Always-on-top macOS desk pet for the DeepSeek Harness, with a native menu and DIY skins. Shows what your agent is doing: working, waiting, finished, failed. Seven skins, or make your own from one image. No dependencies.
DeepSeek Harness plugin: dockable Markdown preview panel that opens side-by-side with the conversation, tracks recently accessed .md files per session, and intercepts in-chat .md references so they preview instead of launching the system editor. Built on top of dsh-vision-opencode for a visual-verification + source-preview workflow.
Workspace document vault for the dsh web GUI: a conversation '文档' tab with an all-type file tree (Markdown/PDF/HTML/code/Excel·CSV/images), full GFM rendering via the platform MarkdownText (tables, task lists, footnotes, KaTeX math, highlighted code fences), Mermaid diagrams, Obsidian-style [[wikilinks]], PDF blob preview, image zoom/pan, native SheetJS spreadsheets, and in-page editing with find/replace. Optional dsh-better-sidebar viewer integration.
DeepSeek Harness host plugin: serves a configured workspace/media folder over the web server under /media, so any conversation can display local images by referencing http://<host>:<port>/media/<relative-path>.
Vision tools · Productivity
$ npx -p @deepseek-ai/dsh dsh plugin --profile web add github:qfwycn/dsh-media-serve
MiniMax multimodal bridge for DeepSeek Harness (DSH). One mmx_bridge tool covers describe/image/video/speech/music/cover/search/quota; optional web_search/read_image takeover; built-in client enhancement renders inline players/previews plus a settings-page management card in the Web GUI.
Agent collaboration · Vision tools · Integrations
$ npx -p @deepseek-ai/dsh dsh plugin --profile web add github:welsione/dsh-mmx-bridge
Global model command palette and provider/model configuration panel for DeepSeek Harness, with a visual provider catalog, startup OpenRouter free-model sync, selective request retries, loopback relays, online capacity presets, and optional media tools.
Vision tools
$ npx -p @deepseek-ai/dsh dsh plugin --profile web add github:Jensen-Yao/dsh-model-palette
Model pricing and capability board for DeepSeek Harness: compare per-1M-token prices, find the cheapest route, and see coding/agentic/vision tags for every LLM you can connect — in the DSH settings UI.
Plug-in vision for text-only LLMs — a DeepSeek Harness (dsh) fork of ModLens adding multi-engine support (Gemini, Volcengine Ark/Doubao, Claude) and per-call engine selection
DSH multimodal input plugin: route file attachments (images, video, audio, text) through per-preset model chains and feed the results to the session model as prompt tokens. Adds a Multimodal settings page.
Agent collaboration · Vision tools · Productivity
$ npx -p @deepseek-ai/dsh dsh plugin --profile web add github:yauntyour/DSH-Multimodal
DeepSeek Harness (dsh) web plugin: paste images into the composer with thumbnail previews, route them as file attachments for text-only models, and show zoomable thumbnails in sent messages
Vision tools
$ npx -p @deepseek-ai/dsh dsh plugin --profile web add github:wertyq111/dsh-paste-preview
Background image plugin for the DeepSeek Harness web UI (dsh web): pick a local image as the whole-UI background, adjust a theme-aware matte, or clear it anytime.
Vision tools · Interface extensions
$ npx -p @deepseek-ai/dsh dsh plugin --profile web add github:haozhu11/dsh-plugin-background
$ npx -p @deepseek-ai/dsh dsh plugin --profile web add github:jayantTang/DSH_Mobile#1033529aa03afe8a57f298ed00d748d184405917&path:plugins/doubao-image
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Questions about DSH Hub
What is DSH Hub?
DSH Hub is a community plugin directory for DeepSeek Harness, bringing together descriptions, source links and installation instructions to help you discover and compare extensions.
Does inclusion mean a plugin is tested and compatible?
No. Detail pages show recorded compatibility and dependency ranges. Unknown does not mean compatible; check the project documentation before installing.
How do I install a plugin?
Open its detail page and check the installation section. Copy the command into your Harness environment when available, or follow the project README.