Edict vs SuperAGI
Which should you use? A side-by-side look at what each one does, who it suits, what it costs, how hard it is to set up, and where each falls short.
Open source · MIT
Multi-agent AI system modeled on China's Tang-era governance, with a live task dashboard, requires OpenClaw.
Open source · MIT
Open-source Python framework for building and running autonomous AI agents.
The short answer
Choose Edict if you need…
- Developers already running OpenClaw who want a multi-agent workflow with visible task history
- People who want a review step before agent output is executed, as the README describes
- Teams who want to watch and pause agent tasks from a dashboard
- Users who want to switch the LLM model used by each agent from a UI
Choose SuperAGI if you need…
- Python developers experimenting with autonomous AI agents
- Teams exploring agent frameworks built around large language models
- People who want an MIT-licensed codebase they can read and modify
Side-by-side
| Edict | SuperAGI | |
|---|---|---|
| Type | AI model / agent | AI model / agent |
| Price | Free and open source | Free and open source |
| Licence | MIT | MIT |
| GitHub stars | 17k | 17.7k |
| Setup difficulty | Advanced | Advanced |
| How you get it | Clone and build from source | Clone and build from source |
| Main language | Python | Python |
| Last code update | 39 days ago | 22 months ago |
What each one is
Edict
Edict is a set of about 12 AI agents arranged in roles borrowed from an ancient Chinese imperial administration: one sorts incoming requests, others plan, review, and dispatch work, and six execution departments carry it out. A web dashboard shows tasks on a kanban board, agent health, token usage, and an audit trail of each task's path. It is built to run on top of OpenClaw, which the README lists as a requirement.
SuperAGI
SuperAGI is an open-source Python project that describes itself as a framework for building, managing, and running autonomous AI agents. The description says it is aimed at developers who want to create agents that act on their own toward a goal. The README was not provided in usable form, so details beyond the project description and metadata could not be verified here.
Best for
Edict
- Developers already running OpenClaw who want a multi-agent workflow with visible task history
- People who want a review step before agent output is executed, as the README describes
- Teams who want to watch and pause agent tasks from a dashboard
- Users who want to switch the LLM model used by each agent from a UI
SuperAGI
- Python developers experimenting with autonomous AI agents
- Teams exploring agent frameworks built around large language models
- People who want an MIT-licensed codebase they can read and modify
Strengths
Edict
- Dashboard shows task status, heartbeats, and full task history in one place
- README describes a review stage that can send work back for rework before execution
- Configuration is set up by an install script and can run as a systemd service
SuperAGI
- MIT license permits free use and modification
- Large community interest, with about 17.7k GitHub stars
- Written in Python, a widely used language for AI work
Not ideal for
Edict
- People without OpenClaw installed, since the README lists it as required and the dashboard depends on it for live data
- Non-technical users, because setup involves shell scripts, API keys, and an agent configuration
- Anyone needing Windows support, since the README lists macOS and Linux as the prerequisites
SuperAGI
- Non-developers looking for a ready-made app, since the description targets developers
- Production users who need proven reliability, because the README could not confirm reliability claims and the last push date is January 2025
- People who need detailed setup instructions from this entry alone, since no install steps could be verified
Trade-offs
Edict
- Depends on OpenClaw, so it is not useful on its own without that separate system
- README is written mainly in Chinese, and the English README is a separate file the excerpt did not include
- No formal release is listed, and some claims in the README (such as comparisons with other frameworks) are the author's own
SuperAGI
- README content was unavailable, so features and setup cannot be confirmed
- Last push was 2025-01-22 and the latest release is v0.0.14, so maintenance activity is uncertain
- Autonomous agents built on LLMs can behave unpredictably and need careful supervision
Getting started
Edict
Clone the repository
git clone https://github.com/cft0808/edict.gitEnter the project folder
cd edictSuperAGI
Clone the repository
git clone https://github.com/TransformerOptimus/SuperAGIFrequently asked questions
What is the difference between Edict and SuperAGI?
Edict: Multi-agent AI system modeled on China's Tang-era governance, with a live task dashboard, requires OpenClaw. SuperAGI: Open-source Python framework for building and running autonomous AI agents. Edict suits developers already running openclaw who want a multi-agent workflow with visible task history, while SuperAGI suits python developers experimenting with autonomous ai agents.
Are Edict and SuperAGI free?
Edict: Free and open source. SuperAGI: Free and open source.
Is Edict or SuperAGI more popular?
SuperAGI has more GitHub stars (17.7k) than Edict (17k). Popularity isn't the same as fit — check which one matches your use case above.
What are other alternatives to Edict and SuperAGI?
Other options people compare them with include CrewAI, MetaGPT, DeerFlow, Ponytail, Hermes Agent.
Keep comparing
Built from our catalogue entries for both products: open-source details come from each project's README (AI-assisted, refreshed weekly) and GitHub data; AI-tool details are editorial. Spotted something wrong? Let us know from either product's page.