Agno
What is Agno?
Agno is a Python framework and AgentOS runtime for teams that build and run AI agents in the same stack. It supports multi-agent systems, workflows, tools, memory and knowledge management, plus FastAPI scaffolding, per-session state, tracing, and evaluations. Agno integrates with Slack, Notion, Google Sheets, and Stripe, and works with OpenAI, Anthropic, Google Gemini, Ollama, and Mistral. Plans run Free, Pro $150/mo, and Enterprise custom.
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At a glance
- Agno is best for Python teams who want to ship production agents without building runtime infrastructure.
- Free; Pro $150/mo; Enterprise Custom
- Yes — Agno offers a clean Python API for building and running AI agents, plus FastAPI integration and a scalable AgentOS API.
What does Agno do?
Agno handles agent development and production runtime by pairing an open-source Python framework with AgentOS, so teams can build in Python and run the same system as a service. The framework supports multi-agent systems, workflows, tools, and memory/knowledge management, while the runtime adds session monitoring, metrics, evaluations, and a control plane for live or local deployments. Its FastAPI scaffolding and clean Python API help teams move from prototype to deployed service without rebuilding the stack. At scale, Agno shows private-by-default operation: your AgentOS runs in your cloud, and usage, logs, metrics, traces, memory, knowledge, sessions, and user data stay in your environment. The site points to 50+ endpoints, 3 dimensions, 40K GitHub stars, and 99.99% uptime. It also supports self-hosting, and the docs note a scalable AgentOS API plus FastAPI integration. Customers and builders cite quick setup, flexible async/sync use, and strong support for production monitoring.
Why use Agno?
- Agno separates the framework from the runtime, so teams can keep building in Python while offloading production infrastructure to AgentOS.
- Private-by-default deployment keeps logs, traces, memory, knowledge, and user data inside your cloud environment.
- Self-hosting and a self-hosted Control Plane give teams more control when managed hosting is not enough.
- The platform combines monitoring, evaluations, and session visibility in one stack, reducing the need to stitch together separate tools.
- Framework-agnostic design lets teams avoid locking their agent architecture to one model or provider path.
Who is Agno for?
- Python developers who want a framework-agnostic way to build and run agents.
- Platform teams who need production monitoring, control, and deployment for agent systems.
- AI engineers who want multi-agent workflows with memory and knowledge built in.
- Teams with strict data-control needs who prefer running AgentOS in their own cloud.
- Builders who want to move from prototype to live service with minimal infrastructure work.
What are Agno's key features?
FastAPI Scaffolding
Generates FastAPI-based agent services with 50+ endpoints, so teams can move from prototype to deployable API without wiring every route by hand.
Per-session state
Keeps state per session for chats and workflows, which matters when agents need continuity across turns, tools, and multi-step tasks.
JWT auth
Supports JWT authentication for API access, helping teams secure agent endpoints and control who can call production services.
RBAC
Adds role-based access control for AgentOS and live systems, giving organizations finer permission control across users, seats, and operations.
SSE Streaming
Streams agent output over SSE, so apps can show partial responses in real time instead of waiting for a full completion.
Tracing
Provides tracing with OpenTelemetry integration, making it easier to inspect agent behavior, debug failures, and understand latency across runs.
Background workers
Runs long tasks in background workers, which helps agents handle asynchronous jobs without blocking user requests or chat sessions.
Approval queue
Routes actions through an approval queue for human review, useful when agents need checks before executing sensitive steps.
What does Agno integrate with?
- LangGraph
- DSPy
- Claude Agent SDK
- Redis
- OpenTelemetry
- AWS
- Google Cloud
- Railway
- Pinecone
- Weaviate
- Qdrant
- AWS S3
- Slack
- Notion
- OpenAI
- Anthropic
- Google Gemini
- Ollama
- Mistral
- Stripe
- HubSpot
- Google Sheets
- Anthropic Claude
What are Agno's use cases?
Python agents for builders
Python developers use Agno to turn a prototype into a working agent service without locking into one framework, using FastAPI Scaffolding and Model-agnostic reasoning to keep the stack flexible. They can expose real endpoints, stream responses with SSE Streaming, and move from local experiments to a deployable service faster.
Production control for platform teams
Platform teams use Agno to monitor and govern live agent systems, using Tracing, Session monitoring, and Audit log to see what each agent did and why. With RBAC and JWT auth, they can give the right people access while keeping production controls tight.
Multi-agent workflows with memory
AI engineers use Agno to build multi-agent workflows that remember context and reuse knowledge, using Memory manager and Knowledge manager to keep sessions grounded in prior work. They can pair that with Background workers and Evaluations to run longer tasks and verify outputs before shipping.
Self-hosted agent services
Teams with strict data-control needs use Agno to run AgentOS in their own cloud, using Run securely in your own cloud and RBAC to keep sensitive workflows inside their environment. They still get Session monitoring and Approval queue for controlled operations without giving up visibility.
How does Agno work?
- Start by scaffolding your first agent service with FastAPI Scaffolding, then wire in your Python logic through the clean API and add Tools and MCP support for external actions.
- Connect state and knowledge next: configure Per-session state, Memory manager, and Knowledge manager so each conversation can remember context and retrieve the right information.
- Add production controls with JWT auth, RBAC, Rate limiting, and Approval queue, then use HITL and Audit log to review sensitive actions before they execute.
- Turn on Tracing, Session monitoring, and Evaluations to inspect runs, compare outputs, and catch regressions as your agents handle real traffic.
- Deploy the AgentOS in your own cloud or live environment, then keep Background workers and SSE Streaming running so users get responsive, reliable agent experiences.
How much does Agno cost?
Free
Free- For building agent systems
- Open Source
- Build multi-agent systems
- Run agent systems using the AgentOS
- Control Plane for local AgentOS
- Chat with agents, teams and workflows
- Session monitoring & metrics
- Knowledge & memory management
- System evaluations
- Jumpstart & community
- Pre-built production-ready codebases
- Community support and forums
Pro
$150/mo- For managing production systems
- Everything in Free
- 1 live connection
- 4 total seats included
- Unlimited usage
- Unlimited retention
- Unlimited chats
- Add-ons
- $30/mo per seat
- $95/mo per live connection
Enterprise
Custom- For mission critical, custom solutions
- Everything in Pro
- Support & scale
- Dedicated slack channel
- Dedicated technical lead
- Support SLA
- Customization
- Custom SSO and RBAC
- Custom agent solutions
- Self-hosted Control Plane
Frequently asked questions
What is Agno?
Agno is a Python framework and AgentOS runtime for teams that build and run AI agents in the same stack. It supports multi-agent systems, workflows, tools, memory and knowledge management, plus FastAPI scaffolding, per-session state, tracing, and evaluations. Agno integrates with Slack, Notion, Google Sheets, and Stripe, and works with OpenAI, Anthropic, Google Gemini, Ollama, and Mistral. Plans run Free, Pro $150/mo, and Enterprise custom.
How much does Agno cost? Is it free?
Agno has a free plan, with paid tiers including Pro at $150/mo, Enterprise at Custom.
What is Agno used for? Who is it for?
Agno is used for FastAPI Scaffolding, Per-session state, and JWT auth. It's built for Python developers, Platform teams, and AI engineers.
Does Agno have an API and what does it integrate with?
Agno offers a clean Python API for building and running AI agents, plus FastAPI integration and a scalable AgentOS API.
Editor's read
Check whether the Pro plan's 1 live connection is enough for your deployment shape. If you need more live AgentOS connections, the listed add-ons are $95/mo per live connection, so that limit changes the real monthly cost.
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