--- title: "Aegis vs moby" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/justin0504-aegis-vs-moby-moby" tools: ["justin0504-aegis", "moby-moby"] --- # Aegis vs moby *GraphCanon updated Jul 15, 2026* ## Verdict Pick Aegis when aegis is primarily TypeScript; moby is Go; pick moby when moby is primarily Go; Aegis is TypeScript. [Aegis](https://github.com/Justin0504/Aegis) reports 365 GitHub stars, 37 forks, and 4 open issues, last pushed Jul 15, 2026. [moby](https://mobyproject.org/) has 72k stars, 19k forks, and 3.8k open issues, last pushed Jul 10, 2026. Figures are from public GitHub metadata via [Aegis's repository](https://github.com/Justin0504/Aegis) and [moby's repository](https://github.com/moby/moby). | | [Aegis](/tools/justin0504-aegis.md) | [moby](/tools/moby-moby.md) | | --- | --- | --- | | Tagline | Runtime policy enforcement for AI agents. Cryptographic audit trail, human-in-the-loop approvals, kill switch. Zero code changes. | The Moby Project - a collaborative project for the container ecosystem to assemble container-based systems | | Stars | 365 | 71,899 | | Forks | 37 | 19,126 | | Open issues | 4 | 3,821 | | Language | TypeScript | Go | | Adopt for | - | - | | Persona | - | - | | Runtime | - | - | | License | MIT | Apache-2.0 | | Categories | AI Agents, Inference & Serving, LLM Frameworks | Developer Tools, Inference & Serving, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [Aegis](/tools/justin0504-aegis.md) | [moby](/tools/moby-moby.md) | | --- | --- | --- | | Days since push | 0d | 1d | | Open issues (now) | 4 | 3.8k | | Owner type | User | Organization | | Full report | [trust report](/tools/justin0504-aegis/trust.md) | [trust report](/tools/moby-moby/trust.md) | ## Choose when ### Choose Aegis if… - Aegis is primarily TypeScript; moby is Go. - License: Aegis is MIT, moby is Apache-2.0. - Tags unique to Aegis: ai-agents, ai-safety, anthropic, audit-trail. - Also covers AI Agents. ### Choose moby if… - moby is primarily Go; Aegis is TypeScript. - License: moby is Apache-2.0, Aegis is MIT. - Tags unique to moby: containers, docker, go, golang. - Also covers Developer Tools. ## When NOT to use Aegis - AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. - Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ## When NOT to use moby - Developer Tools: A gateway is overkill when you're pinned to a single provider and model. - Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. - 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 Aegis and moby? Aegis: Runtime policy enforcement for AI agents. Cryptographic audit trail, human-in-the-loop approvals, kill switch. Zero code changes.. moby: The Moby Project - a collaborative project for the container ecosystem to assemble container-based systems. See the comparison table for live GitHub stats and shared categories. ### When should I choose Aegis over moby? Choose Aegis over moby when Aegis is primarily TypeScript; moby is Go; License: Aegis is MIT, moby is Apache-2.0; Tags unique to Aegis: ai-agents, ai-safety, anthropic, audit-trail; Also covers AI Agents. ### When should I choose moby over Aegis? Choose moby over Aegis when moby is primarily Go; Aegis is TypeScript; License: moby is Apache-2.0, Aegis is MIT; Tags unique to moby: containers, docker, go, golang; Also covers Developer Tools. ### When should I avoid Aegis? AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ### When should I avoid moby? Developer Tools: A gateway is overkill when you're pinned to a single provider and model. Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ### Is Aegis or moby more popular on GitHub? moby has more GitHub stars (71,899 vs 365). Stars measure visibility, not whether either tool fits your constraints. ### Are Aegis and moby open source? Yes - both are open-source projects on GitHub (Aegis: MIT, moby: Apache-2.0). ### Where can I find alternatives to Aegis or moby? GraphCanon lists graph-backed alternatives at [Aegis alternatives](/tools/justin0504-aegis/alternatives) and [moby alternatives](/tools/moby-moby/alternatives) ([Aegis markdown twin](/tools/justin0504-aegis/alternatives.md), [moby markdown twin](/tools/moby-moby/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/justin0504-aegis-vs-moby-moby.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, Aegis or moby? Aegis: Very active. moby: 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 Aegis and moby? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [Aegis trust report](/tools/justin0504-aegis/trust); [moby trust report](/tools/moby-moby/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=justin0504-aegis`](/api/graphcanon/graph?tool=justin0504-aegis) - 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/_