How to Use the Hudu MCP in CrewAI

Deploy a specialized crew of agents in CrewAI to manage your IT environment using Hudu for research, analysis, and execution.

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Connect Hudu MCP to CrewAI

Create your Vinkius account to connect Hudu 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 Hudu with CrewAI

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Agent Teams for Hudu Operations

Assign research tasks to one agent using `list_articles` while another agent performs actions with `create_asset`. CrewAI orchestrates these specialists so they share memory and work toward a common goal. This setup allows one agent to specialize in documentation retrieval while another handles the heavy lifting of updating your IT records. They collaborate, ensuring the work is accurate and fast.

Autonomous Infrastructure Monitoring

Set a monitor agent to watch your systems and use `list_assets` to detect discrepancies. When the agent finds an issue, it can call `get_procedure` to suggest a fix or document the status change. Your crew acts as a 24/7 technical team. By giving them access to Hudu, they can verify current states against your documented records and flag anything that looks out of place.

Hierarchical Execution in CrewAI

Structure your agents so a manager monitors the output of the workers using the Hudu MCP Server. If a worker fails to find a password via `get_password`, the manager can reassign the task or escalate it. This hierarchical approach ensures your documentation tasks are completed with oversight. You define the chain of command, and the agents use the provided tools to execute the work as instructed.

Setup guide

Set up Hudu 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 Hudu tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

task = Task(
    description="List recent Hudu 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 →

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="Hudu Analyst",
        goal="Access and analyze Hudu data via MCP.",
        backstory="Expert analyst with direct Hudu access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent Hudu 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 Hudu. 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 Hudu MCP in CrewAI

You define the tool list within the agent configuration. This allows you to give only the 'Researcher' agent access to `list_procedures` while keeping other tools restricted.

CrewAI uses shared memory for your crew. Any data retrieved by one agent via `get_company` is available to the rest of the team for their subsequent tasks.

Yes. You control the scope of the tools. By limiting your agents to read-only functions like `list_assets`, you prevent unauthorized changes to your vault.

It handles IT documentation, including sensitive password strings, asset metadata, company records, and knowledge base articles stored in your vault.

If a tool call fails, the agent receives the error message directly. It can then log the failure or try a different approach based on your instructions.

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