Agno

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Build, run, and manage agentic software at scale.
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<a href="https://docs.agno.com">Docs</a>
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<a href="https://github.com/agno-agi/agno/tree/main/cookbook">Cookbook</a>
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<a href="https://docs.agno.com/first-agent">Quickstart</a>
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<a href="https://www.agno.com/discord">Discord</a>
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What is Agno

Agno is the runtime for agentic software. Build agents, teams, and workflows. Run them as scalable services. Monitor and manage them in production.

| Layer | What it does |
|-------|--------------|
| Framework | Build agents, teams, and workflows with memory, knowledge, guardrails, and 100+ integrations. |
| Runtime | Serve your system in production with a stateless, session-scoped FastAPI backend. |
| Control Plane | Test, monitor, and manage your system using the AgentOS UI. |

Quick Start

Build a stateful, tool-using agent and serve it as a production API in ~20 lines.

from agno.agent import Agent
from agno.db.sqlite import SqliteDb
from agno.models.anthropic import Claude
from agno.os import AgentOS
from agno.tools.mcp import MCPTools
agno_assist = Agent(
    name="Agno Assist",
    model=Claude(id="claude-sonnet-4-6"),
    db=SqliteDb(db_file="agno.db"),
    tools=[MCPTools(url="https://docs.agno.com/mcp")],
    add_history_to_context=True,
    num_history_runs=3,
    markdown=True,
)
agent_os = AgentOS(agents=[agno_assist], tracing=True)
app = agent_os.get_app()

Run it:

export ANTHROPIC_API_KEY="*"
uvx --python 3.12 \
  --with "agno[os]" \
  --with anthropic \
  --with mcp \
  fastapi dev agno_assist.py

In ~20 lines, you get:

A stateful agent with streaming responses

Per-user, per-session isolation

A production API at http://localhost:8000

Native tracing

Connect to the AgentOS UI to monitor, manage, and test your agents.

Open os.agno.com and sign in.

Click "Add new OS" in the top navigation.

Select "Local" to connect to a local AgentOS.

Enter your endpoint URL (default: http://localhost:8000).

Name it "Local AgentOS".

Click "Connect".

https://github.com/user-attachments/assets/75258047-2471-4920-8874-30d68c492683

Open Chat, select your agent, and ask:

> What is Agno?

The agent retrieves context from the Agno MCP server and responds with grounded answers.

https://github.com/user-attachmen

... [truncated — view full README on GitHub]