Verified project record

agno-agi/agno

agno-agi/agno provides a framework and runtime to build, run, and manage agent platforms while maintaining control over data, memory, and security. It combines an SDK for building agents, a runtime for serving them via REST API, and a web UI for platform management.

Project overview

The project directly addresses the challenge of owning your agent stack end-to-end, offering a runtime, SDK, management UI, and self-hosted storage so that teams can control their data, memory, and security posture.

Project type: AI Agent
Deployment: Refer to project documentation
License: Apache-2.0

Best for

Developers who want to own their agent stack and maintain control of their data, memory, and security posture.
AI engineers and enterprise teams building agent platforms that run as a service and are managed via a web UI.
Teams that need to store sessions, memory, knowledge, and traces in their own database.

Key capabilities

Run your agent platform using the AgentOS runtime, which provides a REST API for serving agents.
Manage everything using the AgentOS UI.
Build your agent platform using the Agno SDK.
Store sessions, memory, knowledge, and traces in your own database.
Pause runs for user confirmation and block tools that require admin approval.

Limitations and risks

Initial setup relies on external coding agents (Claude Code, Cursor, Codex) or manual coding. Factor this into your tooling and workflow decisions.
The runtime sends a telemetry event per agent run. This can be disabled, but teams should review this behavior before adoption.

Getting started

Setup difficulty is rated medium. You can set up the platform by handing a prompt to a coding agent, then cloning the agent-platform repo and running it locally using Docker. Alternatively, it can be built manually via Python code.
Initial setup relies on external coding agents (such as Claude Code, Cursor, or Codex) or manual coding; plan accordingly when choosing your path.

Evidence and sources

Open original GitHub project