Toonflow
Open-source AI tool for making short dramas and motion comics, with a canvas, agents, and image/video generatiHBAI-Ltd/Toonflow-app
- Stars
- 20.2k
- Forks
- 3.6k
- Licence
- MIT
- Language
- Vue
- Last update
- 6 days ago
- Type
- App
What it is
Toonflow is an open-source tool for creating short dramas, motion comics, and short videos. It combines script writing, storyboarding, management of character and scene assets, and image and video generation on an infinite canvas. The README says it can be self-hosted, lets you connect your own models, and can be extended with AI agents, MCP, and plugins.
- Write a script and break it into storyboard shots on the infinite canvas
- Organize character and scene assets for reuse across episodes
- Generate images and then videos from storyboard prompts
- Build a repeatable creation flow with AI agents and visual workflows
Great for
- Independent creators making short dramas or motion comics who want a self-hosted workflow
- Creators who want to choose their own image or video generation models
- Developers who want to extend a canvas-based creation pipeline with plugins or MCP
- Teams that need to keep creative assets on their own infrastructure
Not ideal for
- People who want a fully managed cloud service with no setup, since the README centers on local deployment and client downloads
- Users who need guaranteed output quality from specific models, because the README does not specify which models are supported or how well they perform
- Anyone expecting a simple one-click video maker; the feature set described is broad and the README gives limited onboarding detail in the excerpt provided
How to get it
- 1
Download the app
Clone the repository
git clone https://github.com/HBAI-Ltd/Toonflow-app.git - 2
Run it
- Download the client for your platform from the GitHub releases page (the latest release is v2.0.8)
- Install and launch the app
- Open the tutorial linked in the README for setup and model configuration
- Create a project and start with a script or storyboard on the canvas
- 3
Get the most out of it
- Connect the image and video models you prefer, since the README highlights free model choice
- Use the asset management features to reuse characters and scenes across shots
- Explore the plugin market linked in the README to extend functionality
- Try MCP integration if you want external tools to drive the workflow
Downloads
Strengths
- Open source under the MIT license, so the code can be inspected and modified
- Self-hosted with support for choosing your own models, per the README
- Covers the full chain from script and storyboard to image and video generation in one canvas
Trade-offs
- The README excerpt provided is truncated and does not include full setup steps, so exact requirements are unclear
- Output depends on the external models you connect; the README does not benchmark them
- Documentation shown is largely in Chinese, with the English README linked separately
How it compares
| Project | Stars | Type | Level | Updated | Best for |
|---|---|---|---|---|---|
| Toonflow-app (this) | 20.2k | App | intermediate | 6 days ago | Independent creators making short dramas or motion comics who want a self-hosted workflow |
| Open-Generative-AI | 32k | App | beginner | 5 days ago | People who want to try many AI image and video models in one place |
| Prompt-Engineering-Guide | 79.8k | Learning resource | beginner | 8 months ago | People who are new to prompting and want structured lessons with examples |
| ai-agents-for-beginners | 78.7k | Learning resource | beginner | 4 days ago | Developers new to AI agents who want guided lessons with code |
| ai-engineering-from-scratch | 76.3k | Learning resource | intermediate | 4 days ago | Students who want to understand how LLMs, retrieval, and agents work internally |
| langgraph | 44.3k | Library | intermediate | 4 days ago | Python developers building multi-step AI agents that must survive failures or long waits |
Stats synced from GitHub. The assessment above was drafted with AI from the project's README on 2026-10-29 and may miss recent changes — check the README before relying on a command. MIT licence: free to use, modify and distribute, including commercially, as long as you keep the copyright notice.