How to Use the Wine-Searcher MCP in LlamaIndex

Q: How do I query historical pricing using Wine-Searcher and LlamaIndex?

LlamaIndex indexes the results from marketprice. You can then build a knowledge base where you query past sessions to see how global market pricing for specific wines has changed over time.

Q: Can I use Wine-Searcher with LlamaIndex for pairing recommendations?

Yes. The grapeinfo tool provides variety details, which you can index alongside culinary documents. Your RAG application then semantically links the two data types to provide expert pairings.

Q: Does Wine-Searcher handle regional data for LlamaIndex?

The regioninfo tool provides essential terroir details. By indexing this, you create a searchable map of wine regions that can be queried alongside user documents.

Index wine data for semantic search: LlamaIndex with Wine-Searcher MCP Server.

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Connect Wine-Searcher MCP to LlamaIndex

Create your Vinkius account to connect Wine-Searcher to LlamaIndex 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-Searcher with LlamaIndex

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Semantic Search via MCP Server

When you run `wine_check`, the output isn't just a single answer; it's structured data (scores, regions, varieties). LlamaIndex indexes this result into your vector store. Later, you can query that knowledge base and get answers grounded in the actual API data. This means if you search for 'best pairing for Pinot Noir in Burgundy,' the index uses the results from `grape_info` and `region_info` to give a contextually accurate answer, not just a simple match.

Knowledge-Augmented Wine Analysis

The `search_wines` tool retrieves matching wines with pricing, scores, and merchant availability. By indexing this result, you create an evergreen resource. You can query past sessions or configurations weeks later and get answers based on the recorded API data. This makes your RAG app extremely powerful for historical trend analysis. The index keeps track of how `market_price` shifts over time.

RAG with Wine-Searcher MCP Server

`producer_info` gives you winery research data, which LlamaIndex indexes alongside your own documents. When a user asks about brand comparison, the system cross-references both uploaded manuals and live producer data. This combination allows you to build unified knowledge bases that combine external API facts with internal corporate documentation.

Setup guide

Set up Wine-Searcher MCP in LlamaIndex

Prerequisites

Python 3.10+ installed
llama-index-tools-mcp package
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai. The MCP tools package provides BasicMCPClient and McpToolSpec.
2

Connect with BasicMCPClient
Point BasicMCPClient to your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports SSE and Streamable HTTP transports.
3

Convert to LlamaIndex tools
Call mcp_tool_spec.to_tool_list_async() to convert all Wine-Searcher MCP tools into native FunctionTool objects that any LlamaIndex agent can use.
4

Run with any LLM
Create a FunctionAgent with the tools and your preferred LLM. Swap OpenAI for Anthropic, Gemini, or any LlamaIndex-supported provider.

agent.py

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

# Connect to the MCP
mcp_client = BasicMCPClient(
    "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
mcp_tool_spec = McpToolSpec(client=mcp_client)

# Convert MCP tools to LlamaIndex tools
tools = await mcp_tool_spec.to_tool_list_async()

# Create and run the agent
agent = FunctionAgent(
    tools=tools,
    llm=OpenAI(model="gpt-4o"),
    system_prompt="You have access to Wine-Searcher tools.",
)
response = await agent.run("List recent Wine-Searcher data")

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Wine-Searcher. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Wine-Searcher MCP in LlamaIndex

LlamaIndex indexes the results from `market_price`. You can then build a knowledge base where you query past sessions to see how global market pricing for specific wines has changed over time.

Yes. The `grape_info` tool provides variety details, which you can index alongside culinary documents. Your RAG application then semantically links the two data types to provide expert pairings.

The `region_info` tool provides essential terroir details. By indexing this, you create a searchable map of wine regions that can be queried alongside user documents.

It includes global pricing, critic scores, and producer information from 100,000+ merchants. The index makes this massive dataset searchable without hallucination.

The server touches e-commerce pricing and product metadata, including global market pricing and critic scores. It does not access personal user accounts or sensitive PII.

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