What it is
Agno, formerly Phidata, is a Python framework for building agents and multi-agent teams. It ships with sessions, memory, knowledge bases stored in your own database, human-approval pauses and more than 100 prebuilt tool integrations.
AgentOS is its runtime: a FastAPI application that serves your agents as an API with streaming and background runs, and can also expose them as an MCP server or in Slack, Discord, Telegram and WhatsApp. It runs in your own cloud and writes state to databases you configure.
A web control plane for chat, traces, memory, evaluations and approvals is free against a local AgentOS. Connecting it to a live deployment needs the Pro plan at $150 a month.
Our review
Agno's argument is AgentOS, which saves a team from building its own serving layer. Sessions, memory, knowledge, streaming and background runs come in one FastAPI app, and the same agents can be exposed over MCP or in Slack. The project moves quickly: five releases, 3.1.5 to 3.1.9, shipped between 19 and 22 October 2026.
The defaults deserve more attention than the features. According to the security docs, AgentOS runs in a "none" mode with no central credential requirement unless you set OS_SECURITY_KEY or a JWT source, and the docs recommend JWT with role-based access for production. On an unauthenticated MCP server, service-account tokens do nothing unless you add an auth layer. GitHub lists a critical advisory for arbitrary code execution through eval() in function calls (June 2026), a high-severity SQL injection (July 2026) and a bug that let session state overwrite between users (October 2025).
The commercial side is clearer than most. The control plane connects from the browser directly to your runtime, and state stays in your databases. Pro costs $150 a month for one live connection and three seats; extra seats are $30, extra connections $95 and SAML SSO $300, so a six-person team watching production and staging pays $335 a month, or $635 with SSO. The pricing page does not mention SOC 2.
Reviewers note that LangGraph gives finer control over intricate flows, and Agno's large speed figures are its own. The more useful comparison is with writing the serving layer yourself on FastAPI: Agno saves that work, and the price is adopting its session and auth model wholesale, defaults included.
Where it earns its place
A backend engineer at a 20-person fintech adding an internal research agent
Serve one agent to staff over an authenticated API with per-user sessions
Build the agent in Python, wrap it in AgentOS, deploy it to your own cloud with Postgres for state, and switch on JWT authorisation before exposing it, because the default is none. The runtime is free; the cost is hosting and model tokens.
A product team shipping an assistant inside ChatGPT and Claude
Expose the same agent over MCP and REST without two codebases
AgentOS serves agents over MCP alongside REST. Configure mcp_auth explicitly, since service-account tokens are ignored on an MCP server with no auth layer.
An engineering manager running a six-person AI team
Give everyone traces, approvals and metrics on the production agent
Pro at $150 a month covers one live connection and three seats; three extra seats ($90) and a staging connection ($95) bring it to $335 a month, and SAML SSO adds $300. Enterprise adds end-user identity, roles and audit logs at custom pricing.
Before you commit
- Setup
- pip install agno (Python 3.9+; 3.1.9 at the time of checking). An agent runs in a plain script, and AgentOS wraps it as a FastAPI app; the control plane connects to a local AgentOS for free.
- Integrations
- 100+ prebuilt tools, most model providers, REST with streaming, MCP serving, Slack, Discord, Telegram and WhatsApp channels, and databases of your choice for sessions, memory and knowledge.
- Data and privacy
- AgentOS writes runtime state to your databases, and the control plane connects from the browser straight to your runtime. Auth is off by default. AGNO_TELEMETRY=false disables telemetry for agents, teams and workflows; AgentOS and eval telemetry are set per instance. Three GitHub advisories, one critical.
- Cost at scale
- The framework and runtime are free; you pay for hosting and model calls. The control plane is $150 a month on Pro plus $30 per extra seat, $95 per extra connection and $300 for SAML SSO; Enterprise is custom.
- Limits
- 1,924 open issues and pull requests. Patch releases arrive almost daily, so pin versions. Python only, and SOC 2 is not mentioned on the pricing page.
What's good
- AgentOS serves agents as a REST API, MCP server or chat bot
- Sessions, memory and knowledge stored in your own database
- Control plane talks to your runtime directly from the browser
- Releases most days
What's not
- AgentOS runs with no authentication by default
- Critical eval() code-execution advisory in June 2026
- Monitoring a live deployment costs $150/month and up
- Python only; less flow control than LangGraph
Best for
Python teams that want to run production agents on their own infrastructure with minimal plumbing.
Alternatives
Agno: common questions
- Is Agno worth it?
- Agno turns a Python agent into a served API with very little glue, but that API ships with authentication switched off. We rate it 4.1 out of 5.
- How much does Agno cost?
- Framework and AgentOS free under Apache 2.0. Control plane: free against a local AgentOS; Pro $150/month (one live connection, three seats, extra seats $30, SAML SSO $300); Enterprise custom.
- What are the downsides of Agno?
- AgentOS runs with no authentication by default; critical eval() code-execution advisory in June 2026; monitoring a live deployment costs $150/month and up; python only; less flow control than LangGraph.
- Who is Agno best for?
- Python teams that want to run production agents on their own infrastructure with minimal plumbing.
- How much does Agno cost for a team or in production?
- The framework and runtime are free; you pay for hosting and model calls. The control plane is $150 a month on Pro plus $30 per extra seat, $95 per extra connection and $300 for SAML SSO; Enterprise is custom.
- Is Agno safe for company data?
- AgentOS writes runtime state to your databases, and the control plane connects from the browser straight to your runtime. Auth is off by default. AGNO_TELEMETRY=false disables telemetry for agents, teams and workflows; AgentOS and eval telemetry are set per instance. Three GitHub advisories, one critical.
- What are the best Agno alternatives?
- The closest alternatives we have reviewed are CrewAI, LangGraph and Pydantic AI.
Answers checked Oct 23, 2026.
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