How to Use the Betterfly MCP in AutoGen

Q: How do I configure the Betterfly MCP for AutoGen?

Install autogen-extmcp. Use mcpservertools with your Vinkius URL to fetch the tools, then pass them to your AssistantAgent.

Q: What happens if an agent tries to pause a user incorrectly?

You can put a human in the loop. The agents debate the pauseuser action and ask for your final approval in the terminal.

Give your AutoGen multi-agent teams the ability to debate and manage Betterfly wellness programs.

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Connect Betterfly MCP to AutoGen

Create your Vinkius account to connect Betterfly 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 Betterfly with AutoGen

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Perplexity

Let agents debate Betterfly challenge creation.

You don't just want an agent blindly launching company-wide events. You set up a team in AutoGen where a wellness agent proposes a new fitness drive. It checks `get_company_metrics` to see current engagement levels. A budget agent reviews the proposal. It looks at past payouts using `get_user_rewards` and argues that the new challenge is too expensive. They negotiate the parameters before finally agreeing to call `create_challenge` via the MCP Server.

Automate HR interventions through consensus.

Managing underperforming or inactive accounts requires nuance. An analytics agent monitors `list_activities` to spot users who haven't logged steps in months. It flags these accounts to an HR compliance agent. The compliance agent pulls `get_user` to review the profile details. If both agents agree the account is dormant and costing money, they execute `pause_user` to temporarily restrict access. The decision is logged as a conversation.

Analyze ESG impact with competing perspectives.

Corporate sustainability reporting often lacks critical review. You can assign one agent to gather raw data using the MCP tools, specifically `get_impact_stats` and `list_donations`. That agent presents the total social contributions to the group. A skeptic agent reviews those numbers against `list_partners` to verify the ecosystem links. They debate whether the company is meeting its ESG goals before generating a final consensus report for management.

Setup guide

Set up Betterfly 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 Betterfly 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="Betterfly_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

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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="Betterfly_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Betterfly 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 Betterfly. 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 Betterfly MCP in AutoGen

Install `autogen-ext[mcp]`. Use `mcp_server_tools` with your Vinkius URL to fetch the tools, then pass them to your `AssistantAgent`.

They can, but you usually design them to debate first. One agent verifies the goal via `list_activities` while another approves the `assign_reward` call.

Single agents just execute. AutoGen lets a finance agent and a wellness agent argue over the data from `get_company_metrics` before making a decision.

You can put a human in the loop. The agents debate the `pause_user` action and ask for your final approval in the terminal.

Vinkius routes all tool calls through an ephemeral V8 Isolate Sandbox. When your agents discuss step counts from `list_activities` via the Betterfly MCP Server, that sensitive health data passes through a zero-trust environment.

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