How to Use the Domo MCP in LangChain

Chain your Domo governance tasks directly into LangChain pipelines for automated user and group lifecycle management.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Domo MCP to LangChain

Create your Vinkius account to connect Domo 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 Domo with LangChain

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Sequence Domo user management in LangChain

Pipe the output of your agent directly into `create_user` to provision new accounts based on incoming ticket data. You link these operations to downstream logic to ensure every new entry gets assigned to the correct workspace. This MCP Server lets your agent handle the full lifecycle. Once a user is ready, use `add_user_to_group` to set permissions without leaving your execution chain.

Automate Domo group structures

Define group membership logic that triggers whenever your agent detects organizational changes. You initialize a container using `create_group` and immediately populate it based on project requirements. Everything stays tracked within your LangSmith traces. You see exactly when `remove_user_from_group` executes, giving you a clear audit trail of every modification.

Direct Domo lifecycle control

Handle offboarding by invoking `delete_user` through your agent as soon as a contract expires. This removes manual wait times from your security workflow. Update existing profiles with `update_user` to reflect role changes in real time. Your pipeline maintains the state of your environment without human intervention.

Setup guide

Set up Domo 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 Domo 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({
    "domo-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 Domo 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 Domo. 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 Domo 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 Domo MCP in LangChain

You connect the MCP Server to your agent and define a tool-calling loop. The agent evaluates current state against your requirements and executes `create_user` or `update_user` as needed.

LangChain doesn't manage rate limits natively, so you must add a delay or queue in your code. The Domo tools execute immediately upon call, so build your chains with this constraint in mind.

Yes, all data remains within your local process and encrypted transport. The MCP Server touches only user identities and group metadata, never your raw business intelligence data.

Your agent receives an error response directly from the tool. You should implement a try-catch block in your chain to handle these failures and trigger a retry or alert.

You can register multiple server instances to your client. Each instance handles its own specific credentials and endpoint, allowing you to manage disparate Domo environments simultaneously.

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