How to Use the Humanitix MCP in LangChain

Q: How does the Humanitix MCP tool schema translate to LangChain tools?

The server automatically translates endpoints like listcampaigns and listinventory into structured LangChain tool objects. Your agents can immediately inspect their JSON schemas and call them.

Q: Can I trace Humanitix API calls made by LangChain in LangSmith?

Absolutely. Every time your agent calls getme or listhosts, LangSmith captures the exact parameters and JSON payloads. This lets you debug failing API calls in seconds.

Get real-time ticket sales and attendee data directly inside your LangChain reasoning loops.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Humanitix MCP to LangChain

Create your Vinkius account to connect Humanitix 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.

GDPR Free for Subscribers

Setup Humanitix with LangChain

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Chain Live Event Data into Reasoning Loops

We feed your LangChain agents raw event data using `list_events` and `list_venues` to make decisions on the fly. Your agent pulls the event location and details, then pipes that output directly to the next step of the chain. This means you don't write glue code to pass venue details to your scheduling chains. You track the entire execution path inside LangSmith to see exactly how your agent resolved a venue conflict. Every time `list_hosts` runs to find the organizer's contact info, you see the latency and token usage in your trace. No black boxes, just clear execution steps.

Trace Ticket Audits with the LangChain MCP Server

This MCP Server exposes `list_orders` and `list_tickets` so your LangChain chains can audit registration counts in real time. The agent inspects the order payload, pulls the ticket IDs, and decides whether to trigger a notification chain. It does this by evaluating the intermediate outputs dynamically. Because LangChain handles multi-server aggregation, you can combine this ticket data with your CRM database in a single run. If `list_inventory` shows a ticket category is sold out, the chain immediately branches to find alternative options.

Automate Attendee Check-Ins

Your agent uses `list_attendees` to verify guests and build custom check-in loops. It pulls the list, parses the names, and feeds them into your local notification adapters. This turns a manual list export into an automated, multi-step pipeline. You build these pipelines with LangGraph to handle complex state transitions during high-traffic check-in windows. If a guest isn't found, the agent calls `get_event` to verify they bought tickets for the correct date.

Setup guide

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

Get your connection token →

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

Connect Humanitix now

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 Humanitix MCP in LangChain

Install the adapter package first. Then instantiate the MultiServerMCPClient with the server URL and pass the tools directly to your agent initialization function.

Yes, you should configure your LangChain runnables with retry logic to handle rate limits. The server returns standard HTTP codes when querying Humanitix orders, allowing your chains to back off gracefully.

The server automatically translates endpoints like `list_campaigns` and `list_inventory` into structured LangChain tool objects. Your agents can immediately inspect their JSON schemas and call them.

Absolutely. Every time your agent calls `get_me` or `list_hosts`, LangSmith captures the exact parameters and JSON payloads. This lets you debug failing API calls in seconds.

The server processes attendee names, emails, and ticket purchases entirely in memory. Your private ticket records are never stored or logged by Vinkius, maintaining direct secure access to your event database.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript