How to Use the Glofox MCP in AutoGen
Let AutoGen agents debate schedule conflicts and membership rules using live Glofox data.
Works with every AI agent you already use
…and any MCP-compatible client
Connect Glofox MCP to AutoGen
Create your Vinkius account to connect Glofox 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.
Resolve trainer scheduling conflicts through debate
Use `list_trainers` to pull active coach schedules and let your AutoGen agents negotiate class assignments. One agent representing the trainers can cross-reference availability with class times retrieved via `list_classes` to find the optimal schedule. A separate coordinator agent can challenge these assignments based on historical attendance patterns. They deliberate until they find a schedule that maximizes class capacity without burning out your staff.
Audit membership plans using this Glofox MCP Server
Run `list_memberships` to extract current pricing tiers and access hours for an automated operational audit. Your AutoGen security agent can review these perks while a financial agent checks them against actual transaction records. By analyzing the output of `list_purchases`, the agents debate whether low-tier memberships are accessing premium classes. This consensus-driven audit ensures your gym's pricing structure is enforced accurately across all accounts.
Manage course enrollment and waitlists automatically
Use `list_courses` to track multi-week program enrollment and identify sessions that are overbooked. Your MCP agents discuss whether to open a new session or move waitlisted members to alternative times. They pull live waitlist data using `list_bookings` to make these decisions. This cooperative workflow resolves booking bottlenecks before your front desk opens in the morning.
Set up Glofox 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 includesmcp_server_toolsfor 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
AssistantAgentand callagent.run(). The agent invokes Glofox tools and returns structured results.
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="Glofox_assistant",
model_client=OpenAIChatCompletionClient(model="gpt-4o"),
tools=tools,
)
result = await agent.run("List recent Glofox data")
print(result.messages[-1].content) 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.
McpWorkbenchis 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=workbenchto your agent. State is preserved across multiple tool calls within the same session.
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="Glofox_assistant",
model_client=OpenAIChatCompletionClient(model="gpt-4o"),
workbench=workbench,
)
result = await agent.run("List recent Glofox data")
print(result.messages[-1].content) Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Glofox. 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 Glofox MCP in AutoGen
Use it with your favorite AI tools
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