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Here is a full example of an AgentOS with multiple agents and teams. It also shows how to instantiate agents with a database, knowledge base, and tools.

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Code

cookbook/06_agent_os/demo.py
"""
AgentOS Demo

Prerequisites:
uv pip install -U fastapi uvicorn sqlalchemy pgvector psycopg openai mcp
"""

from agno.agent import Agent
from agno.db.postgres import PostgresDb
from agno.knowledge.knowledge import Knowledge
from agno.models.openai import OpenAIResponses
from agno.os import AgentOS
from agno.team import Team
from agno.tools.hackernews import HackerNewsTools
from agno.tools.mcp import MCPTools
from agno.vectordb.pgvector import PgVector

# Database connection
db_url = "postgresql+psycopg://ai:ai@localhost:5532/ai"

# Create Postgres-backed memory store
db = PostgresDb(db_url=db_url)

# Create Postgres-backed vector store
vector_db = PgVector(
    db_url=db_url,
    table_name="agno_docs",
)
knowledge = Knowledge(
    name="Agno Docs",
    contents_db=db,
    vector_db=vector_db,
)

# Create your agents
agno_agent = Agent(
    name="Agno Agent",
    model=OpenAIResponses(id="gpt-5.2"),
    tools=[MCPTools(transport="streamable-http", url="https://docs.agno.com/mcp")],
    db=db,
    update_memory_on_run=True,
    knowledge=knowledge,
    markdown=True,
)

simple_agent = Agent(
    name="Simple Agent",
    role="Simple agent",
    id="simple_agent",
    model=OpenAIResponses(id="gpt-5.2"),
    instructions=["You are a simple agent"],
    db=db,
    update_memory_on_run=True,
)

research_agent = Agent(
    name="Research Agent",
    role="Research agent",
    id="research_agent",
    model=OpenAIResponses(id="gpt-5.2"),
    instructions=["You are a research agent"],
    tools=[HackerNewsTools()],
    db=db,
    update_memory_on_run=True,
)

# Create a team
research_team = Team(
    name="Research Team",
    description="A team of agents that research the web",
    members=[research_agent, simple_agent],
    model=OpenAIResponses(id="gpt-5.2"),
    id="research_team",
    instructions=[
        "You are the lead researcher of a research team! 🔍",
    ],
    db=db,
    update_memory_on_run=True,
    add_datetime_to_context=True,
    markdown=True,
)

# Create the AgentOS
agent_os = AgentOS(
    id="agentos-demo",
    agents=[agno_agent],
    teams=[research_team],
)
app = agent_os.get_app()


if __name__ == "__main__":
    agent_os.serve(app="demo:app", port=7777)

​
Usage

1

Set up your virtual environment

uv venv --python 3.12
source .venv/bin/activate
2

Set Environment Variables

export OPENAI_API_KEY=your_openai_api_key
export OS_SECURITY_KEY=your_security_key  # Optional for authentication
3

Install dependencies

uv pip install -U fastapi uvicorn sqlalchemy pgvector psycopg openai mcp agno
4

Setup PostgreSQL Database

# Using Docker
docker run -d \
  --name agno-postgres \
  -e POSTGRES_DB=ai \
  -e POSTGRES_USER=ai \
  -e POSTGRES_PASSWORD=ai \
  -p 5532:5432 \
  pgvector/pgvector:pg17
5

Run Example

python cookbook/06_agent_os/demo.py