Agno is an open-source Python framework and runtime for building agent platforms that a team owns end to end. Python developers use it to define agents, teams, and workflows in code, serve them from a FastAPI runtime in their own cloud, and operate them from a shared control plane. It suits teams that want production agents with their data, memory, and access control inside their own infrastructure rather than inside a vendor's.[1][2]
Quick verdict
Python teams shipping production agents in their own cloud will get the most from Agno. Its code-first SDK, self-hosted AgentOS runtime, and flat control-plane pricing cover the full build-run-manage lifecycle without per-event metering. Non-developers and teams wanting fully managed hosting should choose something else, since you write Python and run the runtime yourself. If your platform must live in your VPC with predictable seat-based pricing, choose Agno; if you want graphs-first orchestration or a managed black box, choose LangGraph or a hosted assistant instead.[1][2]
Key features
Python-first agents, teams, and workflows Define the atomic agent, multi-agent teams, and deterministic workflows directly in Python, with shared context and handoffs between members.[1][2]
AgentOS runtime you own Serving happens through a FastAPI application in the operator's infrastructure, with more than 50 endpoints covering runs, sessions, memory, knowledge, traces, evaluations, and scheduling over REST, SSE, and websockets.[1]
Your database holds everything Sessions, memory, knowledge, and traces persist in SQLite for quick starts and Postgres with pgvector for production, with table auto-provisioning and per-component database control.[1]
One hundred-plus integrations Prebuilt toolkits connect GitHub, Slack, Postgres, and more, while context providers pull live data from Slack, Drive, wikis, MCP servers, and custom sources.[1]
Approvals and tenant isolation Runs pause for user confirmation, blockable tools require admin approval, and JWT-based RBAC gives multi-user, multi-tenant isolation out of the box.[1][2]
Serve anywhere agents meet users The same deployment exposes REST, an MCP server, and Slack, Telegram, WhatsApp, and Discord interfaces, and can plug into Claude or ChatGPT as a custom connector on any plan.[1]
Scheduling with durable queues Cron schedules and background jobs run without external infrastructure, and accepted jobs can persist through restarts.[1]
Deploy on any container cloud Identical starter templates target Docker, Railway, AWS, GCP, Azure, Fly, Render, Modal, and Kubernetes Helm, and the runtime drops into an existing FastAPI app.[1]
Who will love it
The SDK-to-runtime path keeps code, data, JWT access control, and audit trails inside the team's own VPC, which fits regulated or security-conscious deployments. Security is framed as ownership throughout, with SAML SSO, custom RBAC, and audit scope reserved for the enterprise tier.[1][2]
The control plane reads the operator's runtime directly in the browser, Agno never holds a copy, and retention is infinite and entirely the operator's call. Connectors to Claude and ChatGPT on every plan mean those agents still meet users where they already work.[1]
The runtime is free at any scale with no per-event, token, or egress fees, so growing usage does not grow the Agno bill; teams pay seats and live connections only. A 14-day Pro trial lets a team evaluate the control plane against its own instance before committing.[1]
Who should avoid it
Everything starts with Python code, model keys, and a database; no verified no-code path exists for building agents.[1]
Agno holds no data and runs nothing for you, so provisioning, uptime, backups, and scaling the runtime are the operator's job. The documented answer to production questions is consistently more configuration in your own cloud, not a managed upgrade path.[1][2]
A team that only needs one simple assistant will carry platform machinery, tenants, and control-plane concepts it never uses.[1]
Alternatives and compatibility
Against LangGraph, choose graphs-first orchestration when the team's mental model and hiring are already LangChain-shaped; Agno instead emphasizes plain Python control flow plus the serving runtime.[1]
Against CrewAI, choose the role-and-crew metaphor when it matches the org chart; Agno's teams cover similar ground with the runtime and control plane bundled in.[1]
Against managed assistants, choose the black box when nobody on the team writes backend code or wants to run infrastructure. Teams already on FastAPI get an extra incentive: the runtime mounts into an existing application rather than running as a separate sidecar.[1][2]
Questions worth asking
What is the best Agno alternative for non-technical users?
A managed AI assistant is the safer choice, since Agno starts with Python code, provider keys, and self-hosted infrastructure. Agno fits non-developers only as end users of agents a technical team builds and runs.[1]
Is Agno really no-code?
No. Agents, teams, workflows, databases, and deployments are all defined in Python and configuration; the control plane operates what developers built but does not replace building it.[1]
How much does Agno cost per month?
The SDK and AgentOS runtime are open source and free at any scale, with no per-event, token, or egress fees; model usage bills separately through the team's own provider keys. The control plane is free against a local instance, while Pro costs 150 dollars per month for three team seats and one live connection, with extra seats at 30 dollars and extra connections at 95 dollars each; a 14-day Pro trial is available. Prices checked October 7, 2026.[1]
Sources and editorial review
Source research. Reviewed on October 7, 2026. Written by Sanjib Sah. AI assisted; reviewed by a human editor.
We have not run or tested this product.
- agno-agi/agno README
official · Observed October 7, 2026
Official repository README: build-run-manage lifecycle, SDK, AgentOS runtime, own-stack security, integrations, deploy targets, Apache 2.0 licence, telemetry opt-out. Read October 7, 2026. Star count 42,598 taken from catalogue snapshot, not this page.
- Agno AgentOS Runtime Overview
official · Observed October 7, 2026
Official runtime documentation: FastAPI ownership, 50-plus endpoints, database options, approvals, interfaces, scheduler, observability. Read October 7, 2026.
- Agno Pricing
official · Observed October 7, 2026
Official pricing: cloud tiers, Pro 150 dollars monthly with 3 seats and 1 connection, extra seats and connections, no usage fees, 14-day trial, enterprise SSO. Read October 7, 2026. Page also carries vendor-published customer quotes, excluded as testimonial evidence by rule.
Compared with these products
No explicit proprietary baseline is recorded.