How to Use the VineRadar MCP in LangChain

Q: How do I use VineRadar and LangChain to audit vintages?

You can build a chain that first uses searchvineyards based on location. Then, the second step takes those results and passes them into getwinedetails to pull specific vintage data for auditing.

Build multi-step reasoning pipelines for VineRadar using LangChain.

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Connect VineRadar MCP to LangChain

Create your Vinkius account to connect VineRadar to LangChain 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 VineRadar with LangChain

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Chaining Searches with LangChain MCP Server

You can chain searches together. First, use `search_vineyards` to narrow down a region by location. Next, feed the returned vineyard ID into `get_vineyard_details`. This gives you all the data points needed for your next step, like finding associated wines using `search_wines`.

Retrieving Specific Wine Data via LangChain

Need to validate a specific wine? Call `get_wine_details` right out of the gate. This returns everything on that bottle, from varietals to vintage. If you don't have an ID, start by listing all available types with `list_wine_varietals`. Then, your agent can decide if those types match what a user is looking for.

Checking API Health with LangChain MCP Server

Before running any complex chain, check the status first. Use `check_api_status` to make sure the entire VineRadar API is up and ready. This step acts as a guardrail for your agent. If it fails, you don't waste tokens calling other tools like `search_wines`; you just fail fast.

Setup guide

Set up VineRadar MCP in LangChain

Prerequisites

Python 3.10+ installed
langchain-mcp-adapters + langgraph packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install langchain-mcp-adapters langgraph langchain-openai. The MCP adapters package converts MCP tools into native LangChain BaseTool objects.
2

Connect via HTTP transport
Use MultiServerMCPClient with "transport": "http" pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create a ReAct agent
Pass the discovered tools to create_react_agent() from LangGraph. The agent automatically routes VineRadar tool calls through the MCP protocol.
4

Run with any LLM
Swap ChatOpenAI for ChatAnthropic, ChatGoogleGenerativeAI, or any LangChain-compatible model. The MCP tools work identically across all providers.

agent.py

from langchain_mcp_adapters.client import MultiServerMCPClient
from langgraph.prebuilt import create_react_agent
from langchain_openai import ChatOpenAI

async with MultiServerMCPClient({
    "vineradar-mcp": {
        "transport": "http",
        "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
    }
}) as client:
    tools = client.get_tools()

    agent = create_react_agent(
        ChatOpenAI(model="gpt-4o"),
        tools,
    )
    result = await agent.ainvoke({
        "messages": "List recent VineRadar transactions"
    })
    print(result["messages"][-1].content)

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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 VineRadar. 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 VineRadar MCP in LangChain

You can build a chain that first uses `search_vineyards` based on location. Then, the second step takes those results and passes them into `get_wine_details` to pull specific vintage data for auditing.

Absolutely. You can run a multi-step query: first, search generally with `search_wines`, then take the resulting wine IDs and pass them into `get_wine_details` for richer context.

The server exposes vineyard and wine details, but since you're building a chain, always ensure your subsequent tools only use anonymized IDs. This keeps the full record of the vineyard ID contained within the initial step.

Yes. The client supports connecting multiple servers, so you can aggregate data from VineRadar alongside other APIs in a single reasoning pipeline.

The agent determines the order dynamically. It looks at the intermediate output of one tool—say, a list of varietals—and decides that this list must become the input argument for the next tool call.

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