--- title: "harbor vs prompts.chat" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/av-harbor-vs-f-prompts-chat" tools: ["av-harbor", "f-prompts-chat"] --- # harbor vs prompts.chat *GraphCanon updated Jul 15, 2026* ## Verdict Pick harbor when harbor is primarily Python; prompts.chat is HTML; pick prompts.chat when prompts.chat is primarily HTML; harbor is Python. [harbor](https://discord.gg/8nDRphrhSF) reports 3.1k GitHub stars, 212 forks, and 56 open issues, last pushed Jun 21, 2026. [prompts.chat](https://prompts.chat) has 165k stars, 21k forks, and 60 open issues, last pushed Jul 11, 2026. Figures are from public GitHub metadata via [harbor's repository](https://github.com/av/harbor) and [prompts.chat's repository](https://github.com/f/prompts.chat). | | [harbor](/tools/av-harbor.md) | [prompts.chat](/tools/f-prompts-chat.md) | | --- | --- | --- | | Tagline | Stop configuring your AI stack. Start using it. One command brings a complete pre-wired LLM stack with hundreds of services to explore. | Share, discover, and collect prompts from the community | | Stars | 3,140 | 165,372 | | Forks | 212 | 21,400 | | Open issues | 56 | 60 | | Language | Python | HTML | | Adopt for | - | Critical decision points for evaluating `prompts.chat` | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | Other | | Categories | Developer Tools, LLM Frameworks | Developer Tools, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [harbor](/tools/av-harbor.md) | [prompts.chat](/tools/f-prompts-chat.md) | | --- | --- | --- | | Maintenance | Active (82%) | Very active (96%) | | Days since push | 24d | 0d | | Open issues (now) | 56 | 60 | | Full report | [trust report](/tools/av-harbor/trust.md) | [trust report](/tools/f-prompts-chat/trust.md) | ## Decision facts: prompts.chat - **Adopt for:** Critical decision points for evaluating `prompts.chat` ## Choose when ### Choose harbor if… - harbor is primarily Python; prompts.chat is HTML. - License: harbor is Apache-2.0, prompts.chat is Other. - Tags unique to harbor: automation, bash, cli, container. ### Choose prompts.chat if… - prompts.chat is primarily HTML; harbor is Python. - License: prompts.chat is Other, harbor is Apache-2.0. - Tags unique to prompts.chat: artificial-intelligence, awesome-list, chatgpt, claude. - Critical decision points for evaluating `prompts.chat` ## When NOT to use harbor - Developer Tools: A gateway is overkill when you're pinned to a single provider and model. - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ## When NOT to use prompts.chat - Developer Tools: A gateway is overkill when you're pinned to a single provider and model. - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ## Common questions ### What is the difference between harbor and prompts.chat? harbor: Stop configuring your AI stack. Start using it. One command brings a complete pre-wired LLM stack with hundreds of services to explore.. prompts.chat: Share, discover, and collect prompts from the community. See the comparison table for live GitHub stats and shared categories. ### When should I choose harbor over prompts.chat? Choose harbor over prompts.chat when harbor is primarily Python; prompts.chat is HTML; License: harbor is Apache-2.0, prompts.chat is Other; Tags unique to harbor: automation, bash, cli, container. ### When should I choose prompts.chat over harbor? Choose prompts.chat over harbor when prompts.chat is primarily HTML; harbor is Python; License: prompts.chat is Other, harbor is Apache-2.0; Tags unique to prompts.chat: artificial-intelligence, awesome-list, chatgpt, claude; Critical decision points for evaluating `prompts.chat`. ### When should I avoid harbor? Developer Tools: A gateway is overkill when you're pinned to a single provider and model. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ### When should I avoid prompts.chat? Developer Tools: A gateway is overkill when you're pinned to a single provider and model. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ### Is harbor or prompts.chat more popular on GitHub? prompts.chat has more GitHub stars (165,372 vs 3,140). Stars measure visibility, not whether either tool fits your constraints. ### Are harbor and prompts.chat open source? Yes - both are open-source projects on GitHub (harbor: Apache-2.0, prompts.chat: Other). ### Where can I find alternatives to harbor or prompts.chat? GraphCanon lists graph-backed alternatives at [harbor alternatives](/tools/av-harbor/alternatives) and [prompts.chat alternatives](/tools/f-prompts-chat/alternatives) ([harbor markdown twin](/tools/av-harbor/alternatives.md), [prompts.chat markdown twin](/tools/f-prompts-chat/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/av-harbor-vs-f-prompts-chat.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, harbor or prompts.chat? harbor: Active. prompts.chat: 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 harbor and prompts.chat? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [harbor trust report](/tools/av-harbor/trust); [prompts.chat trust report](/tools/f-prompts-chat/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=av-harbor`](/api/graphcanon/graph?tool=av-harbor) - 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/_