web access with an API. Orca explicitly focuses on coding agents, with desktop and mobile interfaces. Both provide MIT licensing and self-hosting. The supplied evidence supports this distinction, but leaves model compatibility details, human approval arrangements, and operating costs insufficiently documented to settle those parts of your decision.