​
Code

cookbook/agent_os/mcp/enable_mcp_example.py

from agno.agent import Agent
from agno.db.postgres import PostgresDb
from agno.models.anthropic import Claude
from agno.os import AgentOS
from agno.tools.duckduckgo import DuckDuckGoTools

# Setup the database
db = PostgresDb(db_url="postgresql+psycopg://ai:ai@localhost:5532/ai")

# Setup basic agents, teams and workflows
web_research_agent = Agent(
    id="web-research-agent",
    name="Web Research Agent",
    model=Claude(id="claude-sonnet-4-0"),
    db=db,
    tools=[DuckDuckGoTools()],
    add_history_to_context=True,
    num_history_runs=3,
    add_datetime_to_context=True,
    markdown=True,
)


# Setup our AgentOS with MCP enabled
agent_os = AgentOS(
    description="Example app with MCP enabled",
    agents=[web_research_agent],
    enable_mcp=True,  # This enables a LLM-friendly MCP server at /mcp
)

app = agent_os.get_app()

if __name__ == "__main__":
    """Run our AgentOS.

    You can see view your LLM-friendly MCP server at:
    http://localhost:7777/mcp

    """
    agent_os.serve(app="enable_mcp_example:app", reload=True)

​
Define a local test client

test_client.py
import asyncio

from agno.agent import Agent
from agno.models.anthropic import Claude
from agno.tools.mcp import MCPTools

# This is the URL of the MCP server we want to use.
server_url = "http://localhost:7777/mcp"


async def run_agent(message: str) -> None:
    async with MCPTools(transport="streamable-http", url=server_url) as mcp_tools:
        agent = Agent(
            model=Claude(id="claude-sonnet-4-0"),
            tools=[mcp_tools],
            markdown=True,
        )
        await agent.aprint_response(input=message, stream=True, markdown=True)


# Example usage
if __name__ == "__main__":
    asyncio.run(run_agent("Which agents do I have in my AgentOS?"))

​
Usage

1

Create a virtual environment

Open the Terminal and create a python virtual environment.
python3 -m venv .venv
source .venv/bin/activate
2

Set Environment Variables

export ANTHROPIC_API_KEY=your_anthropic_api_key
export DATABASE_URL=postgresql+psycopg://ai:ai@localhost:5532/ai  # Optional
3

Install libraries

pip install -U agno anthropic fastapi uvicorn sqlalchemy pgvector psycopg
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 Server

python cookbook/agent_os/mcp/enable_mcp_example.py
6

Run Test Client

python cookbook/agent_os/mcp/test_client.py