Plugins

A local AI voice studio for DeepSeek Harness with nine local TTS engines for voice design, voice cloning, emotional performance, a reference-audio library and audio export. It only registers /ai-voice/api routes; the UI lives in the companion-memory plugin's integrations page, and every engine needs its own Python virtualenv and downloaded model weights, which are not bundled.

Database workbench inside DSH: import the connections DBeaver already stores (data-sources.json, decrypting saved passwords locally) or register SQLite, PostgreSQL, MySQL and Oracle sources by hand, then hand them to the agent through eight mcp__db__ tools — list_datasources, list_tables, describe_table, sample_rows, execute_sql, explain_query, get_ddl and test_connection. Sources start read-only; one global switch enables INSERT/UPDATE/DDL, every call is row-capped and appended to a JSONL audit log. Also covers groups, bulk actions, a read-only schema browser and a bundled Python MCP server whose dependencies install from the panel. No DSH files to edit.

Local DSH companion plugin with long-term memory, graph-assisted retrieval, emotional state, reflection, group context, and audit views. Targets Windows with Node 24 and Python 3.14 (the basic engine uses the Python standard library, no pip; without Python it falls back to the JS retrieval path).

Per-project long-term memory for DeepSeek Harness: a panel to browse, search and edit what each project knows, and a pointer injected after the first user message telling the agent to read the handoff pack. The memory store itself is a local MCP server (Python + SQLite) in the same repository; install the plugin from npm, then clone the repo, set up the MCP server per the README, and the plugin locates the checkout through DSH_RAG_ROOT or a common install path. Handoff packs are ordered for prompt-cache reuse: stable baseline first, facts appended at the end.

A local small-model habit hint plugin for DeepSeek Harness that reads recent turns, extracts the user habits, key points and hints, and injects them into the conversation system prompt. It needs a Python virtualenv with torch/transformers/peft plus a user-supplied Qwen3-0.6B base model and LoRA adapter, none of which are bundled; its default scope only runs in sessions that companion-memory has enabled, and with the shipped placeholder paths it silently injects nothing.

Scans a repository with its bundled Python 3.12+ tools and scaffolds one Markdown outline per source directory, then publishes the index with a hash manifest that proves the documents match the code; the bundled reader verifies that manifest before serving an overview or one document. The project root needs a project_docs/ directory and a CLAUDE.md entry point.

One-line song cover: fetch a track or take a local file, split stems, derive a key shift, run RVC conversion through Applio, align the vocal, mix three variants and gate the master — nine stages across three tools, zero npm dependencies. Requires a local Applio install (Python, ffmpeg, yt-dlp), a voice model and a CUDA GPU.

Stock research tools for US, China A-share and Hong Kong stocks via the stockproof MCP server (Python 3.10+; install with pip install "stockproof\[mcp,cn]" — A-share/HK data needs Python 3.11+): news, earnings and announcement reads with cited sources, explanations of price moves, a whole-market A-share screen, a quant lab that backtests ideas on point-in-time history with a locked holdout, a portfolio check-up and a local web dashboard; 23 tools.

Control a local Linux desktop from DeepSeek Harness with 19 tools: screenshot, mouse, keyboard, scroll, window, application, display and state-verification control over a native X11 session with XTEST, plus optional AT-SPI accessibility-tree reads and widget value setting. Not for Wayland. Requires xdotool on the host (XTEST input); screenshots and window control also want scrot, ffmpeg, wmctrl, xrandr and xprop, and the AT-SPI tools need python3-gi, at-spi2-core and libatk-adaptor. Missing packages can be installed from the plugin's dependency panel with sudo.

Recap a session from dsh, Claude Code, Codex or OpenCode saved on this machine: the intent, key decisions and why, what changed, open threads and where to resume. Adds the session_recap tool, the /recap command and a right-sidebar panel that lists a project's sessions across agents. Uses the session's own model route, removes keys and tokens from transcripts before sending, and caches recaps locally. Needs python3 and zstd.

DSH design-delivery plugin with 10 tools for UI lint, design tokens, three-candidate shortlists, JND parameter probes, and PPTX deck check/export/render. Deck tools need ppt-master, Python with python-pptx and DSH's LibreOffice Kit; design_capture needs a real browser.

Reader-first long-form fiction pipeline: setting and character cards first, 21 gate scripts, a 1000-trope library and 700 theme seeds, at most two tropes per chapter, a self-test for every script; the scripts run on the host's Python 3.

Reads local AI session history from 16 AI tools plus Windows recent-file activity, and generates daily or weekly work reports on your machine. Currently Windows x64 only: the plugin ships a bundled Windows sidecar (no Python needed); macOS/Linux are not supported yet.

Local LoRA and QLoRA fine-tuning in a panel: import JSONL, see a VRAM estimate before training starts, evaluate, and export an adapter. One-click Python venv setup, but you must supply your own Python 3.10+ and an NVIDIA GPU (6 GB or more). Verified end to end on Windows 11 with an RTX 3060 6 GB; the installer refuses non-Windows hosts, so Linux, macOS and other GPUs are unsupported for now.

DeepSeek Harness (DSH) Instagram FastMCP 核心服務插件：提供 Python FastMCP 子進程管理、Session 會話維持、與 Instagram MCP 工具標準介面

Skill for building a game design brief into a playable, publishable TapTap Maker project: it picks the browser workspace or local MCP route, extracts the five elements of the brief, writes a first-round prompt for a minimal core loop, iterates in the official order, checks preview and release materials, and keeps credit, credential and irreversible-action limits in view. Includes eight reference notes on the product, credits, themes and asset limits, the leaderboard, brief parsing, iteration, publishing and safety, four templates, and three read-only Python checks for brief completeness, project layout and release materials.

Connects DSH to timestamped video reading, shared queues/history and Scroll personal Bilibili workflows through an existing Video Reader installation. Windows x64 only: install the core and set VIDEO_READER_ROOT before starting DSH; the bundle does not install Python, FFmpeg, models or Bilibili credentials.

Right-sidebar file-preview enhancement built on `dsh-better-sidebar` (required — without it the plugin stays inert): a floating find bar for any text file (Ctrl+F, literal or regex, case-sensitive, match counter, next/previous) plus a collapsible Structure panel that lists classes, methods and file-level variables for Java, JavaScript, TypeScript and Python and an element outline for HTML (including .vue/.svelte), with click-to-line jumps. Read-only, no separate tab.

Diagrams a reader understands on first look: nine types from one JSON spec, with a checked title, reading path, legend, contrast and connectors. Requires Python 3.9+ for the render and check scripts.

Whole-PDF paper translation for DSH on top of a BabelDOC installation you provide (Python CLI, with an OpenAI-compatible API key in its config.toml): bilingual dual-page output, a token cost estimate before running, a per-domain glossary reused across papers, and the server-side thinking overhead disabled for translation.

Answers Dark Souls III questions from your own Windows PC save (default `%APPDATA%\DarkSoulsIII\*\DS30000.sl2`): level and stats, current area, bonfires/rings/spells/covenants counted by family, kill state for the 24 bosses, and Steam achievements when Steam is installed - exposed as model tools plus a progress pill beside the composer and a 19-area sidebar page with next-step suggestions. The save stays read-only and is parsed locally by a bundled Python 3 script; Python 3 and the `cryptography` package must be installed, and the game data ships with the plugin.

Drive the NI Multisim 14.3 install on a Windows machine through nine msim_* tools: open and save .ms14 designs, read and edit component values and circuit parameters, run DC operating point, AC sweep, single-frequency AC and transient analyses, export schematics, BOM and netlists. A Win32 channel drives the visible window to run the Analyses dialog and capture Multisim's own schematic view and waveform plot; a SPICE command-file engine handles designs that expose no probes; an offline reader unpacks the .ms14 container without starting Multisim at all. Requires Windows, NI Multisim 14.3, and a 32-bit Python 3.11-3.13 with pywin32.

Wayland desktop control for GNOME/Mutter sessions: screenshot, OCR with screen coordinates, click by text, and batch input actions. Needs a Python 3 backend with python3-gi and GStreamer; OCR needs Tesseract.

Read-only knowledge gateway over a local Markdown vault, in four tools: `wiki_recall` returns the matching section in full with page-level citations plus vault health checks and a page skeleton for writing a good answer back; `wiki_context` returns one evidence pack with per-page excerpts, a support verdict and an explicit list of gaps; `wiki_verify` re-checks a drafted answer against that pack and reports claims the evidence cannot back, including unsupported numbers; `wiki_observe` reports how often answers needed correcting. The settings page and sidebar panel share the same query path as the model, so a search you run by hand cannot disagree with what the model was given. The three knowledge-gateway tools (`wiki_context`, `wiki_verify`, `wiki_observe`) need a local Python 3 bridge — `bridge.python` plus `bridge.toolsRoot` containing `wiki_bridge.py`; without it they return `E_PYTHON_UNAVAILABLE`.