head to head · open source

shannon vs code-on-incus

shannon has 50,964 GitHub stars, 5,926 forks, 18 open issues and last shipped 7 days ago. code-on-incus has 771 stars, 67 forks, 24 open issues and last shipped yesterday. shannon leads on adoption by 6,510% (50,964 vs 771 stars). shannon is written in TypeScript under AGPL-3.0; code-on-incus is written in Go under MIT. shannon has attracted 12% as many forks as stars, code-on-incus 9%. code-on-incus was the more recently maintained of the two, and both are self-hostable with no licence fee.

Two open source projects, one decision. Both are free and self-hostable — the differences are community size, license terms, language stack and release pace.

shannon ★ 51K code-on-incus ★ 771 category AI & Machine Learning

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Side by side

shannon code-on-incus
GitHub stars ★ 51K ★ 771
License AGPL-3.0 MIT
Written in TypeScript Go
Last push 2026-10-27 2026-11-02
Forks ⑂ 5.9K ⑂ 67
Self-hosting Yes Yes
Data ownership Your server Your server

pick shannon if

  • You weight community size — 51K stars and counting
  • You want the AGPL-3.0 license terms
  • Your stack matches TypeScript
  • You value the larger contributor base for long-term maintenance

full shannon profile →

pick code-on-incus if

  • You want the code-on-incus feature set and don't need the biggest community
  • You prefer the MIT license terms
  • Your stack matches Go
  • You evaluated both and code-on-incus fits your workflow better

full code-on-incus profile →

About shannon

[!NOTE] Shannon 3.0 is live: deeper security code analysis, more thoroughly vetted findings, a rebuilt CLI, native CI/CD, professional PDF reports, and SARIF. Shannon is an autonomous, AI pentester for web applications and APIs. It analyzes your source code, identifies attack paths, and executes real exploits to prove vulnerabilities before they reach production. No exploit, no report. This repository is Shannon Open Source: the full agent, run locally from your command line. Launch Shannon The interactive launcher will guide you through setup and your first pentest. [!TIP] AI agents and LLMs: start with…

read the full shannon overview →

About code-on-incus

code on incus ( coi ) Give every AI coding agent its own machine with active defense. coi runs your AI coding tool (Claude Code, Codex, opencode, pi, omp) inside its own isolated Linux system a full OS container with root access, systemd, Docker, and the freedom to install anything. The agent works like it would on a real server but it can't touch your host, can't see your credentials, and if it does something dangerous, coi pauses or kills the container on its own. One command drops you into a coding session. Your project is mounted, file permissions just work, and your SSH keys, tokens, and environment…

read the full code-on-incus overview →

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Frequently asked questions

Is shannon or code-on-incus more popular?

shannon has 50,964 GitHub stars and code-on-incus has 771. shannon has the larger community by that measure.

Are shannon and code-on-incus free?

Both are open source. shannon is licensed under AGPL-3.0 and code-on-incus under MIT. Neither carries a licence fee.

What is the difference between shannon and code-on-incus?

shannon is written in TypeScript and code-on-incus in Go. The practical differences are community size, licence terms, language stack and release cadence — all compared in the table above.

Which should I choose, shannon or code-on-incus?

Choose shannon if you want the larger community (50,964 stars) or its AGPL-3.0 licence terms. Choose code-on-incus if its feature set, stack or MIT licence fits better. Both are self-hostable.