How to Use the Hullo MCP in CrewAI

Q: How do I pass Hullo tools to a CrewAI agent?

You can pass the MCP Server URL directly into the agent's mcps parameter. This gives the agent access to tools like createmember and listmembers.

Q: How do I limit which Hullo tools a CrewAI agent can access over MCP?

Use the MCPServerHTTP class from crewai.mcp and apply a toolfilter. This lets you restrict an agent to only use sendmessage while blocking database modification tools.

Q: Can a CrewAI agent update a member's profile details?

The agent can retrieve details using getmember and generate updates, but actual database creation must go through createmember.

Deploy a crew of autonomous agents to manage member relations and community chat using CrewAI and Hullo.

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Connect Hullo MCP to CrewAI

Create your Vinkius account to connect Hullo 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 Hullo with CrewAI

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Run autonomous community managers with CrewAI

The `list_conversations` tool allows your CrewAI agents to monitor active workspace channels. A moderator agent can watch your channels while a support agent stands by to answer questions. When a member asks for help, the support agent uses `get_conversation` to read the context and drafts a response. The moderator agent then reviews the draft and calls `send_message` to reply instantly.

Coordinate member data audits across agent teams

The `list_members` tool lets you deploy a CrewAI audit team to clean up your coworking directory. One agent can pull the full directory while another checks individual profiles via `get_member` for missing contact details. If an agent finds incomplete profiles, it can coordinate with a messaging agent to alert the member. This multi-agent setup keeps your records clean without bothering your front desk staff.

Set up an autonomous onboarding desk using this MCP Server

The `create_member` tool acts as the entry point for your autonomous front-desk crew. When a prospect submits their details, your registration agent calls the tool to generate their profile in your system. Once the profile is active, a welcoming agent takes over to send them their digital key and space guidelines. This sequential workflow ensures every new member gets a consistent onboarding experience.

Setup guide

Set up Hullo 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 Hullo tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

task = Task(
    description="List recent Hullo 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="Hullo Analyst",
        goal="Access and analyze Hullo data via MCP.",
        backstory="Expert analyst with direct Hullo access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent Hullo 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 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.

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Common questions about Hullo MCP in CrewAI

You can pass the MCP Server URL directly into the agent's `mcps` parameter. This gives the agent access to tools like `create_member` and `list_members`.

Yes, CrewAI's shared memory allows different agents to collaborate using the same tools. One agent can call `list_conversations` while another uses `get_conversation` on a specific thread.

Use the `MCPServerHTTP` class from `crewai.mcp` and apply a `tool_filter`. This lets you restrict an agent to only use `send_message` while blocking database modification tools.

The agent can retrieve details using `get_member` and generate updates, but actual database creation must go through `create_member`.

All tool execution happens over secure HTTP or stdio transports managed by our MCP gateway. Your member profiles and chat history are never stored in CrewAI's shared memory after the session ends.

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