How to Use the Luma MCP in LangChain

Q: Can my LangChain agent automatically add guests to a Luma event?

Yes, once you pass addgueststoevent to the agent, it can trigger invites based on any criteria you define in your code. It handles the API handshake internally.

Chain together Luma events and guest lists directly inside your LangChain agents to automate your event operations.

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Connect Luma MCP to LangChain

Create your Vinkius account to connect Luma 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 Luma with LangChain

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Claude

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Automate event creation and guest management

Your LangChain agent uses `create_event` to spin up new gatherings without you touching the web dashboard. It populates details, sets the scope, and prepares the backend for incoming traffic. Once the event is live, the agent calls `add_guests_to_event` to handle your invite list dynamically. You just define the logic in your chain, and the agent executes the additions.

Sync subscriber data into your reasoning pipelines

Feed your agent real-time insights by calling `list_calendar_subscribers`. The data flows directly into your chain, allowing the agent to adjust outreach strategies based on current subscriber counts. This creates a feedback loop where your agent understands audience growth. It uses the output of these list tools to make informed decisions about future event scheduling.

Monitor organization-wide activity

The MCP Server allows your agent to query `list_organization_events` to keep track of every event across your entire account. This provides a high-level view for agents tasked with reporting or scheduling oversight. When you need specific details, the agent pivots to `list_events` for a filtered look at your personal calendar. It connects these data points to build a clear picture of your event footprint.

Setup guide

Set up Luma 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 Luma 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({
    "luma-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 Luma transactions"
    })
    print(result["messages"][-1].content)

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Common questions about Luma MCP in LangChain

You install the MCP adapters package and point your client to the server endpoint. From there, you pull the tools and inject them directly into your agent constructor.

Yes, once you pass `add_guests_to_event` to the agent, it can trigger invites based on any criteria you define in your code. It handles the API handshake internally.

Absolutely. Because these tools are exposed via the MCP standard, your agent can chain them together. For example, it can list events, check attendees, and then add new guests in one pass.

You can use the list tools to pull event data and pass that into your LangSmith traces. This lets you observe exactly what data your agent is seeing during each run.

Your API token stays local to the environment where the MCP server runs. Only the specific event metadata and guest lists requested by your agent are ever transmitted.

Use it with your favorite AI tools

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