Agno: Open Source AI Development Platforms

What is Agno?

What it is

Agno is a model-agnostic platform for building, running, and managing AI agent platforms. It provides both a Python SDK for agent development and a runtime environment (AgentOS) for serving agents as services, backed by a web-based control plane. Agno lives in the Python-based AI development ecosystem and targets teams seeking full ownership of their agent infrastructure without vendor lock-in.

It solves the problem of fragmented agent tooling by unifying agent orchestration, storage, security, and deployment into a single stack. Developers can define agents once and deploy them across environments—local, cloud, or hybrid—while retaining control over data, memory, and access policies.

Key capabilities

Serve agents via a production REST API with 50+ endpoints, including Server-Sent Events and WebSockets
Store sessions, memory, knowledge, and traces in a user-provided Postgres database
Integrate with 100+ external systems (e.g., GitHub, Slack, Postgres) using pre-built toolkits
Access live context from Slack, Google Drive, wikis, MCP servers, and custom sources
Enforce JWT-based role-based access control (RBAC) for multi-user, multi-tenant isolation
Trigger human approval workflows to pause runs or block sensitive tool execution
Schedule background jobs and cron-based agent runs without external infrastructure

Who uses it and how

Teams building internal agent platforms deploy using Docker or cloud templates (Railway, AWS, GCP, Azure, Fly, Render, Modal, Helm)
Product engineers integrate agents into existing apps via the REST API and webhooks
Developers use the SDK to prototype agents in 20 lines of code, then productionize them with observability and security features

Getting started

Clone a starter template like agentos-railway, agentos-docker, or another platform-specific repo, then run docker compose up. The runtime auto-provisions a Postgres DB, MCP server, and control plane. Documentation and MCP indexing (docs.agno.com/mcp) support IDE integration.

When to use it — and when not to

Use Agno when you need full control over your agent stack, multi-tenancy, and observability out of the box, and are comfortable managing Postgres and container deployments. Avoid it if you require a fully managed SaaS with no infrastructure overhead, or if you lack resources to operate your own database and authentication layer. Agno replaces self-built stacks but not hosted agent platforms—it trades convenience for portability and compliance.

project readme (upstream, from github) — read inline

Build, run, and manage agent platforms.

Introduction

Agno is a framework and runtime for agent platforms. Build agents, run them as a service, manage your platform using a web UI.

Build your agent platform using the Agno SDK.
Run your agent platform using the AgentOS runtime.
Manage everything using the AgentOS UI.

Agno allows you to own your agent stack. Maintain control of your data, memory, and security posture (JWT-based RBAC), and turn your agent platform into a learning loop with simulations and usage data.

Get started

Hand this prompt to your coding agent (Claude Code, Cursor, 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.

Your coding agent will set up your agent platform and run it locally using Docker, giving you a REST API for serving your agents, a Postgres database for storing your data and traces, an MCP server, and a control plane.

Deploying somewhere else? Use the same prompt but point it to a different repo. The starter templates are identical except for the deploy scripts: swap agentos-railway for agentos-docker, agentos-aws, agentos-gcp, agentos-azure, agentos-fly, agentos-render, agentos-modal, or agentos-helm.

Prefer to code by hand?

Features

Production API. 50+ endpoints with SSE and websockets to build a product on top.
Storage. Store sessions, memory, knowledge, and traces in your own database.
100+ integrations. Connect to GitHub, Slack, Postgres, and more using pre-built toolkits.
Context Providers. Access live data from Slack, Drive, wikis, MCP, and custom sources.
Human approval. Pause runs for user confirmation. Block tools that require admin approval.
Observability. Monitor with OpenTelemetry tracing, run history, and audit logs.
Security. Get JWT-based RBAC and multi-user, multi-tenant isolation out of the box.
Interfaces. Expose your agents via Slack, Telegram, WhatsApp, Discord, AG-UI, A2A.
Scheduling. Cron-based scheduling and background jobs with no external infrastructure.
Deploy anywhere. Run on any cloud platform that runs containers. Docker, Railway, AWS, GCP.

Use Agno with your coding agent

Two options:

Recommended: Add Agno docs as an MCP server. Add docs.agno.com/mcp to your favourite coding agent.
Add Agno docs as an indexed source. In Cursor: Settings → Indexing & Docs → Add https://docs.agno.com/llms-full.txt. Also works in VSCode, Windsurf, and similar tools.

Read the full guide here.

Community

X: follow for releases and demos
Newsletter: monthly updates on what's shipping

Contributing

See the contributing guide.

License

Agno is distributed under the Apache-2.0 license.

Telemetry

Agno sends a telemetry event per agent run so we know which model providers to prioritize. Prompts, messages, and outputs are never sent. Disable by setting AGNO_TELEMETRY=false.

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Frequently asked questions

Is Agno free to use?

Agno is open source under the Apache-2.0 licence. There is no licence fee and no seat count — you can self-host it or, where the project offers one, pay a vendor for a managed version instead.

What does Agno do?

Model-agnostic platform for building intelligent AI agents

What is Agno written in?

Agno is primarily written in Python. Its source is publicly available at https://github.com/agno-agi/agno, and it has 42,219 GitHub stars.