How to Use the Hullo MCP in LangChain

Q: Can LangChain agents chain Hullo member creation and messaging?

Yes. Your agent can run createmember and immediately pass that output into sendmessage to fire off a welcome text.

Chain coworking administrative tasks and member communications directly in LangChain.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Hullo MCP to LangChain

Create your Vinkius account to connect Hullo 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 Hullo with LangChain

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Automate Coworking Rosters

`create_member` and `list_members` give your agent direct read and write access to your workspace directory. Pass the JSON string into the tool, and the system registers the new tenant instantly. This means you can build a ReAct pipeline that calls this MCP tool to check the current roster before adding a duplicate. LangSmith traces the exact inputs and outputs of `get_member` so you know precisely when the agent checked a user's status.

LangChain MCP Server Integration

`send_message` pushes notifications straight to your coworking members. Your agent decides the content and fires the JSON payload to the right person without human oversight. Combine this with `get_conversation` to build an automated support desk. The chain reads a member's complaint, parses the context, and drafts a reply based on previous workspace interactions.

Traceable Community Engagement

`list_conversations` pulls the entire chat history for your space. You feed this data into subsequent chain links to categorize member sentiment or flag unresolved desk booking issues. Every API call routes through the open standard. If a chain fails mid-execution, you review the exact token usage and latency metrics to debug the bottleneck.

Setup guide

Set up Hullo 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 Hullo 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({
    "hullo-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 Hullo 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 Hullo. 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 Hullo 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 Hullo MCP in LangChain

Install the langchain-mcp-adapters package. Use MultiServerMCPClient with your HTTP endpoint and call client.get_tools() to initialize the connection.

Yes. Your agent can run create_member and immediately pass that output into send_message to fire off a welcome text.

It logs every tool invocation. You see exactly what JSON payload your agent sent to get_member and how long the server took to respond.

The client is stateless by default. You need to use client.session() if you want the agent to remember previous list_conversations results.

Vinkius runs this connection in an ephemeral V8 Isolate Sandbox. Roster details and chat transcripts never touch our disks. You authenticate with a single endpoint token, and the sandbox dies the second the session ends.

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