Python agent framework
Agno’s Python framework provides ready-made pieces for LLMs, memory, tools, and knowledge so developers can focus on agent behavior instead of wiring everything together from scratch.
Agno
RevendiquerAgno is an open-source Python framework for building AI agents and multi-agent workflows, with AgentOS for production API services in your own cloud.
What Agno does
Agno is an open-source Python framework for building AI agents, teams of agents, and workflows, paired with AgentOS, an agentic operating system that turns those systems into an API server and control plane. The product is aimed at developers and teams that want to build multi-agent systems without spending months assembling the runtime and operations layer themselves.
The framework covers agent construction, memory, knowledge retrieval, tools, guardrails, and model integration. AgentOS adds the production layer: prebuilt API endpoints, session and trace monitoring, approval flows, RBAC, audit logs, and a web console for operating running systems inside your own cloud.
Core capabilities
Multi-agent orchestration
The framework supports composing multiple agents that can plan, communicate, and delegate work to one another for more complex workflows.
Unified sync and async API
Agno describes a unified API for sync and async use, aimed at reducing event-loop friction and keeping code changes minimal when switching execution style.
State and reliability features
Built-in memory, session storage, domain knowledge, chat history, retries, error handling, and persistent state are presented as part of the framework’s production-oriented foundation.
Governance and tool access
The source says Agno includes guardrails, moderation, human-in-the-loop flows, and integration with tools and MCP so agents can act with oversight and connect to external systems.
Multimodal and integration support
Agno supports text, images, audio, and video, and the source mentions interoperability with OpenAI, Anthropic, Google Gemini, Ollama, vector databases, Slack, Notion, AWS S3, and GCP.
Common ways teams use Agno
Prototype a first agent
Build an agent from a small Python codebase, then expand it with memory, tools, and knowledge as the workflow grows.
Run multi-agent workflows
Coordinate several agents that can plan, delegate, and share context for multi-step work such as research or support triage.
Operate production systems
Expose agents, teams, and workflows through API endpoints and monitor live sessions, traces, and evaluations in the AgentOS control plane.
Add review and governance
Apply human approval steps and audit logging when an agent needs oversight before completing sensitive actions.
Extend agents with tools and knowledge
Connect agents to external data sources and tools through MCP, vector databases, cloud storage, or collaboration apps where supported by the source.
Pros and Cons
Pros
- Combines a Python agent framework with a production runtime in one product family.
- Supports multi-agent workflows, memory, knowledge, tool use, and human oversight.
- Offers a unified path from prototype to production with API and control-plane capabilities.
- Emphasizes private, in-cloud operation with data staying inside the customer’s environment.
- Provides pricing options from free development use through Pro and Enterprise plans.
Cons
- The source is strongest on Python-based development and does not indicate support for other programming languages.
- Some integration details are only described at a high level, so the exact setup for every external tool or platform is not fully specified on the source pages.
FAQ
What is Agno?
Agno is an open-source Python framework for building and running AI agents. The source describes it as providing ready-made components for LLM interfaces, memory, knowledge retrieval, and tool integrations, plus an AgentOS layer for running agents and workflows as an API server.
Who is Agno for?
Agno is built for Python developers. The source says it works with common Python environments and package managers, and that its framework is designed to get agents from idea to multi-agent system in a few lines of code.
Can Agno support multi-agent systems?
Agno supports composing multiple agents that can plan, communicate, and delegate tasks. The source also describes AgentOS as providing API endpoints, sessions, memory, knowledge, traces, and control-plane tooling for running agent systems.
Can Agno work with different model providers?
The source says Agno supports plug-and-play LLM integrations, including OpenAI GPT, Anthropic Claude, Google Gemini, and open-source models through Ollama or other providers. It also says switching models does not require rewriting core logic.
Does Agno have a free or paid plan?
Yes. The pricing page shows a Free plan for building agent systems and paid Pro and Enterprise plans for managing production systems. The pricing copy also emphasizes that no data leaves your system and there are no per-event fees or surprise egress costs.
Quick Facts
- Category
- Developer Tool
- Primary platform
- Python
- Main product pieces
- Agno framework and AgentOS
- Deployment model
- Runs in your cloud / BYOC
- Pricing signal
- Free, Pro, and Enterprise plans
- Source domain
- agno.com
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