DeepSeek has released an official desktop app for DeepSeek Harness (dsh), its open-source agent harness. The app ships with the v0.2 preview. Installers cover macOS (Apple silicon) and Windows (64-bit).
Is it deployable? Yes, today, as a preview. Download it from deepseek.com/harness or run npx @deepseek-ai/dsh web. DeepSeek warns that compatibility-breaking changes will follow.
What Shipped in v0.2
A harness is the runtime that turns a model into an agent. It reads files, runs commands and keeps a plan. The v0.2 preview targets everyday work as well as coding.
- Built-in capabilities: commonly used tools for office work and development come preloaded.
- Plugin management: a new page installs, configures, enables and disables plugins.
- File and diff review: a right-hand sidebar previews generated files and code changes.
- Document work: users can send documents, spreadsheets or PDFs and ask for charts or slides.
- Automation Task: a plugin schedules recurring prompts, with run history and editable frequency.
The desktop build also bundles the dsh command. Users no longer need a separate Node.js or pnpm install. Users can sign in with a DeepSeek account or add an API key. Per the rc.1 notes, account models get web search without an extra key.
Architecture: Everything is a Plugin
DeepSeek first open-sourced dsh in August 2026, under MIT. It runs on Cordis as described in the research paper ‘A Programming Paradigm for Spatiotemporal Composability‘. The model adapter, tool registry and agent loop are all plugins. Any layer can be replaced.
The harness is not locked to DeepSeek models. The provider guide covers third-party providers and custom OpenAI-compatible endpoints. The repository has passed 240,000 GitHub stars and 29,000 forks.
dsh also doubles as DeepSeek’s evaluation rig. The API changelog says Code Agent benchmarks ran on ‘DeepSeek Harness minimal mode.’ DeepSeek-V4-Flash-0731 scored 82.7 on Terminal Bench 2.1 in that setup.
4 Session Modes
Sessions run in 1 of 4 modes, per 36Kr’s hands-on and the release notes:
- Standard: general work, and now the built-in default.
- Creator: describe a plugin in chat; the agent builds and installs it.
- PTC: programmatic tool calling, with Node code run in a separate process.
- Minimal: the lean loop DeepSeek uses for benchmark runs.
So, What Changed Now
The v0.2.1-alpha.1 build adds an experimental Claude Code Mods compatibility layer. DeepSeek frames it as a test of whether the Mods API is broadly a subset of dsh plugins. It does not promise full compatibility. The build also adds a ‘Let Agent create a plugin’ entry, an optional Developer Tools bundle and a --public-url flag for reverse proxies. It removes runtime invariant plugins, a breaking change for some extensions.
DeepSeek Harness vs Claude Code vs OpenAI Codex
| Feature | DeepSeek Harness v0.2 | Claude Code | OpenAI Codex |
|---|---|---|---|
| Developer | DeepSeek | Anthropic | OpenAI |
| License | MIT | Proprietary | Apache-2.0 |
| Status | Developer preview | Generally available | Generally available |
| Surfaces | Desktop app (macOS Apple silicon, Windows x64), Web UI, headless CLI | Terminal, IDE, GitHub (@claude) | CLI, IDE extension, desktop app, Codex Web |
| Model access | DeepSeek account or API key, plus custom OpenAI-compatible providers | Anthropic Claude models | ChatGPT plan sign-in or OpenAI API key |
| Extension model | Everything is a plugin, including the agent loop | Plugins with custom commands and agents | MCP servers, plugins, skills |
| Quick start | npx @deepseek-ai/dsh web |
curl -fsSL https://claude.ai/install.sh | bash |
npm install -g @openai/codex |
Key Takeaways
- DeepSeek Harness v0.2 ships official macOS (Apple silicon) and Windows x64 apps.
- The MIT harness treats every layer, including the agent loop, as a plugin.
- Creator mode lets the agent write and install its own plugins.
- It works with non-DeepSeek models through OpenAI-compatible endpoints.
- It is a developer preview; expect breaking changes between builds.
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