agno-agi/agno

Full-stack framework for building Multi-Agent Systems with memory, knowledge and reasoning.

Summary

Agno is a Python framework and runtime for building, serving, and managing AI agent platforms. It combines an SDK for constructing agents, an "AgentOS" runtime that exposes them as a service, and a web UI for management, with built-in storage, observability, and access control.

What it is useful for

Agno is aimed at engineering teams moving from ad-hoc agent scripts to a deployable, multi-tenant platform. Concrete use cases the README calls out:

• Serving agents over a production API (50+ endpoints, with SSE and websockets)
• Storing sessions, memory, knowledge, and traces in your own database
• Connecting to external services through 100+ toolkits, including GitHub, Slack, and Postgres
• Pulling in live context from Slack, Drive, wikis, MCP servers, or custom sources
• Pausing runs for human approval on sensitive tool calls
• Operating multi-tenant setups with JWT-based RBAC, OpenTelemetry tracing, and audit logs
• Exposing agents across channels such as Slack, Telegram, WhatsApp, Discord, AG-UI, and A2A
• Running cron-based jobs and scheduled tasks without standing up extra infrastructure
• Deploying to any container host: Docker, Railway, AWS, GCP, Azure, Fly, Render, Modal, or Helm

The framing is for teams that want to own the full stack, including data, memory, and security posture, rather than depend on a hosted vendor.

How engineers can use it

The README documents two starting points.

Template-driven setup: hand this prompt to a coding agent (Claude Code, Cursor, or Codex):

Help me set up my agent platform.

Clone https://github.com/agno-agi/agentos-railway into a folder called
agent-platform, cd in, read the README, and follow the get started guide.

This boots a local stack via Docker, including a REST API for agents, Postgres for data and traces, an MCP server, and a control plane. To target another environment, swap the repo for agentos-docker, agentos-aws, agentos-gcp, agentos-azure, agentos-fly, agentos-render, agentos-modal, or agentos-helm.

Hand-coding: the README links to a "Build your first agent in 20 lines of code" guide and a platform overview at docs.agno.com, but does not include the code inline, so those docs are the source for the manual path.

You can also feed Agno docs into your own coding agent, either as an MCP server at docs.agno.com/mcp or as an indexed source via docs.agno.com/llms-full.txt (Cursor, VSCode, Windsurf).

Documented limitations:

• Agno sends a telemetry event per agent run. The README states prompts, messages, and outputs are not transmitted, and you can opt out with the environment variable AGNO_TELEMETRY=false.
• The hand-coding setup steps are only linked, not reproduced in this README, so this repository's README does not contain a complete manual installation walkthrough.