How to Use the Hullo MCP in AutoGen

Q: How do I initialize Hullo in AutoGen?

Install the autogen-extmcp package. Fetch the tools using mcpservertools and pass them directly into your AssistantAgent constructor.

Q: Can AutoGen agents collaborate on Hullo member management?

They excel at it. One agent can pull data with getmember while another reviews the output before approving a profile update.

Deploy debating agents to manage your coworking space with AutoGen and Hullo.

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Connect Hullo MCP to AutoGen

Create your Vinkius account to connect Hullo to AutoGen 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 AutoGen

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Negotiate Community Disputes

`get_conversation` feeds raw chat logs to your AutoGen agents. A moderation agent reads the transcript while a community agent argues for leniency. They debate the context before taking action. Once they reach a consensus, one agent triggers `send_message` to issue a warning or resolve the conflict.

AutoGen MCP Server Integration

`list_members` provides the baseline data for your administrative agents. They cross-reference the active tenants against billing records to find discrepancies. If an agent finds a missing profile, it proposes a fix. Another agent verifies the formatting, and then executes `create_member` with the correct JSON string to update the directory.

Resolve Coworking Tickets

`list_conversations` pulls the daily queue of member requests. Your agents divide the workload, discussing which complaints require immediate attention and which can wait. This MCP setup shifts the triage burden off your human staff. The adapter converts the schemas automatically, letting your agents focus on solving the problem instead of formatting API calls.

Setup guide

Set up Hullo MCP in AutoGen

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] package
Active Vinkius subscription with a valid endpoint token

1

Install AutoGen with MCP
Run pip install "autogen-ext[mcp]" autogen-agentchat. The MCP extension includes mcp_server_tools for stateless tool access.
2

Fetch tools from the MCP
Call mcp_server_tools(SseServerParams(url=...)) with your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Run your agent
Pass the tools to AssistantAgent and call agent.run(). The agent invokes Hullo tools and returns structured results.

agent.py

from autogen_ext.tools.mcp import SseServerParams, mcp_server_tools
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

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

tools = await mcp_server_tools(server_params)

agent = AssistantAgent(
    name="Hullo_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Hullo data")
print(result.messages[-1].content)

Get your connection token →

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] + autogen-agentchat
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Same packages as above. McpWorkbench is ideal when your agent needs stateful sessions across multiple tool calls.
2

Use McpWorkbench as context manager
Wrap your agent in async with McpWorkbench(...) to maintain shared state and resources. The workbench manages the full MCP session lifecycle.
3

Run with workbench
Pass workbench=workbench to your agent. State is preserved across multiple tool calls within the same session.

agent.py

from autogen_ext.tools.mcp import McpWorkbench, SseServerParams
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

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

async with McpWorkbench(server_params) as workbench:
    agent = AssistantAgent(
        name="Hullo_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Hullo data")
    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

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Common questions about Hullo MCP in AutoGen

Install the autogen-ext[mcp] package. Fetch the tools using mcp_server_tools and pass them directly into your AssistantAgent constructor.

They excel at it. One agent can pull data with get_member while another reviews the output before approving a profile update.

No. The framework handles the conversion. You just provide the HTTP transport URL and the agents understand the required JSON strings.

You build a reviewer agent into the loop. It evaluates the proposed send_message payload and rejects it if the tone is off.

Vinkius handles the authentication and runs the connection in an ephemeral sandbox. Your community chat transcripts remain private because the container drops all state immediately after execution.

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