How to Use the CellarPass MCP in LangChain

Q: Can LangChain handle real-time availability checks via CellarPass?

Yes, your LangChain agent calls checkavailability dynamically during a conversation. It reads the current open slots and answers guest inquiries with live winery data.

Run multi-step winery booking and guest lookup chains directly inside your LangChain pipelines.

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Connect CellarPass MCP to LangChain

Create your Vinkius account to connect CellarPass 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 CellarPass with LangChain

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Chain winery booking workflows in LangChain

`check_availability` serves as the initial link in your LangChain booking chain. Your chain passes the real-time winery openings directly to the next step, matching guest preferences to prepare the reservation details without manual intervention. You feed the output of the availability check straight into subsequent reservation steps using this MCP Server. This sequential design eliminates manual API mapping because the output of one winery tool feeds directly into the next LangChain run.

Track guest history with LangSmith visibility

`search_guests` pulls up-to-date winery visit history and VIP status to customize the hospitality experience. Running this through this MCP Server lets you trace every single guest lookup inside LangSmith to monitor latency and token usage. You see exactly when and why your LangChain agent fetched winery guest profiles. This debugging transparency ensures your tasting room staff gets accurate guest data on the floor without lagging.

Route requests across multiple winery locations

`list_venues` identifies all active tasting locations to help your LangChain router agent direct inquiries. The router matches incoming winery bookings to the correct property based on geographic proximity or experience type. By combining this routing logic with `list_experiences`, your LangChain pipeline maps specific tastings to their respective properties dynamically. You build a multi-venue winery booking system that automatically filters options before presenting them to the client.

Setup guide

Set up CellarPass 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 CellarPass 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({
    "cellarpass-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 CellarPass 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 CellarPass. 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 CellarPass MCP in LangChain

Install langchain-mcp-adapters and langgraph via pip. Initialize the MultiServerMCPClient with your Vinkius endpoint URL, pull the tools with client.get_tools(), and pass them to your agent constructor.

Yes, your LangChain agent calls check_availability dynamically during a conversation. It reads the current open slots and answers guest inquiries with live winery data.

Vinkius runs this tool on sandboxed V8 isolates to process parallel calls instantly. Your LangChain chains won't stall even when querying multiple reservation lists during peak hours.

Yes, you can mix these winery tools with database or email integrations in the same LangGraph state machine. The agent decides when to pull guest history and when to trigger external notifications.

All guest profiles and booking records remain protected by Vinkius's zero-trust sandboxing. No reservation details are stored permanently on the execution layer, ensuring strict data isolation.

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