StandaloneOpen sourcePrivacy High40k stars
Agno
High-performance multi-agent framework — build, run and manage teams of AI agents at scale
Deployment
Self-hosted / Agno Cloud
Pricing
Free/OSS
Privacy
High
Channels
3 supported
Quick Start
Copy-paste commands to get Agno running on your machine
Prerequisites
- Python 3.10+ (for Python setup)
- Docker Desktop (for Docker setup)
- OpenAI, Anthropic, or Ollama API access
Creates a new agent project with example code. Edit app/main.py to customize behavior.
Environment Variables
OPENAI_API_KEY=your-key-here (or Anthropic/Ollama)
pip install -U agno
agno init my-agent
cd my-agent
agno runCommon Issues
- Import errors: Ensure pip install -U agno completed successfully
- Memory backend: Add --memory=postgres flag for persistent memory
- Multi-agent coordination: Use agno.Team() for agent collaboration
Why teams pick it
- Extremely fast — benchmarks show 3x LangGraph speed.
- Native multi-agent team support built-in.
- Strong memory architecture with multiple storage backends.
Trade-offs to know
- Developer-focused — no visual builder.
- Ecosystem smaller than LangChain/LangGraph.
- Requires Python knowledge.
How it feels in practice
Deployment
Self-hosted / Agno Cloud
Pricing
Open source and free to self-host. Agno Cloud available for managed deployments.
Privacy
Self-hosted deployments keep data on your infrastructure.
Channels supported
WebapiCLI
Gotchas
Before you commit
- Formerly called Phidata — old docs may use old name.
- Start with single agent before multi-agent orchestration.
How does Agno compare?
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