Agno

What it does

Agno takes agent definitions built with its Python SDK (agents, teams and workflows, with models, tools, instructions and memory) and, through AgentOS, serves them as a REST API and an MCP server. Agents can then be reached from your own product, from Claude and ChatGPT over MCP, or from chat apps such as Slack via Agno Interfaces.

Teams use Agno to build agents that need sessions, memory, knowledge, scheduling, human approvals and evaluations without writing that plumbing themselves. The Control Plane adds a hosted dashboard for traces, sessions, metrics and audit logs against a live AgentOS connection. Agno states the platform runs in your own cloud or database and that it does not hold a copy of your data.

Agno suits engineering teams building product copilots, support or research agents who are comfortable running containers and a Python codebase. The runtime and SDK are free and open source; Pro at $150 per month covers the control plane for a live deployment, with extra seats and connections billed separately. Enterprise features such as custom RBAC and a self-hosted control plane require contacting sales.

What it can do

• Build agents, teams and workflows with the Agno SDK, with models, tools, instructions, memory and knowledge.
• Serve agents as a REST API and MCP server through AgentOS, with sessions, resumable streaming and scheduling.
• Add human-in-the-loop approvals, guardrails and JWT-based RBAC to agent runs.
• Inspect runs with traces, sessions, metrics and evaluations in the Control Plane dashboard.
• Run agents in your own cloud or database, with the Control Plane reading your runtime directly.

Works with

• Claude and ChatGPT via MCP server
• Slack via Agno Interfaces
• WhatsApp via Agno Interfaces
• Docker, Railway, AWS, Fly.io and Google Cloud deployment guides

Example workflows

Serve a support agent to a product and Slack

Inputs: an Agno agent with docs and order-history tools. Steps: define the agent in the SDK, run it as AgentOS, expose the REST endpoint to your product and enable a Slack interface. Outputs: the same agent answering in-product and in Slack, with sessions visible in the Control Plane.

Schedule a weekly digest agent

Inputs: an agent that summarises product usage metrics. Steps: register it on the AgentOS scheduler and set a Friday-morning cadence. Outputs: a recurring run whose traces and results can be reviewed in the dashboard.

Before you choose

• The runtime and SDK are free and open source; the Control Plane is paid from Pro and Enterprise tiers.
• Serving agents over REST or MCP does not require a paid plan; Pro is for seeing and governing a live deployment.
• Enterprise features such as custom RBAC and a self-hosted control plane require contacting sales.

Listed under

• Coding
• DevOps and observability
• MCP and agent tools
• Sandboxes and infrastructure
• Agent framework
• Agent observability
• Agent platform
• Agents
• AI agents
• Developers

Get started

Create an account on the Control Plane, or clone a starter repository and run the setup skill with a coding agent.

1. Create an account at os.agno.com and open the Control Plane.
2. Choose a starter repository for your cloud (for example Docker or Railway) and clone it.
3. Run the setup-platform skill with a coding agent, then build and deploy your first agent as an AgentOS service.

Pro is billed monthly; extra seats are $30/month and extra live connections $95/month each. No per-event, token or egress fees. Pro offers a 14-day free trial.

14-day free trial.

Source: agno.com/pricing, checked 29 Oct 2026. Prices can change; check before you buy.

Sources for this overview

Product pages, documentation, and pricing checked 29 Oct 2026. Each source supports part of the overview; availability and prices can change.

• Agno: The Agent Platform That Builds Itself ↗www.agno.com
• Agno Pricing: Free Runtime, $150 for the Control Plane ↗www.agno.com
• Welcome to Agno | Agno ↗docs.agno.com

Company website

agno.com: product, pricing and policy pages

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knowledge_base

Last checked 29 Oct 2026. Every field keeps its source and date; unknown means we couldn’t confirm it.