How to Use the MoeGo MCP in AutoGen

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

Use pip install -U autogen-extmcp to get the necessary MCP extensions. Then, pass the server URL to mcpservertools and assign the resulting tools to your AssistantAgent.

Q: Can AutoGen agents debate booking decisions before updating MoeGo?

Yes, agents can discuss options using listappointments and liststaff data. They only trigger createappointment once they reach a consensus on the optimal slot.

Q: How do AutoGen agents handle customer lookup in MoeGo?

An agent can query listcustomers to find the correct profile, while another agent verifies the associated pets using listpets. This prevents duplicate accounts and ensures accurate record linking.

Q: How is my MoeGo business configuration protected in AutoGen?

Your business settings fetched via getbusinesssettings are kept strictly within your local agent session. The Vinkius sandbox ensures that configuration data and appointment details remain isolated and secure.

Build multi-agent AutoGen debates to resolve scheduling conflicts and assign groomers using MoeGo.

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Create your Vinkius account to connect MoeGo 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 MoeGo with AutoGen

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Resolve Scheduling Conflicts via Agent Debates

Booking isn't always straightforward. With AutoGen, a scheduling agent can propose a slot using `create_appointment`, while an operations agent checks staff availability using `list_staff` to debate the choice. They negotiate the best time based on active business constraints. This multi-agent deliberation ensures you don't double-book groomers or schedule complex services during short shifts.

Automated Review Analysis and Staff Assignment

Let your agents collaborate on quality control. One agent pulls customer feedback using `list_reviews`, while another matches those reviews to specific groomers retrieved via `list_customers`. They discuss performance metrics and automatically draft schedule updates. By combining different perspectives, the system makes smarter decisions about which staff members should handle high-profile clients.

Coordinate Complex Pet Care Plans with AutoGen

This MCP Server enables deep collaboration on complex pet profiles. One agent retrieves pet medical and behavioral notes using `get_pet`, while another checks service requirements via `list_services`. Together, they determine the safest grooming plan. They can even flag high-risk pets to senior staff before the booking is finalized via `create_appointment`.

Setup guide

Set up MoeGo 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 MoeGo 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="MoeGo_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

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

Use pip install -U autogen-ext[mcp] to get the necessary MCP extensions. Then, pass the server URL to mcp_server_tools and assign the resulting tools to your AssistantAgent.

Yes, agents can discuss options using list_appointments and list_staff data. They only trigger create_appointment once they reach a consensus on the optimal slot.

An agent can query list_customers to find the correct profile, while another agent verifies the associated pets using list_pets. This prevents duplicate accounts and ensures accurate record linking.

Yes, the adapter supports both stdio and Streamable HTTP transports. You can choose the connection method that best fits your local or cloud deployment architecture.

Your business settings fetched via get_business_settings are kept strictly within your local agent session. The Vinkius sandbox ensures that configuration data and appointment details remain isolated and secure.

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