Agno

Agno is an open-source Python framework and runtime for building AI agents and running them as production services inside your own cloud. It goes further than a library: alongside the SDK for agents, teams and workflows, its AgentOS layer provides the API server, MCP server, authentication, scheduling and durable execution that teams usually assemble by hand. A browser-based control plane connects directly to your runtime, so traces, sessions and memory never leave your database.

What is Agno used for?

Agno is used by engineering teams that need agents to behave like dependable backend services. Typical uses include:

• Building agents that call internal APIs, databases and MCP servers as tools
• Combining specialist agents into teams that delegate work to each other
• Writing workflows with routing, conditions, loops and parallel steps
• Serving one agent to your product over REST, to Claude and ChatGPT over MCP, and to Slack or Discord
• Adding human approvals, schedules and resume or replay for long-running jobs
• Reviewing chats, traces, memory and evaluations in the control plane

Who Agno is best for

Agno fits Python developers, platform teams and startups that want full ownership of their agent stack, including where data is stored. It suits companies with security or compliance needs that rule out hosted agent platforms. It also appeals to teams using coding agents, since Agno provides templates and setup prompts designed for them. Nontechnical users and teams without someone to run infrastructure should choose a hosted builder.

Agno pricing

As of October 2026, Agno's Free plan costs $0 and includes unlimited usage and retention, the ability to run anywhere, support for the Agno SDK and other frameworks, a control plane for your local AgentOS, templates and community support. Pro costs $150 per month and adds a control plane for live AgentOS deployments with one live connection, 3 team seats, basic role-based access and email support. Extra seats cost $30 per month, extra live connections $95 per month, and SAML SSO $300 per month. A 14-day free trial of Pro is available. Enterprise is custom and adds governance, end-user audit logs, custom RBAC and Slack Connect support. Agno does not charge per event, compute or storage.

Agno limitations

• You host the runtime and database, so uptime and scaling are your responsibility
• Monitoring live deployments from the control plane requires Pro
• The SDK is Python, so TypeScript teams need another framework
• Agents still incur model costs from whichever providers you use

Agno vs alternatives

LangChain is the better pick when you want the widest ecosystem of integrations and a large body of tutorials and community answers. LlamaIndex is stronger when retrieval over complex documents is the central problem. AutoGPT suits people who want an autonomous agent builder with a visual interface rather than writing Python. Agno wins when you want a framework plus a production runtime and control plane that keep all agent data inside your own cloud.

Tips for getting started with Agno

Start from one of the template repositories for your cloud provider, which set up AgentOS with PostgreSQL storage. Build a single agent with two or three tools, then expose it through the MCP server and test it from Claude or ChatGPT. Add memory and knowledge only once the base agent is reliable. Use the free local control plane to inspect traces before paying for live connections.

Agno FAQ

Is Agno free?

Yes. Agno is open source under Apache 2.0 and its Free plan has unlimited usage. Pro costs $150 per month for a live control plane connection and team seats.

What language does Agno use?

Agno's SDK is a Python framework for building agents, teams and workflows, which then run as services on AgentOS.

Can Agno agents work in Claude and ChatGPT?

Yes. AgentOS includes an MCP server, so agents you build with Agno can be used from Claude and ChatGPT as well as from Slack, Discord and your own product.

Agno vs LangChain: which is better?

Agno is better if you want a framework with a built-in production runtime that runs in your cloud, while LangChain is better for its larger integration ecosystem.