What wines are covered?

The database covers all major wine varieties including Cabernet Sauvignon, Merlot, Pinot Noir, Chardonnay, Sauvignon Blanc, Riesling, Malbec, Prosecco, Champagne, and dozens more from wine regions worldwide.

Wine Pairing & Sommelier MCP Server for LlamaIndex 4 tools — connect in under 2 minutes

Name: Wine Pairing & Sommelier
Availability: InStock
Author: Vinkius

docs.llamaindex.ai/en/stable/module_guides/tools/mcp

Built by Vinkius GDPR 4 Tools Framework

LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Wine Pairing & Sommelier as an MCP tool provider through the Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.

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python

import asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

async def main():
    # Your Vinkius token — get it at cloud.vinkius.com
    mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
    mcp_tool_spec = McpToolSpec(client=mcp_client)
    tools = await mcp_tool_spec.to_tool_list_async()

    agent = FunctionAgent(
        tools=tools,
        llm=OpenAI(model="gpt-4o"),
        system_prompt=(
            "You are an assistant with access to Wine Pairing & Sommelier. "
            "You have 4 tools available."
        ),
    )

    response = await agent.run(
        "What tools are available in Wine Pairing & Sommelier?"
    )
    print(response)

asyncio.run(main())

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About Wine Pairing & Sommelier MCP Server

The Wine Pairing & Sommelier MCP Server transforms your AI agent into a knowledgeable wine expert. Powered by comprehensive wine data, it handles everything from food-wine pairing to specific bottle recommendations.

LlamaIndex agents combine Wine Pairing & Sommelier tool responses with indexed documents for comprehensive, grounded answers. Connect 4 tools through the Vinkius and query live data alongside vector stores and SQL databases in a single turn — ideal for hybrid search, data enrichment, and analytical workflows.

Core Capabilities

Food → Wine — Enter any dish or ingredient and get expert wine pairing suggestions.
Wine → Dish — Already have a wine? Discover the perfect dishes to pair with it.
Wine Descriptions — Learn about any wine variety: flavor profile, origin, and characteristics.
Product Recommendations — Get specific bottle suggestions with ratings, prices, and purchase links.

Uses the Spoonacular API key (same as Spoonacular MCP). An essential companion for hospitality, dining, and lifestyle AI applications.

The Wine Pairing & Sommelier MCP Server exposes 4 tools through the Vinkius. Connect it to LlamaIndex in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Wine Pairing & Sommelier to LlamaIndex via MCP

Follow these steps to integrate the Wine Pairing & Sommelier MCP Server with LlamaIndex.

Install dependencies

Run pip install llama-index-tools-mcp llama-index-llms-openai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.py and run: python agent.py

Explore tools

The agent discovers 4 tools from Wine Pairing & Sommelier

Why Use LlamaIndex with the Wine Pairing & Sommelier MCP Server

LlamaIndex provides unique advantages when paired with Wine Pairing & Sommelier through the Model Context Protocol.

Data-first architecture: LlamaIndex agents combine Wine Pairing & Sommelier tool responses with indexed documents for comprehensive, grounded answers

Query pipeline framework lets you chain Wine Pairing & Sommelier tool calls with transformations, filters, and re-rankers in a typed pipeline

Multi-source reasoning: agents can query Wine Pairing & Sommelier, a vector store, and a SQL database in a single turn and synthesize results

Observability integrations show exactly what Wine Pairing & Sommelier tools were called, what data was returned, and how it influenced the final answer

Wine Pairing & Sommelier + LlamaIndex Use Cases

Practical scenarios where LlamaIndex combined with the Wine Pairing & Sommelier MCP Server delivers measurable value.

Hybrid search: combine Wine Pairing & Sommelier real-time data with embedded document indexes for answers that are both current and comprehensive

Data enrichment: query Wine Pairing & Sommelier to augment indexed data with live information before generating user-facing responses

Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying Wine Pairing & Sommelier for fresh data

Analytical workflows: chain Wine Pairing & Sommelier queries with LlamaIndex's data connectors to build multi-source analytical reports

Wine Pairing & Sommelier MCP Tools for LlamaIndex (4)

These 4 tools become available when you connect Wine Pairing & Sommelier to LlamaIndex via MCP:

get_dish_for_wine

g. merlot, chardonnay, pinot noir, riesling) and get expert dish pairing recommendations. Find the perfect dish to pair with a wine

get_wine_description

Get a detailed description of a wine type

get_wine_pairing

g. steak, salmon, pasta, chocolate) and get expert wine pairing recommendations with specific product suggestions, ratings, and prices. Find the perfect wine to pair with a dish or ingredient

recommend_wines

Get specific wine product recommendations with ratings and prices

Example Prompts for Wine Pairing & Sommelier in LlamaIndex

Ready-to-use prompts you can give your LlamaIndex agent to start working with Wine Pairing & Sommelier immediately.

"What wine pairs best with grilled salmon?"

"What dishes pair well with an Argentinian Malbec?"

"Give me a description of a typical New Zealand Sauvignon Blanc."

Troubleshooting Wine Pairing & Sommelier MCP Server with LlamaIndex

Common issues when connecting Wine Pairing & Sommelier to LlamaIndex through the Vinkius, and how to resolve them.

BasicMCPClient not found

Install: pip install llama-index-tools-mcp

Wine Pairing & Sommelier + LlamaIndex FAQ

Common questions about integrating Wine Pairing & Sommelier MCP Server with LlamaIndex.

How does LlamaIndex connect to MCP servers?

Use the MCP client adapter to create a connection. LlamaIndex discovers all tools and wraps them as query engine tools compatible with any LlamaIndex agent.

Can I combine MCP tools with vector stores?

Yes. LlamaIndex agents can query Wine Pairing & Sommelier tools and vector store indexes in the same turn, combining real-time and embedded data for grounded responses.