cookbook/91_tools/mcp/mcp_toolbox_demo/README.md
This demo showcases how to set up and run an Agno Agent that can interact with a PostgreSQL database through the MCP Toolbox for Databases. The agent acts as a hotel assistant capable of searching, booking, and canceling hotel reservations.
MCP Toolbox for Databases (MCP Toolbox) provides a unified interface for AI agents to interact with databases.
In this demo, we have a collection of tools (defined in config/tools.yaml) that allow the agent to perform various hotel management tasks, such as searching for hotels, making bookings, and retrieving hotel information. The tools are groups into two toolsets:
hotel-management: For searching and retrieving hotel informationbooking-system: For handling reservations and cancellationsRead more about the MCP Toolbox confiuration here: MCP Toolbox Configuration.
uv package managerThe demo includes:
Start the MCP Toolbox and PostgreSQL database using Docker Compose (docker-compose.yml).
Navigate to the demo directory:
cd cookbook/90_tools/mcp/mcp_toolbox_demo
# Start all services in detached mode
docker-compose up -d
For Podman users:
podman compose up -d
Check that both containers are running:
docker-compose ps
Test the database connection:
docker-compose exec db psql -U toolbox_user -d toolbox_db -c "SELECT COUNT(*) FROM hotels;"
You should see a count of the hotels in the database.
# Install dependencies using uv
uv sync
Setup OpenAI API key:
export OPENAI_API_KEY="your_openai_api_key"
Start the agent:
# Activate the virtual environment and run the agent or use uv
uv run agent.py
The agent will start an interactive CLI where you can:
Once the agent is running, try these commands:
> Find hotels in Basel with Basel in it's name.
> Can you book the Hyatt Regency for me?
> Show me all luxury hotels
> What are the available hotels in Zurich?
To run the AgentOS:
uv run agent_os.py
Connect AgentOS Control Plane to http://localhost:7777 and interact with the agent via the web interface.
To run Hotel booking workflow:
uv run hotel_management_workflows.py
This workflow searches for boutique hotels in Zurich, then books the first available hotel. Here is sample output:
$ uv run workflow_demo.py
šØ Hotel Search and Booking Workflow
Request: Find luxury hotels in Zurich and book the first available one
==================================================
INFO Executing async step (non-streaming): Search Hotels
INFO Executing async step (non-streaming): Book Hotel
INFO Successfully created table 'agno_sessions'
ā
Workflow Result:
Content: The hotel has been successfully booked!
- **Hotel Name**: The Ritz-Carlton Zurich
- **Hotel ID**: 4
To run the type-safe agent:
uv run hotel_management_typesafe.py
This agent uses Pydantic models to ensure type safety when interacting with the database.
http://localhost:5001localhost:5432
toolbox_dbtoolbox_usermy-passwordNote: These are test credentials. Do not use in production.
The agent is configured with two toolsets:
hotel-management: Search and retrieve hotel informationbooking-system: Handle reservations and cancellationsuv sync to install all required packagesTo stop and remove all services:
docker-compose down -v