--- title: "lobehub vs orca" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/lobehub-lobehub-vs-stablyai-orca" tools: ["lobehub-lobehub", "stablyai-orca"] --- # lobehub vs orca Neutral, constraint-first comparison with live GitHub stats. | | [lobehub](/tools/lobehub-lobehub.md) | [orca](/tools/stablyai-orca.md) | | --- | --- | --- | | Tagline | Your Chief Agent Operator for organizing agents into continuous operations | The AI Orchestrator for 100x builders | | Stars | 79,597 | 13,788 | | Forks | 15,565 | 931 | | Open issues | 586 | 1,180 | | Language | TypeScript | TypeScript | | Adopt for | LobeHub is designed as a Chief Agent Operator, focusing on orchestrating AI agents into continuous operations through tasks such as hiring, scheduling, and reporting. | Orca is an AI Orchestrator designed to run a fleet of parallel agents across multiple workspaces, offering mobile access for monitoring and control in real-time. Ideal for teams looking to manage complex coding tasks and | | Persona | - | - | | Runtime | - | - | | License | Other | MIT | | Categories | AI Agents | AI Agents, Developer Tools | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [lobehub](/tools/lobehub-lobehub.md) | [orca](/tools/stablyai-orca.md) | | --- | --- | --- | | Open issues (now) | 586 | 1.2k | | Security scan | No MCP manifest | Not scanned | | Full report | [trust report](/tools/lobehub-lobehub/trust.md) | [trust report](/tools/stablyai-orca/trust.md) | **Typed relationship:** lobehub _(alternative)_ orca Lobehub acts as an organizing system for continuous operations of agents which is somewhat similar but different in scope than Orca’s orchestration capabilities. ## Decision facts: lobehub - **Requirements:** LobeHub supports deployment via Vercel, Zeabur, Sealos, or Alibaba Cloud. It can also be deployed using Docker. - **Adopt for:** LobeHub is designed as a Chief Agent Operator, focusing on orchestrating AI agents into continuous operations through tasks such as hiring, scheduling, and reporting. - **Runtime:** unknown ## Decision facts: orca - **Adopt for:** Orca is an AI Orchestrator designed to run a fleet of parallel agents across multiple workspaces, offering mobile access for monitoring and control in real-time. Ideal for teams looking to manage complex coding tasks and ## Choose when ### Choose lobehub if… - License: lobehub is Other, orca is MIT. - Requirements: LobeHub supports deployment via Vercel, Zeabur, Sealos, or Alibaba Cloud. It can also be deployed using Docker.. - Lobehub acts as an organizing system for continuous operations of agents which is somewhat similar but different in scope than Orca’s orchestration capabilities. - Tags unique to lobehub: agent-collaboration, ai, chief-agent-operator, agent. - lobehub ships Docker support for self-hosted deployment. - lobehub ships an MCP server manifest. - If you need around-the-clock management of your AI team. ### Choose orca if… - License: orca is MIT, lobehub is Other. - Lobehub acts as an organizing system for continuous operations of agents which is somewhat similar but different in scope than Orca’s orchestration capabilities. - Tags unique to orca: cursor-agent, agent-ide, devtools, codex. - Also covers Developer Tools. - You need to orchestrate and monitor the execution of multiple AI coders or agents simultaneously. ## When NOT to use lobehub - If only single agent management is needed; LobeHub's strength lies in orchestrating multiple agents. - When the operational environment does not require continuous (24/7) operations of AI agents as LobeHub focuses on providing that constant availability. - For users who prefer open-source alternatives with extensive community support, given its license isn’t explicitly marked as open-source. ## When NOT to use orca - If your project requirements do not include orchestrating multiple agents or benefiting from real-time remote monitoring capabilities. - When you do not need extensive workspace isolation between different worktree branches managed as separate AI coding agents. - Your needs are best served by a single-agent ADE without advanced orchestration features. ## Common questions ### What is the difference between lobehub and orca? lobehub: Your Chief Agent Operator for organizing agents into continuous operations. orca: The AI Orchestrator for 100x builders. See the comparison table for live GitHub stats and shared categories. ### When should I choose lobehub over orca? Choose lobehub over orca when License: lobehub is Other, orca is MIT; Requirements: LobeHub supports deployment via Vercel, Zeabur, Sealos, or Alibaba Cloud. It can also be deployed using Docker.; Lobehub acts as an organizing system for continuous operations of agents which is somewhat similar but different in scope than Orca’s orchestration capabilities; Tags unique to lobehub: agent-collaboration, ai, chief-agent-operator, agent; lobehub ships Docker support for self-hosted deployment; lobehub ships an MCP server manifest; If you need around-the-clock management of your AI team. ### When should I choose orca over lobehub? Choose orca over lobehub when License: orca is MIT, lobehub is Other; Lobehub acts as an organizing system for continuous operations of agents which is somewhat similar but different in scope than Orca’s orchestration capabilities; Tags unique to orca: cursor-agent, agent-ide, devtools, codex; Also covers Developer Tools; You need to orchestrate and monitor the execution of multiple AI coders or agents simultaneously. ### When should I avoid lobehub? If only single agent management is needed; LobeHub's strength lies in orchestrating multiple agents. When the operational environment does not require continuous (24/7) operations of AI agents as LobeHub focuses on providing that constant availability. For users who prefer open-source alternatives with extensive community support, given its license isn’t explicitly marked as open-source. ### When should I avoid orca? If your project requirements do not include orchestrating multiple agents or benefiting from real-time remote monitoring capabilities. When you do not need extensive workspace isolation between different worktree branches managed as separate AI coding agents. Your needs are best served by a single-agent ADE without advanced orchestration features. ### Is lobehub or orca more popular on GitHub? lobehub has more GitHub stars (79,597 vs 13,788). Stars measure visibility, not whether either tool fits your constraints. ### Are lobehub and orca open source? Yes - both are open-source projects on GitHub (lobehub: Other, orca: MIT). ### Where can I find alternatives to lobehub or orca? GraphCanon lists graph-backed alternatives at /tools/lobehub-lobehub/alternatives and /tools/stablyai-orca/alternatives (/tools/lobehub-lobehub/alternatives.md, /tools/stablyai-orca/alternatives.md), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at /compare/lobehub-lobehub-vs-stablyai-orca.md mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, lobehub or orca? lobehub: Very active. orca: Very active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for lobehub and orca? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: lobehub: /tools/lobehub-lobehub/trust; orca: /tools/stablyai-orca/trust. --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=lobehub-lobehub`](/api/graphcanon/graph?tool=lobehub-lobehub) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_