How to Use the Wine Pairing & Sommelier MCP in Google ADK

Build enterprise wine pairing logic directly on your BigQuery data using the Google ADK.

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Connect Wine Pairing & Sommelier MCP to Google ADK

Create your Vinkius account to connect Wine Pairing & Sommelier to Google ADK and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Wine Pairing & Sommelier with Google ADK

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Deep Wine Descriptions (MCP Server)

Need to build out a comprehensive knowledge base? The `get_wine_description` tool provides detailed write-ups for any wine type. This is perfect for enriching content that already lives in BigQuery. Your agent can pull these descriptions and use the long context window (1M+ tokens) to correlate them with existing customer data.

Pairing Food/Wine at Scale

When dealing with enterprise-level menus, you need reliable pairings. `get_wine_pairing` takes food inputs like chocolate or salmon and returns suggested wines with product details. This scales well because it acts as a structured query on your data. The Google ADK allows the agent to process these recommendations against massive datasets stored in Vertex AI.

Running Complex Pairing Queries

For multi-step processes, like finding a dish first and then pairing it with wine, the full MCP Server toolset works. You combine `get_dish_for_wine` results with product pricing from `recommend_wines`. This allows your agent to execute complex business logic using its native Google Cloud integration.

Setup guide

Set up Wine Pairing & Sommelier MCP in Google ADK

Prerequisites

Python 3.10+ installed
google-adk package (pip install google-adk)
Active Vinkius subscription with a valid endpoint token

1

Install Google ADK

Run pip install google-adk to install the Agent Development Kit. MCP support is included via the McpToolset class.
2

Connect via SSE transport

Use McpToolset.from_server() with SseServerParams pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create an LlmAgent

Pass the returned mcp_tools list directly to LlmAgent(tools=mcp_tools). The ADK maps each MCP tool to a native Gemini function call — no manual schema definitions required.
4

Run with any Gemini model

The agent works with any Gemini model (gemini-2.0-flash, gemini-2.5-pro, etc.). Copy the full example on the right to get started with Wine Pairing & Sommelier tools in your ADK agent.

agent.py

from google.adk.agents import LlmAgent
from google.adk.tools.mcp_tool.mcp_toolset import McpToolset
from google.adk.tools.mcp_tool.mcp_session_manager import SseServerParams

# Connect to the MCP via SSE
mcp_tools, exit_stack = await McpToolset.from_server(
    connection_params=SseServerParams(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    )
)

# Create your agent with auto-discovered tools
agent = LlmAgent(
    name="Wine Pairing & Sommelier_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Wine Pairing & Sommelier tools via MCP.",
    tools=mcp_tools,
)

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Common questions about Wine Pairing & Sommelier MCP in Google ADK

Yes, it's built for that. The agent can take structured output from the server—like product names and ratings—and use them to query or augment your existing datasets in BigQuery.

You certainly can. The toolset provides core pairing logic for food groups (like pasta, steak). You just need to enrich the inputs or use your long-context reasoning to add seasonality context.

Because it runs on a powerful framework that supports 1M+ tokens, the agent maintains context across many queries. It keeps track of multiple pairing suggestions simultaneously.

The server primarily handles structured metadata: wine types, dish names, ratings (float), and pricing information. This is ideal for integrating into your enterprise schema.

You'll use the agent’s ability to connect to BigQuery. The server gives you the recommendations; your agent executes the final actions or joins that result set with your proprietary business metrics.

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