agent-run vs Cate
Which AI tool is better in 2026? Let's compare.
Quick Verdict
Cate wins with a rated score of 4.7/5 vs 3.8/5 for agent-run.
| Feature | agent-run | Cate |
|---|---|---|
| Rating | ★★★⯨☆ 3.8 | ★★★★⯨ 4.7 |
| Pricing | Free (Open Source, GPL-3.0) | Free (Open Source) |
| Best For | agent-run is a tiny (under 1 MB) standalone binary that runs coding agents — pi, opencode, codex, or claude — inside a Bubblewrap (bwrap) sandbox. Its purpose is to let an agent operate freely inside your project without being able to touch anything outside it: the host filesystem is mounted read-only by default, and only paths you explicitly allow become read-write. It's built for catching agent mistakes, not malicious code — if an agent tries to delete your home directory or exfiltrate a file, the sandbox contains it. Configuration is a simple TOML file with per-tool sections (tools.claude, tools.codex, …) controlling env inheritance, network access, and mounts. The bwrap binary is compiled for the target platform and embedded directly into agent-run, then exec'd at runtime via a memfd, so there's no separate dependency to install. It currently supports aarch64 and x86_64 Linux and depends on unprivileged user namespaces. | Open-source canvas IDE for agentic coding workflows that provides a visual interface for managing multi-step AI coding tasks. |
Detailed Analysis: agent-run vs Cate
Rating Comparison
agent-run scores 3.8/5 while Cate scores 4.7/5. Cate clearly outperforms agent-run in our testing. The 0.9-point gap reflects meaningful differences in feature quality, reliability, and overall user experience.
Pricing & Value
Both tools offer free tiers, lowering the barrier to entry. However, comparing their paid plans — Free (Open Source, GPL-3.0) vs Free (Open Source) — reveals different value propositions depending on your usage scale.
Feature Comparison
When comparing features, agent-run excels at agent-run is a tiny (under 1 mb) standalone binary that runs coding agents — pi, opencode, codex, or claude — inside a bubblewrap (bwrap) sandbox. its purpose is to let an agent operate freely inside your project without being able to touch anything outside it: the host filesystem is mounted read-only by default, and only paths you explicitly allow become read-write. it's built for catching agent mistakes, not malicious code — if an agent tries to delete your home directory or exfiltrate a file, the sandbox contains it. configuration is a simple toml file with per-tool sections (tools.claude, tools.codex, …) controlling env inheritance, network access, and mounts. the bwrap binary is compiled for the target platform and embedded directly into agent-run, then exec'd at runtime via a memfd, so there's no separate dependency to install. it currently supports aarch64 and x86_64 linux and depends on unprivileged user namespaces., while Cate specializes in open-source canvas ide for agentic coding workflows that provides a visual interface for managing multi-step ai coding tasks.. agent-run stands out with Under 1MB, no runtime dependencies, Read-only host FS by default, explicit mounts only, Catches agent mistakes before they spread, Simple TOML config, per-tool isolation, Self-contained embedded bwrap. Cate differentiates itself with Boosts workflow efficiency, User-friendly interface, Free to use / Open source.
Use Case & Target Audience
Cate is best suited for users who prioritize overall quality and are willing to invest in a proven solution. agent-run appeals to users who may have specific niche requirements or budget constraints that agent-run addresses uniquely. For teams already invested in complementary tools, ecosystem compatibility may be the deciding factor.
Verdict
Based on our comprehensive analysis, Cate is the recommended choice for most users. However, if agent-run's specific strengths match your particular needs, it remains a viable alternative worth considering.
Alternatives Worth Considering
While agent-run and Cate are both strong contenders in the AI tools space, depending on your specific needs, you may also want to explore other tools in this category. Visit our full category listing for a complete overview of available options, or check our expert rankings for curated recommendations.
agent-run Overview
Pros
- • Under 1MB, no runtime dependencies
- • Read-only host FS by default, explicit mounts only
- • Catches agent mistakes before they spread
- • Simple TOML config, per-tool isolation
- • Self-contained embedded bwrap
Cons
- • Linux-only (bwrap + user namespaces)
- • Threat model is mistakes, not hardened malware
- • Env vars do not expand inside mount paths
- • No config merging across files yet
- • Limited arch support (aarch64, x86_64)
Cate Overview
Pros
- • Boosts workflow efficiency
- • User-friendly interface
- • Free to use / Open source
Cons
- • Requires learning curve
- • Self-hosting or setup required
Frequently Asked Questions
Which is better, agent-run or Cate?
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Based on our comprehensive evaluation, Cate scores 4.7/5 compared to agent-run's 3.8/5. Cate is the stronger choice for most users, but agent-run may still be preferable for specific use cases.
Is agent-run free?
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Yes, agent-run offers a free tier. agent-run is priced at Free (Open Source, GPL-3.0). For the most up-to-date pricing information, visit the official agent-run website.
Is Cate free?
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Yes, Cate offers a free tier. Cate is priced at Free (Open Source). Check the official Cate website for the latest pricing details.
What are the main differences between agent-run and Cate?
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agent-run focuses on agent-run is a tiny (under 1 mb) standalone binary that runs coding agents — pi, opencode, codex, or claude — inside a bubblewrap (bwrap) sandbox. its purpose is to let an agent operate freely inside your project without being able to touch anything outside it: the host filesystem is mounted read-only by default, and only paths you explicitly allow become read-write. it's built for catching agent mistakes, not malicious code — if an agent tries to delete your home directory or exfiltrate a file, the sandbox contains it. configuration is a simple toml file with per-tool sections (tools.claude, tools.codex, …) controlling env inheritance, network access, and mounts. the bwrap binary is compiled for the target platform and embedded directly into agent-run, then exec'd at runtime via a memfd, so there's no separate dependency to install. it currently supports aarch64 and x86_64 linux and depends on unprivileged user namespaces., while Cate specializes in open-source canvas ide for agentic coding workflows that provides a visual interface for managing multi-step ai coding tasks.. agent-run costs Free (Open Source, GPL-3.0) versus Cate at Free (Open Source). agent-run stands out with Under 1MB, no runtime dependencies, Read-only host FS by default, explicit mounts only, Catches agent mistakes before they spread, Simple TOML config, per-tool isolation, Self-contained embedded bwrap. Cate stands out with Boosts workflow efficiency, User-friendly interface, Free to use / Open source. Your choice should be guided by which tool's strengths align better with your specific workflow requirements.