How to Use the Domo MCP in CrewAI

Deploy autonomous CrewAI specialist teams to govern your Domo users and access groups.

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Connect Domo MCP to CrewAI

Create your Vinkius account to connect Domo to CrewAI 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 Domo with CrewAI

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Autonomous Domo auditing with CrewAI

The `update_user` and `remove_user_from_group` tools allow CrewAI specialist agents to autonomously audit and clean up inactive Domo accounts. You can set up a CrewAI team where an Audit Agent scans user lists, while an Admin Agent uses this MCP Server to run the cleanup. This setup prevents Domo access creep. The CrewAI Audit Agent identifies accounts that no longer match corporate directory templates, and passes those profiles to the Admin Agent, which executes `delete_user` to secure the Domo instance.

Collaborative Domo group provisioning

The `create_group` and `add_user_to_group` tools let CrewAI agent teams collaborate on setting up new Domo departments. A Setup Agent can determine the necessary team structure, run `create_group`, and then hand the new Domo group ID to an Onboarding Agent to run `add_user_to_group` for the designated team members. The CrewAI agents share memory, ensuring they do not attempt to recreate existing Domo structures. If a Domo group already exists, they pivot to updating memberships using `add_user_to_group` instead of failing.

Intelligent Domo role escalation management

The `update_user` tool allows CrewAI security agents to raise permissions dynamically before scheduling a cleanup action. A CrewAI Security Agent can monitor incoming requests, while an Action Agent uses this MCP Server to run `update_user` to raise permissions, and schedules a subsequent `remove_user_from_group` call to revoke it later. The entire Domo lifecycle is managed by autonomous CrewAI agents following your defined security policies. The agents use the toolset to verify that the target Domo user exists before trying to modify their roles, avoiding empty API calls.

Setup guide

Set up Domo MCP in CrewAI

Prerequisites

Python 3.10+ installed
crewai package (pip install crewai)
Active Vinkius subscription with a valid endpoint token

1

Install CrewAI
Run pip install crewai to install the framework. MCP support is built-in via the mcps parameter.
2

Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the mcps list. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. CrewAI handles tool discovery and caching automatically.
3

Kick off your crew
Create a Crew with your agent and tasks. Call crew.kickoff() — the agent will automatically invoke Domo tools as needed.

crew.py

from crewai import Agent, Task, Crew

agent = Agent(
    role="Domo Analyst",
    goal="Access and analyze Domo data via MCP.",
    backstory="Expert analyst with direct Domo access.",
    mcps=[
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ],
)

task = Task(
    description="List recent Domo transactions",
    agent=agent,
    expected_output="A summary of recent activity",
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

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Prerequisites

Python 3.10+ installed
crewai + crewai-tools packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install crewai crewai-tools. The MCPServerAdapter handles lifecycle management and tool conversion.
2

Connect with MCPServerAdapter
Use MCPServerAdapter as a context manager with SseServerParameters pointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle.
3

Assign tools and run
Pass the returned mcp_tools to your agent's tools parameter. The adapter converts MCP tools to native BaseTool objects compatible with all CrewAI agents.

crew.py

from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
from mcp import SseServerParameters

server_params = SseServerParameters(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

with MCPServerAdapter(server_params) as mcp_tools:
    agent = Agent(
        role="Domo Analyst",
        goal="Access and analyze Domo data via MCP.",
        backstory="Expert analyst with direct Domo access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent Domo transactions",
        agent=agent,
        expected_output="A summary of recent activity",
    )

    crew = Crew(agents=[agent], tasks=[task])
    result = crew.kickoff()
    print(result)

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.

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Common questions about Domo MCP in CrewAI

You can configure your CrewAI agent by passing the Vinkius HTTP endpoint directly into the `mcps` array parameter. This immediately exposes tools like `create_user` and `create_group` to that specific agent's toolkit.

Yes, CrewAI's hierarchical execution allows a supervisor agent to assign tasks. One agent can verify the user profile, while another agent runs `add_user_to_group` to place them in the correct Domo access tier.

You can use CrewAI's tool filtering or configure a moderator agent to intercept destructive actions. By restricting the `delete_user` tool to a highly specialized, supervised agent, you ensure standard agents can only run safe operations like `update_user`.

Yes, CrewAI supports stdio, SSE, and HTTP transports. When running in a local terminal environment, the framework uses stdio to communicate with the MCP Server, letting your agents query and modify Domo groups directly from the command line.

Your actual Domo API credentials, user names, and group affiliations are encrypted and managed on the Vinkius platform. The CrewAI framework only interacts with the secure, sandboxed MCP Server endpoint, preventing your Python environment from exposing raw master keys.

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