Qwen-MM-Plugins

Native multimodal plugins for Qwen models. Make any agent harness multimodal-native.

Contents

• 🧩 Capabilities
• 🏗 Architecture
• 📦 Installation
• 🔧 Dependencies
• 🔑 Configuration
• 🚀 Quick Start
• 🧪 Development

🧩 Capabilities

Each capability is installed separately — a skill (so the model knows the toolset exists) plus an optional MCP server (the tools themselves).

We ship cookbooks of Qwen3.8-Max + these plugins in action — each capability's cookbook has its full tool listing, setup, and worked cases.

🏗 Architecture

📦 Installation

A capability = a skill (so the model knows the tools exist) + an optional MCP server (the tools themselves, launched on demand by uvx — needs uv, no manual pip).

Recommended: the guided installer

One script handles install · configure · verify · uninstall across every harness it supports (Claude Code · Codex · Qoder · OpenClaw · Qwen Code · Gemini CLI). It drives each harness's own native install under the hood — nothing reinvented — and writes a single shared config file (~/.qwen-mm-plugins/config) that GUI and terminal harnesses both read, so you set things up once:

curl -fsSL https://raw.githubusercontent.com/QwenLM/Qwen-MM-Plugins/main/install.sh | bash

Windows x64: use WSL2 (Ubuntu recommended) and clone the repository inside your WSL home directory (for example ~/code), rather than under a mounted Windows drive such as /mnt/c. Then run the same commands there. WSL2 is currently the only supported Windows environment; native Windows has not yet been validated.

By hand (per-harness)

Prefer your harness's own commands — or you're on opencode / pi / QwenPaw, which the installer doesn't cover? Register the skill + MCP yourself.

Plugin-marketplace harnesses (Claude Code · Qoder · Codex · OpenClaw · Qwen Code) — add the marketplace, then install a capability (replace <cap> with core / api / search / video-memory / video-edit / blender / freecad). Install core by default — it's the local-I/O base every other capability builds on — plus whichever others you need:

# Claude Code
claude   plugin  marketplace add https://github.com/QwenLM/Qwen-MM-Plugins.git
claude   plugin  install       qwen-mm-plugins-<cap>@qwen-mm-plugins
# Qoder
qodercli plugins marketplace add https://github.com/QwenLM/Qwen-MM-Plugins.git
qodercli plugins install       qwen-mm-plugins-<cap>@qwen-mm-plugins
# Codex
codex    plugin  marketplace add https://github.com/QwenLM/Qwen-MM-Plugins.git
codex    plugin  add           qwen-mm-plugins-<cap>@qwen-mm-plugins
# OpenClaw
openclaw plugins install       qwen-mm-plugins-<cap> --marketplace https://github.com/QwenLM/Qwen-MM-Plugins.git
# Qwen Code
qwen extensions install https://github.com/QwenLM/Qwen-MM-Plugins.git:qwen-mm-plugins-<cap> --consent

🔧 Dependencies

uvx installs the Python dependencies for the chosen profile on first launch — no manual pip. The only things you install yourself are system tools: ffmpeg (video / audio), plus optional libreoffice / blender / texlive / chromium for visualize. Run bash install.sh verify to self-test what's installed — it confirms your API key and reports any missing system tools.

🔑 Configuration

The API-based tools need a key — native image / video / document reading doesn't:

• DASHSCOPE_API_KEY — vision_chat / ocr / grounding / transcribe_audio / Omni audio-video understanding / generation / video-memory build
• SERPER_API_KEY — web_search / web_extractor / image_search

Export them in your shell, or persist them to ~/.qwen-mm-plugins/config. The guided installer's Configure step writes that file for you:

bash install.sh configure

🚀 Quick Start

Once a capability is installed, reference a file in your harness and just ask — the model picks the right tool automatically. Reading is dynamic-resolution: every image, video frame, and document page is auto-scaled to the VL model's patch grid, so a 4K screenshot's fine print and a tiny thumbnail both come in at the detail they need — no manual resizing.

# core — read images / video / docs / 3D models (local, dynamic-resolution)
@dashboard-4k.png      Read every number in this dashboard.
@report.pdf            Summarize page 3.

# api — cloud VL + Omni APIs: caption / OCR / grounding / segmentation / ASR, plus Omni audio-video understanding
@receipt.jpg           OCR this and total the line items.
@street.jpg            Draw a box around every car in the scene.
@meeting.mp4           Transcribe this with speaker labels and timestamps.
@sports-clip.mp4       Count every completed pass and list when each one occurs.
@song.mp3              Tag the genre, mood, instruments, key, and vocal profile.

# search — web + reverse-image search to confirm what's on screen
@place.jpg             Where was this photo taken?

# video-memory — QA over long videos; the first query auto-builds memory
@lecture-2h.mp4        What are the main points, with timestamps?

# video-edit — image / video / audio generation + editing workflows
                       Generate a 1024×1024 image of a red panda coding at night.
@/path/to/media        Help me edit this video down to about 3 minutes.

# blender — drive a running Blender to model / texture / light / render (thin client, 22 tools)
                       Model a low-poly wooden stool, add a warm key light, and render it.

# freecad — parametric CAD in a running FreeCAD (thin client, 14 tools; STEP/STL, FEM)
                       Model an M6 hex bolt 30 mm long and export it as STEP.

# edu-agent — turn a math/science problem into a step-by-step Chinese explainer video (skill-only)
@geometry-problem.png  Explain how to solve this as a narrated video.

🧪 Development

Development setup, contribution guidelines, and verification commands are in CONTRIBUTING.md.

📄 License

Apache-2.0. The Blender and FreeCAD capabilities vendor third-party MIT-licensed code.