psql -U postgres

CREATE USER toolbox_user WITH PASSWORD 'my-password';
CREATE DATABASE toolbox_db;
GRANT ALL PRIVILEGES ON DATABASE toolbox_db TO toolbox_user;
ALTER DATABASE toolbox_db OWNER TO toolbox_user;

\c toolbox_db toolbox_user

CREATE TABLE hotels(
  id            INTEGER NOT NULL PRIMARY KEY,
  name          VARCHAR NOT NULL,
  location      VARCHAR NOT NULL,
  price_tier    VARCHAR NOT NULL,
  booked        BIT     NOT NULL
);

INSERT INTO hotels(id, name, location, price_tier, booked)
VALUES
  (1, 'Hilton Basel', 'Basel', 'Luxury', B'0'),
  (2, 'Marriott Zurich', 'Zurich', 'Upscale', B'0'),
  (3, 'Hyatt Regency Basel', 'Basel', 'Upper Upscale', B'0');

brew install mcp-toolbox

sources:
  my-pg-source:
    kind: postgres
    host: 127.0.0.1
    port: 5432
    database: toolbox_db
    user: toolbox_user
    password: my-password

tools:
  search-hotels-by-location:
    kind: postgres-sql
    source: my-pg-source
    description: Search for hotels based on location.
    parameters:
      - name: location
        type: string
        description: The location of the hotel.
    statement: SELECT id, name, location, price_tier FROM hotels WHERE location ILIKE '%' || $1 || '%';
  book-hotel:
    kind: postgres-sql
    source: my-pg-source
    description: >-
        Book a hotel by its ID. If the hotel is successfully booked, returns a confirmation message.
    parameters:
      - name: hotel_id
        type: integer
        description: The ID of the hotel to book.
    statement: UPDATE hotels SET booked = B'1' WHERE id = $1;

toolsets:
  hotel_toolset:
    - search-hotels-by-location
    - book-hotel

toolbox --tools-file "tools.yaml"

!pip install toolbox-langchain

from toolbox_langchain import ToolboxClient

with ToolboxClient("http://127.0.0.1:5000") as client:
    search_tool = await client.aload_tool("search-hotels-by-location")

from toolbox_langchain import ToolboxClient

with ToolboxClient("http://127.0.0.1:5000") as client:
    search_tool = await client.aload_tool("search-hotels-by-location")
    results = search_tool.invoke({"location": "Basel"})
    print(results)

[{"id":1,"location":"Basel","name":"Hilton Basel","price_tier":"Luxury"},{"id":3,"location":"Basel","name":"Hyatt Regency Basel","price_tier":"Upper Upscale"}]

pip install -qU toolbox-langchain langgraph langchain-google-vertexai

from langchain.agents import create_agent
from langchain_google_vertexai import ChatVertexAI
from langgraph.checkpoint.memory import MemorySaver
from toolbox_langchain import ToolboxClient


prompt = """
You're a helpful hotel assistant. You handle hotel searching and booking.
When the user searches for a hotel, list the full details for each hotel found: id, name, location, and price tier.
Always use the hotel ID for booking operations.
For any bookings, provide a clear confirmation message.
Don't ask for clarification or confirmation from the user; perform the requested action directly.
"""


async def run_queries(agent_executor):
    config = {"configurable": {"thread_id": "hotel-thread-1"}}

    # --- Query 1: Search for hotels ---
    query1 = "I need to find a hotel in Basel."
    print(f'\n--- USER: "{query1}" ---')
    inputs1 = {"messages": [("user", prompt + query1)]}
    async for event in agent_executor.astream_events(
        inputs1, config=config, version="v2"
    ):
        if event["event"] == "on_chat_model_end" and event["data"]["output"].content:
            print(f"--- AGENT: ---\n{event['data']['output'].content}")

    # --- Query 2: Book a hotel ---
    query2 = "Great, please book the Hyatt Regency Basel for me."
    print(f'\n--- USER: "{query2}" ---')
    inputs2 = {"messages": [("user", query2)]}
    async for event in agent_executor.astream_events(
        inputs2, config=config, version="v2"
    ):
        if event["event"] == "on_chat_model_end" and event["data"]["output"].content:
            print(f"--- AGENT: ---\n{event['data']['output'].content}")

async def main():
    await run_hotel_agent()


async def run_hotel_agent():
    model = ChatVertexAI(model_name="gemini-2.5-flash")

    # Load the tools from the running MCP Toolbox server
    async with ToolboxClient("http://127.0.0.1:5000") as client:
        tools = await client.aload_toolset("hotel_toolset")

        agent = create_agent(model, tools, checkpointer=MemorySaver())

        await run_queries(agent)


await main()