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Up to three tools. The table shows the data as-is, without picking a “best”.
| Field | marimo | Dagu | act |
|---|---|---|---|
| Platforms | Universal | Universal, MCP | GitHub |
| Local support | Yes | Yes | Yes |
| Paid API | No | No | No |
| License | Apache-2.0 | GPL-3.0 | MIT |
| Stars | 23382 | 4509 | 72501 |
| Last activity | October 29, 2026 | October 28, 2026 | — |
| Install complexity | EASY | سهل للبداية؛ يحتاج ضبط أمان قبل المشاركة / Easy to start; security configuration required before sharing | — |
| Category | Workflow, Data | Workflow, DevOps, Monitoring | Testing, Git, DevOps |
| Best use | Ideal for a data analyst, Python developer, or small team that wants reproducible experiments, clear Git review, and an interactive report or internal tool from the same source. It is not a replacement for governed BI or a production service requiring enterprise scaling and permissions. | Best for a developer or small team with connected scripts that need schedules, history, and a clear failure point. It adds dependencies, retries, and an operations UI without an external database in single-server mode. A simple independent command may not need it, and some team controls such as additional users, SSO, RBAC, and audit logging currently require a paid license. | Best for a developer or small team that repeatedly edits GitHub Actions workflows and wants to test a job before pushing. It provides a local run log, while a final GitHub check remains necessary. It is not suitable when exact hosted-runner parity is required. |