Engineers and researchers use Agno to build:

Level 1: Agents with tools and instructions (example).
Level 2: Agents with knowledge and storage (example).
Level 3: Agents with memory and reasoning (example).
Level 4: Agent Teams that can reason and collaborate (example).
Level 5: Agentic Workflows with state and determinism (example).

Example: Level 1 Reasoning Agent that uses the YFinance API to answer questions:

Reasoning Finance Agent

from agno.agent import Agent
from agno.models.anthropic import Claude
from agno.tools.reasoning import ReasoningTools
from agno.tools.yfinance import YFinanceTools

reasoning_agent = Agent(
    model=Claude(id="claude-sonnet-4-20250514"),
    tools=[
        ReasoningTools(add_instructions=True),
        YFinanceTools(stock_price=True, analyst_recommendations=True, company_info=True, company_news=True),
    ],
    instructions="Use tables to display data.",
    markdown=True,
)

Watch the reasoning finance agent in action

Getting Started

If you’re new to Agno, learn how to build your first Agent, chat with it on the playground and monitor it on app.agno.com.

Your first Agents

Learn how to build Agents with Agno

Agent Playground

Chat with your Agents using a beautiful Agent UI

Agent Monitoring

Monitor your Agents on agno.com

After that, dive deeper into the concepts below or explore the examples gallery to build real-world applications with Agno.

Why Agno?

Agno will help you build best-in-class, highly-performant agentic systems, saving you hours of research and boilerplate. Here are some key features that set Agno apart:

Model Agnostic: Agno provides a unified interface to 23+ model providers, no lock-in.
Highly performant: Agents instantiate in ~3μs and use ~6.5Kib memory on average.
Reasoning is a first class citizen: Reasoning improves reliability and is a must-have for complex autonomous agents. Agno supports 3 approaches to reasoning: Reasoning Models, ReasoningTools or our custom chain-of-thought approach.
Natively Multi-Modal: Agno Agents are natively multi-modal, they accept text, image, audio and video as input and generate text, image, audio and video as output.
Advanced Multi-Agent Architecture: Agno provides an industry leading multi-agent architecture (Agent Teams) with reasoning, memory, and shared context.
Built-in Agentic Search: Agents can search for information at runtime using 20+ vector databases. Agno provides state-of-the-art Agentic RAG, fully async and highly performant.
Built-in Memory & Session Storage: Agents come with built-in Storage & Memory drivers that give your Agents long-term memory and session storage.
Structured Outputs: Agno Agents can return fully-typed responses using model provided structured outputs or json_mode.
Pre-built FastAPI Routes: After building your Agents, serve them using pre-built FastAPI routes. 0 to production in minutes.
Monitoring: Monitor agent sessions and performance in real-time on agno.com.