AgentRun vs Trigger.dev

Side-by-side comparison of two AI agent tools

Short answer

  • AgentRun has had no commit in 23 months; Trigger.dev is actively maintained (711 commits in the last 90 days).
  • Trigger.dev is growing faster: +150 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 Trigger.dev for: trigger.dev – build and deploy durable AI agents and workflows.

From GitHub data refreshed daily.

AgentRunopen-source

The easiest, and fastest way to run AI-generated Python code safely

T
Trigger.devopen-source

Trigger.dev – build and deploy durable AI agents and workflows

Metrics

AgentRunTrigger.dev
Stars38016.5k
Star velocity /mo1.9047619047619049150
Commits (90d)0711
Releases (6m)010
Overall score0.17605315992886910.7556547595846174

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
        View AgentRun DetailsView Trigger.dev Details

        FAQ

        Which is more popular, AgentRun or Trigger.dev?
        Trigger.dev has more GitHub stars (16,455 vs 380).
        Which is more actively developed, AgentRun or Trigger.dev?
        Trigger.dev had more commits in the last 90 days (711 vs 0).
        Should I use AgentRun or Trigger.dev?
        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.