dsh-mcp-xcodeDSH plugin bridging agents to the Xcode headless MCP service (xcrun mcpbridge) over stdio JSON-RPC, exposing Xcode build/test/preview/simulator tools as agent tools. Zero runtime dependencies.
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dsh-mcp-xcodeDSH plugin bridging agents to the Xcode headless MCP service (xcrun mcpbridge) over stdio JSON-RPC, exposing Xcode build/test/preview/simulator tools as agent tools. Zero runtime dependencies.
dsh-mcpmanagerDSH MCP manager — inspect, add, edit and remove MCP server configs in the profile patch; restarts are delegated to the host agent. · DSH MCP 管理器:查看/新增/编辑/删除 profile 中的 MCP server 配置,重启生效交由 agent 处理。
$ npx -p @deepseek-ai/dsh dsh plugin --profile web add github:EricXu20266/dsh-mcpmanagerdsh-md-convertConvert Office documents (.doc/.docx/.xls/.xlsx/.ppt/.pptx) and PDFs (incl. scanned, via local OCR) to structurally-formatted Markdown, powered by MarkItDown. CLI + dsh agent tool.
$ npx -p @deepseek-ai/dsh dsh plugin --profile web add github:yakoylp/dsh-md-convertdsh-media-forgeMedia Forge: agent + skills workflow for media-generation APIs, with a sidebar panel for loading saved generation skills into a conversation
$ npx -p @deepseek-ai/dsh dsh plugin --profile web add github:Bigesila-B/dsh-media-forgedsh-media-genPlan and execute Atlas Cloud image, video, audio, and 3D workflows in DeepSeek Harness.
$ npx -p @deepseek-ai/dsh dsh plugin --profile web add github:AtlasCloudAI/dsh-media-gendsh-meeting-coordinatorDSH 多 Agent「会议室」插件:会籍(会议室)+ fork 上下文入场 + 主持人控场多轮讨论 + 会后各自压缩并回到工作区继续工作。基于 dsh-std 元协议。
$ npx -p @deepseek-ai/dsh dsh plugin --profile web add github:liaowenqi123/dsh-meeting-coordinatordsh-memesDSH plugin: meme/reaction picker for DeepSeek Harness agents. No memes, no soul. Picks the right reaction image from the kagura-agent/memes library at runtime — semantic tag matching over 26 categories.
$ npx -p @deepseek-ai/dsh dsh plugin --profile web add github:kagura-agent/dsh-memesdsh-memflowMEMFLOW memory framework for DeepSeek Harness — distributed memory architecture: every project carries its own memory/, one plugin for Hermes-like memory across all your workflows
$ npx -p @deepseek-ai/dsh dsh plugin --profile web add github:crwsr124/dsh-memflowdsh-memoMemo — session memory search for DeepSeek Harness agents: cross-session full-text recall (memo_search), distilled notes (memo_remember), and corpus stats (memo_stats) over the official sessionQuery service. Zero infrastructure, local-first.
dsh-memoriesDeepSeek Harness dual-ledger cross-session memory: auto-extracted long-term facts (MEMORY.md) plus a living project progress ledger (PROGRESS.md), recalled into every new session.
$ npx -p @deepseek-ai/dsh dsh plugin --profile web add github:jisi71/dsh-memoriesdsh-memoryLayered file memory for DeepSeek Harness: global snapshot injection, workspace notes, session recall, post-compaction flush, and a bundled usage skill
$ npx -p @deepseek-ai/dsh dsh plugin --profile web add github:aqsk-BLG/dsh-memorydsh-memoryDSH memory plugin: RRF multi-lane recall / confirm-based writes / Fernet vault / session harvest(DSH 记忆插件:五路 RRF 召回 / 确认制写入 / Fernet 加密库 / 会话转录)
$ npx -p @deepseek-ai/dsh dsh plugin --profile web add github:boomzikazita/dsh-memorydsh-memoryCross-session long-term memory for DeepSeek Harness: a schema-validated memory domain over ctx.storage plus model-facing remember/recall/index/forget tools and a memory protocol prompt section.
dsh-memorySession-end memory for DeepSeek Harness: distils each turn's new dialogue into durable notes, then recalls the global set plus the current workspace's in a per-agent prompt section.
$ npx -p @deepseek-ai/dsh dsh plugin --profile web add github:HaydenSmith1121/dsh-memorydsh-memoryDSH 长期记忆增强插件:文档索引 + 语义检索 + 跨会话 KV 记忆(agent 工具)
dsh-memoryPersistent long-term memory plugin for DeepSeek Harness (dsh): single memory tool, markdown storage, auto session summary, curator governance, user-profile injection.
dsh-memoryLong-term memory for DeepSeek Harness agents: user preferences, project facts, session summaries, and knowledge entries, with auto-injection at session start.
$ npx -p @deepseek-ai/dsh dsh plugin --profile web add github:yangyongzhen/dsh-memorydsh-memory-dashboardDeepSeek Harness 内嵌的本地四层记忆浏览器
$ npx -p @deepseek-ai/dsh dsh plugin --profile web add github:perinchiang/dsh-memory-dashboarddsh-memory-deltaLayered, auto-injected cross-session memory for AI coding agents: a DSH plugin plus a standalone zero-dependency CLI. Borrows the spec/change/archive discipline from OpenSpec (MIT), but pushes instead of pulls.
$ npx -p @deepseek-ai/dsh dsh plugin --profile web add github:lpf20200901/dsh-memory-deltadsh-memory-evolve为 DeepSeek Harness 带来分层记忆(全局 / 用户 / 项目 / GIT 分支 / 每日)与自我进化(经验沉淀 + 技能自动创建)和技能管理、待办管理、CLI 调度(kimi/codex/grok/hermes 等外部 AI 统一调度)、临时信息便签,带 WebUI 管理界面。Hermes-style long-term memory, self-evolution, skills, todos and external CLI agent dispatch for DeepSeek Harness.
dsh-memory-evolve-suite为 DeepSeek Harness 带来分层记忆(全局 / 用户 / 项目 / GIT 分支 / 每日)与自我进化(经验沉淀 + 技能自动创建)和技能管理、待办管理、CLI 调度(kimi/codex/grok/hermes 等外部 AI 统一调度)、临时信息便签,带 WebUI 管理界面。Hermes-style long-term memory, self-evolution, skills, todos and external CLI agent dispatch for DeepSeek Harness. 本构建另内置三份记忆运维技能(压缩 / 整理 / 注入轨毒源取证)。
$ npx -p @deepseek-ai/dsh dsh plugin --profile web add github:Archer76/dsh-memory-evolve-suitedsh-memory-gaGated GA-style layered memory for DeepSeek Harness: hard-injected L1, working checkpoint, settlement to Skills/L1/L2 — no silent auto-retain.
$ npx -p @deepseek-ai/dsh dsh plugin --profile web add github:DiligenceLai/dsh-memory-gadsh-memory-graphNon-invasive SQLite hybrid memory and knowledge-graph plugin for DeepSeek Harness
$ npx -p @deepseek-ai/dsh dsh plugin --profile web add github:zmh2000829/dsh-memory-graphdsh-memory-hermesHermes-style bounded curated memory for DeepSeek Harness (out-of-tree plugin)
$ npx -p @deepseek-ai/dsh dsh plugin --profile web add github:SipengXie2024/dsh-memory-hermesUse a feature keyword or category, then sort by recent updates or GitHub stars.
Read the description, AI analysis and original README to understand what a plugin does.
Review compatibility, dependency ranges and instructions, then copy the available install command.
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No. Detail pages show recorded compatibility and dependency ranges. Unknown does not mean compatible; check the project documentation before installing.
Open its detail page and check the installation section. Copy the command into your Harness environment when available, or follow the project README.