How to Use the Eventtia MCP in LangChain

Q: How do I use Eventtia with LangChain to check event performance?

You build a chain. First, call listallevents to get event IDs. Then, pass those IDs to geteventperformancestats to get metrics for each one. LangChain lets you string these tool calls together to create a full report.

Q: Can my LangChain agent see my Eventtia account limits?

Yes. The geteventtiaaccountmetadata tool is designed for that. Your agent can call it to check API rate limits or other account settings before running a large batch of operations.

Q: What's the best way to list all attendees for a live event using Eventtia and LangChain?

Create an agent that first calls listcurrentlyliveevents. It should then take the ID from the result and pass it directly to the listeventattendees tool. This two-step chain ensures you're only pulling data for active events.

Build agents that manage your events with LangChain. Chain Eventtia tool calls to automate complex event operations.

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Connect Eventtia MCP to LangChain

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Setup Eventtia with LangChain

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Run Multi-Step Event Audits

Start by getting a list of all your events with `list_all_events`. Then, for each one, have your agent decide whether to pull detailed stats using `get_event_performance_stats` or just check who's attending with `list_event_attendees`. It's a simple chain that gives you a complete picture. Your agent can build complex logic. For example, it could run `quick_event_engagement_audit` and, if engagement is low, automatically fetch the `list_event_sessions` to identify which ones are underperforming. The output of one tool becomes the input for the next decision your agent makes.

Chain B2B Meeting Workflows

Build a pipeline that starts with `list_event_business_meetings` to get a raw list of scheduled B2B meetings. From there, your LangChain agent can cross-reference attendee details using `list_event_attendees` and speaker info with `list_event_speakers` to enrich the meeting data. This isn't just about pulling data. It's about creating a sequence. For instance, after fetching meetings, your agent could check `get_event_detailed_data` to see if the event's networking features are even enabled. This lets you build agents that adapt their behavior based on the event's live configuration.

Live Event Monitoring with LangChain

Create an agent that constantly checks for active events using `list_currently_live_events`. When a live event is found, it can trigger another chain to pull session schedules (`list_event_sessions`) and speaker lists (`list_event_speakers`) in real-time. You can design agents that react to what's happening now. If a new B2B meeting appears via `list_event_business_meetings` during a live event, the agent can automatically take action. This MCP Server gives your chains the live data they need to act.

Setup guide

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

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Common questions about Eventtia MCP in LangChain

You build a chain. First, call `list_all_events` to get event IDs. Then, pass those IDs to `get_event_performance_stats` to get metrics for each one. LangChain lets you string these tool calls together to create a full report.

Yes. The `get_eventtia_account_metadata` tool is designed for that. Your agent can call it to check API rate limits or other account settings before running a large batch of operations.

Create an agent that first calls `list_currently_live_events`. It should then take the ID from the result and pass it directly to the `list_event_attendees` tool. This two-step chain ensures you're only pulling data for active events.

The tools are granular. Instead of one giant 'get everything' tool, you have specific ones like `list_event_sessions` and `list_event_speakers`. This lets your agent decide what specific piece of information it needs next, building a more intelligent workflow.

It only touches your Eventtia data: event details, attendee lists, B2B meetings, and session schedules. Vinkius isolates each request in a sandbox, and your auth token is the only thing connecting it to your account. The server itself stores nothing.

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