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How to Use the SevenRooms MCP in LangChain

Build complex scheduling chains and reasoning agents using LangChain.

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Works with every AI agent you already use

…and any MCP-compatible client

SevenRooms MCP on Cursor AI Code Editor MCP Client SevenRooms MCP on Claude Desktop App MCP Integration SevenRooms MCP on OpenAI Agents SDK MCP Compatible SevenRooms MCP on Visual Studio Code MCP Extension Client SevenRooms MCP on GitHub Copilot AI Agent MCP Integration SevenRooms MCP on Google Gemini AI MCP Integration SevenRooms MCP on Lovable AI Development MCP Client SevenRooms MCP on Mistral AI Agents MCP Compatible SevenRooms MCP on Amazon AWS Bedrock MCP Support
MCP Servers — Included with Plan
Vinkius runs on LangChain

Connect SevenRooms MCP to LangChain

Create your Vinkius account to connect SevenRooms to LangChain — we handle the hosting, security, and runtime updates so you don't have to. No server setup required.

GDPR Included with Plan

Key Capabilities

Determine seating capacity across multiple venues.

Need to know if a group can fit into the whole chain? You start by calling `list_venues` to map out all locations. Then, you feed those IDs into `check_availability` for each one to see open tables and current wait times. This sequence lets your agent build an itinerary: it checks capacity across multiple spots before recommending a final choice.

Assemble guest profiles from booking history.

An agent needs context on a customer. First, use `search_guests` to find the profile ID for someone like Mr. Silva. Next, call `get_reservation` using that ID to pull up their recent dining history and preferences. The resulting data lets your chain decide if they need to check `list_events` first, or if the guest is just showing up for a standard dinner.

Manage real-time host communication flows.

When things get chaotic, your agent takes over. Start by calling `list_waitlist` to see who's waiting right now. Then, if you need details on a specific booking, run `get_reservation`. Finally, use `check_availability` to confirm exactly when that table will clear up. This chain handles the entire operational flow: waitlist check -> reservation detail -> resource update.

Setup guide

Set up SevenRooms MCP in LangChain

Prerequisites

  • Python 3.10+ installed
  • langchain-mcp-adapters + langgraph packages
  • Active Vinkius subscription with a valid endpoint token
  1. 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. 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. 3

    Create a ReAct agent

    Pass the discovered tools to create_react_agent() from LangGraph. The agent automatically routes SevenRooms tool calls through the MCP protocol.

  4. 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({
    "sevenrooms-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 SevenRooms transactions"
    })
    print(result["messages"][-1].content)

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by SevenRooms. 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.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about SevenRooms MCP in LangChain

You use the `search_guests` tool. This function pulls core CRM data on a specific person, giving your agent everything from contact info to past visit summaries.
Absolutely. The `check_availability` tool provides immediate details on open tables, wait times, and which dining rooms are free right now.
Yes. Use the `list_reservations` tool when you need to know who is dining tonight. It gives an immediate rundown of all confirmed bookings for that shift.
The `list_events` tool provides details on upcoming venue happenings, including the date, capacity limits, pricing structure, and current availability status for those specific events.
The server touches guest profile data (`get_guest`), which includes personal identification details used for CRM records. This determines who the user is managing reservations for.

Start using the SevenRooms MCP today

We host it, we monitor it, we maintain it. You just paste one token.

Built & Managed by Vinkius 30s setup 8 tools

We've already built the connector for SevenRooms. Just plug in your AI agents and start using Vinkius.

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