AgentRun vs Cua
Side-by-side comparison of two AI agent tools
Short answer
- AgentRun has had no commit in 23 months; Cua is actively maintained (1,409 commits in the last 90 days).
- Cua is growing faster: +2,970 GitHub stars in the last 30 days vs +2 for AgentRun.
- Pick AgentRun for: the easiest, and fastest way to run AI-generated Python code safely. Pick Cua for: scale computer-use 2.0 with open-source drivers, cross-OS fleets, and benchmarks for training, evaluation.
From GitHub data refreshed daily.
AgentRunopen-source
The easiest, and fastest way to run AI-generated Python code safely
C
Cuaopen-source
Scale computer-use 2.0 with open-source drivers, cross-OS fleets, and benchmarks for training, evaluation, and data generation.
Metrics
| AgentRun | Cua | |
|---|---|---|
| Stars | 380 | 27.7k |
| Star velocity /mo | 1.9047619047619049 | 3.0k |
| Commits (90d) | 0 | 1.4k |
| Releases (6m) | 0 | 10 |
| Overall score | 0.1760531599288691 | 0.9092592394174208 |
Pros
- +多层安全防护：结合 Docker 容器隔离和 RestrictedPython 代码检查，有效防止恶意代码执行和系统破坏
- +零配置易用性：单行代码即可集成，自动处理容器管理、依赖安装和资源限制，大幅降低使用门槛
- +生产就绪：97% 测试覆盖率、完整静态类型支持、仅两个依赖项，确保高稳定性和可维护性
Cons
- -依赖 Docker 运行时：需要系统安装 Docker，在某些受限环境（如无容器权限的云平台）中可能无法使用
- -执行开销：容器启动和依赖安装会增加延迟，可能不适合对响应时间要求极高的实时应用
Use Cases
- •AI 聊天机器人增强：为 ChatGPT、Claude 等模型添加数学计算、数据分析和图表生成能力，安全执行用户请求的复杂运算
- •自动化数据科学：让 AI 助手安全运行 pandas、numpy 代码进行数据处理和可视化，无需担心恶意代码风险
- •教育编程平台：在线编程教学平台中安全执行学生提交的代码，提供实时反馈而不影响系统安全
FAQ
- Which is more popular, AgentRun or Cua?
- Cua has more GitHub stars (27,747 vs 380).
- Which is more actively developed, AgentRun or Cua?
- Cua had more commits in the last 90 days (1,409 vs 0).
- Should I use AgentRun or Cua?
- Compare their capabilities, limitations and "best for" notes above. Both are open source, so trying each on a small task is the fastest way to decide.