deepseek-harness vs goose
DeepSeek's open agent harness (`dsh`): everything is a plugin, on the Cordis composability runtime, with a local web UI one npx away. Developer preview, MIT, moving fast. — versus — 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.
DeepSeek's plugin-everything agent harness covers the same ground from the model-vendor side. Goose is the packaged, foundation-governed option with a desktop app and a large extension ecosystem; the DeepSeek harness is closer to reference code you extend.
| deepseek-harness | goose | |
|---|---|---|
| Stars | 200k | 54k |
| Forks | 23k | 6.1k |
| Language | TypeScript | Rust |
| License | MIT | Apache-2.0 |
| Last activity | yesterday | today |
| Topics | agents, orchestration | agents, coding |
| Curated connections | 5 | 5 |
deepseek-harness — the curator's take
Worth watching because of who ships it and how it's built: a frontier lab's own harness, structured so that every capability — models, tools, memory, UI — is a Cordis plugin rather than a hardcoded loop, which is why a `dsh-plugin` ecosystem appeared around it almost immediately. `npx @deepseek-ai/dsh web` gets you a working UI on port 3080 with nothing to configure. Do not build on it yet without accepting the terms the README states outright: developer preview, iterating rapidly, compatibility-breaking changes expected. The star count reflects the lab's gravity more than the maturity of the code, and the docs are thin next to harnesses that have been in production a year.
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.