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Up to three tools. The table shows the data as-is, without picking a “best”.
| Field | marimo | goose | uv |
|---|---|---|---|
| Platforms | Universal | Universal, MCP | Universal |
| Local support | Yes | Yes | Yes |
| Paid API | No | No | No |
| License | Apache-2.0 | Apache-2.0 | MIT OR Apache-2.0 |
| Stars | 23382 | 56014 | 91378 |
| Last activity | October 29, 2026 | October 23, 2026 | October 20, 2026 |
| Install complexity | EASY | MEDIUM | Easy on supported systems; Homebrew must already be installed for this command. Windows and standalone installation options are explained in the guide. |
| Category | Workflow, Data | Code Review, Multi-Agent, Workflow | Workflow, 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 an individual developer or small team that wants an AI agent to complete an inspectable task in a working copy: understand files, make a bounded change, and run a test. Start with manual approval and scope the folder and tools. Do not give it broad access to production or sensitive data. | For a Python developer or small team that wants a shared setup rather than relying on manually installed packages. Commit the dependency definition and lockfile, then sync the environment and run commands with uv. It does not isolate the operating system or untrusted code, or replace application compatibility tests. |