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QwenLM/Qwen-MM-Plugins

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QwenLM/Qwen-MM-Plugins

Description: Make any agent harness multimodal-native.

Language: Python

License: Apache-2.0

Stars: 57

Forks: 1

Open issues: 1

Created: 2026-07-29T09:14:34Z

Pushed: 2026-08-04T23:36:26Z

Default branch: main

Fork: no

Archived: no

README:

Qwen-MM-Plugins

English · [中文](README.zh.md)

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

Contents

  • [🧩 Capabilities](#-capabilities)
  • [🏗 Architecture](#-architecture)
  • [📦 Installation](#-installation)
  • [🔧 Dependencies](#-dependencies)
  • [🔑 Configuration](#-configuration)
  • [🚀 Quick Start](#-quick-start)
  • [🧪 Development](#-development)

🧩 Capabilities

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

| Capability | What it does | Install name | |---|---|---| | core | Foundational vision: dynamic-resolution reading of images / videos / documents / 3D models, plus OCR, grounding, segmentation, ASR, vision chat, and web search | qwen-mm-plugins-core | | video-memory | Long-video memory: a hierarchical graph memory that powers QA over very long videos | qwen-mm-plugins-video-memory | | video-edit | Video editing + generation: editing workflows + image / video / audio generation | qwen-mm-plugins-video-edit | | blender | Blender 3D modeling: drive a running Blender via Python (thin client, 22 tools) — modeling / materials / lighting / rendering | qwen-mm-plugins-blender | | freecad | FreeCAD parametric CAD: drive a running FreeCAD (thin client, 14 tools) — modeling, property edits, STEP/STL import/export, FEM analysis | qwen-mm-plugins-freecad | | edu-agent | Educational tutorial videos: turn a math/science problem or an image into a step-by-step Chinese explainer video / interactive page (skill-only, no MCP server) | qwen-mm-plugins-edu-agent |

👉 Full tool catalog: [docs/en/capabilities.md](docs/en/capabilities.md).

🏗 Architecture

![Qwen-MM-Plugins Architecture](docs/assets/architecture.svg)

📦 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

Or run one action at a time — bash install.sh install / configure / verify / uninstall (what configure and verify do is detailed under [Configuration](#-configuration) and [Dependencies](#-dependencies)).

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) — add the marketplace, then install a capability (replace ` with core / video-memory / video-edit / blender / freecad`):

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

marketplace add also accepts a local repo path; re-running is safe. On codex, marketplace add does not refresh an already-added marketplace, so run codex plugin marketplace upgrade qwen-mm-plugins before plugin add to pick up newly-published capabilities.

Other harnesses (Qwen Code · Gemini CLI · opencode · pi · QwenPaw · …) register the skill + MCP in their own config — exact per-harness blocks are in [docs/en/installation.md](docs/en/installation.md). Easiest of all: just ask the agent — "install qwen-mm-plugins-".

🔧 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 (fetching each capability's env and running --check-system under the hood). Full system-tool table, the edu-agent (skill-only) setup, and the blender/freecad thin-client notes: see [docs/en/installation.md](docs/en/installation.md).

🔑 Configuration

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

  • DASHSCOPE_API_KEYvision_chat / ocr / grounding / transcribe_audio / generation / video-memory build
  • SERPER_API_KEYweb_search / web_extractor / image_search

Export them in your shell, or persist them to ~/.qwen-mm-plugins/config (read whenever a var isn't already in the environment — so GUI-launched harnesses pick them up too). The guided installer's Configure step writes that file for you:

bash install.sh configure

For non-interactive/automation setup and the full environment-variable catalog, see [docs/en/installation.md](docs/en/installation.md).

🚀 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, plus OCR · grounding · segmentation · ASR · web search
@dashboard-4k.png Read every number in this dashboard.
@report.pdf Summarize page...

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