How to Use the WellnessLiving MCP in AutoGen

Q: Can AutoGen help with class scheduling for WellnessLiving?

Absolutely. Agents can cross-reference listservices against listschedule, debating potential time conflicts and suggesting optimal openings for new classes.

Run multi-agent debates on WellnessLiving operations using AutoGen.

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Connect WellnessLiving MCP to AutoGen

Create your Vinkius account to connect WellnessLiving 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 WellnessLiving with AutoGen

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Perplexity

Debating studio operational details with the MCP Server

Need to decide if a new service should run? You set up agents: one checks `list_services` for existing types, another calls `get_business_info` for revenue goals. They debate whether adding 'Yoga Flow' makes sense. The consensus-driven approach forces the system to weigh conflicting data points.

Cross-checking staff and scheduling with AutoGen

Want to schedule a complex event? One agent pulls `list_staff`, another checks `list_schedule` for conflicts. They negotiate: 'Staff Member X is booked at that time!' until they converge on an open slot. The system doesn't just report; it deliberates and finds the optimal solution.

Analyzing client data using AutoGen

You give the agents goals: improve retention. One agent calls `get_report` for attendance metrics, while another pulls client profiles via `search_clients`. They argue over whether membership changes or marketing outreach is the better fix. The resulting decision is a negotiated outcome based on conflicting data analysis.

Setup guide

Set up WellnessLiving 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 WellnessLiving 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="WellnessLiving_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

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

AutoGen uses the MCP Server to give agents tools. Agents debate which tool, like `list_locations` or `get_client`, is necessary at any given step until they reach a consensus.

You can have agents analyze reports (like revenue metrics), staff availability, and client history. They argue over the best course of action based on that structured data.

Absolutely. Agents can cross-reference `list_services` against `list_schedule`, debating potential time conflicts and suggesting optimal openings for new classes.

Yes. You'll set up agents to tackle complex problems, like coordinating staff needs (`list_staff`) with specific location requirements (`get_business_info`).

The server touches client profile information, specifically names and visit history when agents are tasked with analyzing client retention.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

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