goose vs whip
General-purpose local AI agent in Rust — native desktop app, full CLI and embeddable API — over 15+ providers and 70+ MCP extensions. Block's goose, now an Agentic AI Foundation project. — versus — WhipCode: open-source coding agent in Go built on a recursive language-model loop; agents delegate to sub-agents through short programs, with daemon-owned sessions across desktop, TUI and web.
Both are open-source agents with desktop app, CLI and MCP extensions; goose is the mature general-purpose Rust agent, WhipCode a Go harness specialised in recursive delegation for long tasks.
| goose | whip | |
|---|---|---|
| Stars | 55k | 1.1k |
| Forks | 6.3k | 153 |
| Language | Rust | Go |
| License | Apache-2.0 | Apache-2.0 |
| Last activity | today | today |
| Topics | agents, coding | coding, agents |
| Curated connections | 8 | 3 |
goose — the curator's take
The default answer when someone wants a real agent on their own machine and does not want to assemble one. Rust, three surfaces (desktop app, CLI, API), 15+ providers including Ollama and your existing Claude/ChatGPT/Gemini subscriptions over ACP, 70+ MCP extensions, and custom distributions if you want to ship your own branded build. Now governed under the Linux Foundation's AAIF rather than one vendor, which matters if you are betting a product on it. It is deliberately general — code, research, writing, data — so it has no opinion about your SDLC: no verification gates, no worktree isolation, no PR pipeline. If you want an agent that must prove its work, or a spec-to-PR factory, layer that on or pick a purpose-built harness. Note the repo moved from block/goose; old links and forks still point at the old org.
whip — the curator's take
Interesting when your tasks outgrow one context window: instead of a growing transcript, an RLM loop writes small Starlark or JavaScript programs to slice history, files and large tool outputs, and delegates recursively to its own sub-agents, while a daemon keeps sessions alive after you close the window. Built with open-source models in mind, with provider routing, MCP and skills. Its benchmark (20 of 30 on a mixed Terminal-Bench and repo set) is honestly caveated as not a matched comparison. The churn is real: a v1 alpha CLI track, an Apple-Silicon-only desktop beta, and a clean-project reset that is not an upgrade path. Stay on Claude Code or Codex for a stable daily driver; try this when long-horizon delegation is the actual problem.