SuperAGI
Open-source Python framework for building and running autonomous AI agents.
- Stars
- 17.7k
- Forks
- 2.2k
- Licence
- MIT
- Language
- Python
- Last update
- 1.8 years ago
- Type
- AI model / agent
No commits in over a year — check for forks or alternatives before adopting.
What it is
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.
- Study how an autonomous agent framework is structured
- Prototype an agent that uses an LLM to work through a multi-step task
- Adapt the MIT-licensed code for internal experiments
Great for
- 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
Not ideal for
- 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
How to get it
- 1
Clone and build from source
Clone the repository
git clone https://github.com/TransformerOptimus/SuperAGI - 2
Run it
- Read the README in the cloned repository for setup instructions
- Install the listed dependencies described there
- Follow the project's documented steps to start the framework
- 3
Get the most out of it
- Check the project homepage at superagi.com for documentation
- Review the repository's issues and releases for current status
- Start with the smallest example the README provides before building larger agents
Downloads
Strengths
- 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
Trade-offs
- 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
How it compares
| Project | Stars | Type | Level | Updated | Best for |
|---|---|---|---|---|---|
| SuperAGI (this) | 17.7k | AI model / agent | advanced | 1.8 years ago | Python developers experimenting with autonomous AI agents |
| composio | 30.9k | Dev tool | intermediate | 4 days ago | Developers building AI agents that need to read or act in third-party apps |
| edict | 17k | AI model / agent | advanced | 1 months ago | Developers already running OpenClaw who want a multi-agent workflow with visible task history |
| open-swe | 11.2k | AI model / agent | advanced | 4 days ago | Engineering teams that want a self-hosted coding agent they can inspect and adapt |
| langchain | 149k | Framework | intermediate | 4 days ago | Python developers building LLM-powered applications |
| OpenHands | 92.5k | App | intermediate | 4 days ago | Developers who want coding agents running on a server while their laptop is off |
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.