How to Use the Arbox MCP in AutoGen

Q: How do I register the Arbox MCP Server tools in AutoGen?

Install autogen-extmcp and use StreamableHttpServerParams to connect to your Vinkius endpoint. Pass the resulting tool list to your AssistantAgent constructor.

Q: Can AutoGen agents negotiate schedule conflicts in Arbox using MCP?

Yes. One agent can call getschedule to find conflicts, while another agent suggests alternative classes to the user until they reach a consensus.

Q: How do AutoGen agents handle member updates in Arbox?

An agent calls getclient to retrieve current details, debates whether the updates are valid, and then invokes updateclient to save the changes.

Run multi-agent debates to manage Arbox bookings and lead follow-ups in AutoGen.

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Connect Arbox MCP to AutoGen

Create your Vinkius account to connect Arbox 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 Arbox with AutoGen

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Coordinate bookings with an AutoGen MCP Server

`book_class` and `get_schedule` are managed by specialized booking agents that negotiate class availability. One agent checks the schedule for open spots while another verifies the member's eligibility. This setup eliminates booking errors. The agents discuss constraints like class caps and member tiers before finalizing any reservation in your gym's database.

Automate lead qualification through agent debate

`create_lead` and `get_lead` drive the conversation when new prospects contact your fitness studio. A sales agent gathers the lead's goals, and a manager agent reviews the profile before saving it. The agents deliberate on how to categorize the lead. Once they agree, they write the finalized lead details directly into your Arbox CRM.

Assign and verify gym tasks with this MCP Server

`create_task` and `list_tasks` keep your gym staff aligned without manual intervention. Your agents review daily operations and assign follow-up tasks based on lead activity. A supervisor agent checks the task list to make sure nothing slips through. If a high-priority lead is ignored, the agents automatically generate a new follow-up task.

Setup guide

Set up Arbox 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 Arbox 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="Arbox_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Arbox 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="Arbox_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

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

Get your connection token →

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Common questions about Arbox MCP in AutoGen

Install autogen-ext[mcp] and use StreamableHttpServerParams to connect to your Vinkius endpoint. Pass the resulting tool list to your AssistantAgent constructor.

Yes. One agent can call get_schedule to find conflicts, while another agent suggests alternative classes to the user until they reach a consensus.

An agent calls get_client to retrieve current details, debates whether the updates are valid, and then invokes update_client to save the changes.

This setup uses the Streamable HTTP transport provided by Vinkius. It handles schema conversion automatically via the McpToolAdapter in AutoGen.

Vinkius runs each query inside a throwaway V8 sandbox that isolates your API keys and client files. Your gym's membership records and class schedules are never stored or exposed to external networks during agent conversations.

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