How to Use the TurfHop MCP in AutoGen

Q: How do I check for existing accounts using TurfHop and AutoGen?

You instruct the agents to run getcustomer or listcustomers. The resulting data is then debated among the agents to determine if further action (like an update) is necessary.

Resolve complex business decisions through multi-agent debate with AutoGen.

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Connect TurfHop MCP to AutoGen

Create your Vinkius account to connect TurfHop 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 TurfHop with AutoGen

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Perplexity

Automated conflict resolution for jobs

Imagine a scheduling agent debating with a billing agent. One calls `get_job` to check availability, while the other uses `list_products` to verify costs. The agents negotiate until they converge on a definitive action, like calling `create_job` only after both perspectives agree on timing and pricing.

Structured customer onboarding debate

When a new client comes in, multiple roles can weigh in. A 'Verification Agent' calls `get_customer` to check IDs, while the 'Sales Agent' uses `create_customer`. The consensus mechanism ensures all required steps are taken before the final record is established.

Coordinated billing and service updates

The agents can simulate a conversation where one agent proposes an update using `update_job`, and another agent immediately runs `get_invoice` to check if that change impacts current billing. This deliberation process ensures the job and financial records stay synchronized before any final call is made.

Setup guide

Set up TurfHop 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 TurfHop 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="TurfHop_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

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

The agents debate the best time to schedule a service. They might run `list_jobs` first, discuss conflicts, and finally agree on parameters needed to call `create_job`.

Yes. You can set up a 'Finance Agent' that debates over which invoice listing (`list_invoices`) is correct, ensuring billing accuracy through consensus before proceeding.

The system interacts with customer records (customer details), scheduled work reports (job details), and financial documentation (invoice details). All these are potential debate points.

You instruct the agents to run `get_customer` or `list_customers`. The resulting data is then debated among the agents to determine if further action (like an update) is necessary.

You initiate a debate. The agents might review the old data via `get_job` and then debate the proper payload for calling `update_job`.

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