--- title: "awesome vs OpenSwarm" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/sindresorhus-awesome-vs-unohee-openswarm" tools: ["sindresorhus-awesome", "unohee-openswarm"] --- # awesome vs OpenSwarm *GraphCanon updated Jul 12, 2026* ## Verdict Pick awesome when license: awesome is CC0-1.0, OpenSwarm is MIT; pick OpenSwarm when license: OpenSwarm is MIT, awesome is CC0-1.0. [awesome](https://github.com/sindresorhus/awesome) reports 484k GitHub stars, 36k forks, and 92 open issues, last pushed Jun 30, 2026. [OpenSwarm](https://github.com/unohee/OpenSwarm) has 817 stars, 141 forks, and 0 open issues, last pushed Jul 11, 2026. Figures are from public GitHub metadata via [awesome's repository](https://github.com/sindresorhus/awesome) and [OpenSwarm's repository](https://github.com/unohee/OpenSwarm). | | [awesome](/tools/sindresorhus-awesome.md) | [OpenSwarm](/tools/unohee-openswarm.md) | | --- | --- | --- | | Tagline | 😎 Curated list of awesome topics including hardware resources | Autonomous AI dev team orchestrator powered by Claude Code CLI. | | Stars | 484,026 | 817 | | Forks | 35,799 | 141 | | Open issues | 92 | 0 | | Language | - | TypeScript | | Adopt for | - | Autonomous AI team orchestrator integrating Discord and Linear; vector database for memory enhancement. | | Persona | - | - | | Runtime | - | - | | License | CC0-1.0 | MIT | | Categories | LLM Frameworks | AI Agents, Vector Databases | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [awesome](/tools/sindresorhus-awesome.md) | [OpenSwarm](/tools/unohee-openswarm.md) | | --- | --- | --- | | Maintenance | Active (82%) | Very active (96%) | | Days since push | 11d | 0d | | Open issues (now) | 92 | 0 | | Full report | [trust report](/tools/sindresorhus-awesome/trust.md) | [trust report](/tools/unohee-openswarm/trust.md) | ## Decision facts: OpenSwarm - **Adopt for:** Autonomous AI team orchestrator integrating Discord and Linear; vector database for memory enhancement. ## Choose when ### Choose awesome if… - License: awesome is CC0-1.0, OpenSwarm is MIT. - Tags unique to awesome: resources, awesome-list. - Also covers LLM Frameworks. ### Choose OpenSwarm if… - License: OpenSwarm is MIT, awesome is CC0-1.0. - Tags unique to OpenSwarm: multi-agent, linear, autonomous-agents, discord-bot. - Also covers AI Agents, Vector Databases. - OpenSwarm ships Docker support for self-hosted deployment. - OpenSwarm ships an MCP server manifest. - When you need an autonomous tool that leverages Claude Code CLI to organize your development tasks. ## When NOT to use awesome - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ## When NOT to use OpenSwarm - Avoid if you are not currently utilizing Discord and Linear within your workflow since the integrations might not provide value without these tools. - Do not use if cognitive memory via vector databases is unnecessary or unpreferred for task management in development teams. ## Common questions ### What is the difference between awesome and OpenSwarm? awesome: 😎 Curated list of awesome topics including hardware resources. OpenSwarm: Autonomous AI dev team orchestrator powered by Claude Code CLI.. See the comparison table for live GitHub stats and shared categories. ### When should I choose awesome over OpenSwarm? Choose awesome over OpenSwarm when License: awesome is CC0-1.0, OpenSwarm is MIT; Tags unique to awesome: resources, awesome-list; Also covers LLM Frameworks. ### When should I choose OpenSwarm over awesome? Choose OpenSwarm over awesome when License: OpenSwarm is MIT, awesome is CC0-1.0; Tags unique to OpenSwarm: multi-agent, linear, autonomous-agents, discord-bot; Also covers AI Agents, Vector Databases; OpenSwarm ships Docker support for self-hosted deployment; OpenSwarm ships an MCP server manifest; When you need an autonomous tool that leverages Claude Code CLI to organize your development tasks. ### When should I avoid awesome? LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ### When should I avoid OpenSwarm? Avoid if you are not currently utilizing Discord and Linear within your workflow since the integrations might not provide value without these tools. Do not use if cognitive memory via vector databases is unnecessary or unpreferred for task management in development teams. ### Is awesome or OpenSwarm more popular on GitHub? awesome has more GitHub stars (484,026 vs 817). Stars measure visibility, not whether either tool fits your constraints. ### Are awesome and OpenSwarm open source? Yes - both are open-source projects on GitHub (awesome: CC0-1.0, OpenSwarm: MIT). ### Where can I find alternatives to awesome or OpenSwarm? GraphCanon lists graph-backed alternatives at [awesome alternatives](/tools/sindresorhus-awesome/alternatives) and [OpenSwarm alternatives](/tools/unohee-openswarm/alternatives) ([awesome markdown twin](/tools/sindresorhus-awesome/alternatives.md), [OpenSwarm markdown twin](/tools/unohee-openswarm/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 [this comparison](/compare/sindresorhus-awesome-vs-unohee-openswarm.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, awesome or OpenSwarm? awesome: Active. OpenSwarm: 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 awesome and OpenSwarm? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [awesome trust report](/tools/sindresorhus-awesome/trust); [OpenSwarm trust report](/tools/unohee-openswarm/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=sindresorhus-awesome`](/api/graphcanon/graph?tool=sindresorhus-awesome) - 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/_