> ## Documentation Index
> Fetch the complete documentation index at: https://agno-v2.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Agent OS

> Serve a hotel booking assistant in AgentOS using MCPToolbox hotel and booking toolsets.

```python agent_os.py theme={null}
"""
Agent Os
=============================

Demonstrates agent os.
"""

from textwrap import dedent

from agno.agent import Agent
from agno.os import AgentOS
from agno.tools.mcp_toolbox import MCPToolbox

# ---------------------------------------------------------------------------
# Create Agent
# ---------------------------------------------------------------------------


url = "http://127.0.0.1:5001"

mcp_database_tools = MCPToolbox(
    url=url, toolsets=["hotel-management", "booking-system"]
)

agent = Agent(
    tools=[mcp_database_tools],
    instructions=dedent(
        """ \
        You're a helpful hotel assistant. You handle hotel searching, booking and
        cancellations. When the user searches for a hotel, mention it's name, id,
        location and price tier. Always mention hotel ids while performing any
        searches. This is very important for any operations. For any bookings or
        cancellations, please provide the appropriate confirmation. Be sure to
        update checkin or checkout dates if mentioned by the user.
        Don't ask for confirmations from the user.
    """
    ),
    markdown=True,
)


agent_os = AgentOS(
    name="Hotel Assistant",
    description="An agent that helps users find and book hotels.",
    agents=[agent],
)

app = agent_os.get_app()

# ---------------------------------------------------------------------------
# Run Agent
# ---------------------------------------------------------------------------

if __name__ == "__main__":
    agent_os.serve(app="agent_os:app", reload=True)
```

## Run the Example

<Snippet file="create-venv-step.mdx" />

**1. Install dependencies**

```bash theme={null}
uv pip install -U "agno[mcp,os]" openai toolbox-core
```

**2. Export your OpenAI API key**

```bash Mac/Linux theme={null}
export OPENAI_API_KEY="your_openai_api_key_here"
```

```bash Windows theme={null}
$Env:OPENAI_API_KEY="your_openai_api_key_here"
```

**3. Clone Agno**

Clone the pinned Agno source and run the remaining commands from its root:

```bash theme={null}
git clone https://github.com/agno-agi/agno.git
cd agno
git checkout v3.0.4
```

**4. Start MCP Toolbox**

Start the demo database and toolbox service on port 5001:

```bash theme={null}
cd cookbook/91_tools/mcp/mcp_toolbox_demo
docker compose up -d
cd ../../../..
```

**5. Run the example**

Run the example from the repository root:

```bash theme={null}
python cookbook/91_tools/mcp/mcp_toolbox_demo/agent_os.py
```

Full source: [cookbook/91\_tools/mcp/mcp\_toolbox\_demo/agent\_os.py](https://github.com/agno-agi/agno/blob/v3.0.4/cookbook/91_tools/mcp/mcp_toolbox_demo/agent_os.py)


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