How to Use the Giddyup MCP in AutoGen

Q: How do AutoGen agents negotiate Giddyup schedules?

Agents exchange messages to propose schedules based on listjobs data. They only execute the final createjob call once they reach a consensus on the technician and time slot.

Deploy AutoGen agents that debate and coordinate Giddyup job dispatches, lead assignments, and technician schedules.

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Create your Vinkius account to connect Giddyup 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 Giddyup with AutoGen

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Perplexity

Resolve dispatch conflicts via AutoGen agent debate

Let your agents coordinate complex scheduling decisions through structured conversation. A dispatcher agent can call `list_jobs` to identify open tickets, while a routing agent checks technician availability using `list_users`. The agents debate the best assignments based on location and skill set before calling `update_job`. This consensus-driven approach prevents scheduling conflicts and reduces travel times for your field crew.

Automate lead transition using this MCP Server

Manage your sales funnel with specialized agents that handle handoffs. A sales agent uses `get_lead` to review incoming prospects, while an operations agent evaluates resource capacity. Once both agents agree that a lead is qualified and a tech is available, the operations agent calls `create_job` to schedule the work. This ensures you never book a job that your field team cannot fulfill.

Audit invoice records and system statuses

Set up a dedicated billing agent to cross-reference completed work with outstanding balances. The agent pulls active financial data using `list_invoices` and compares it against job logs retrieved from `get_job`. If a customer has an unpaid balance, a finance agent can flag the account and call `update_lead` to alert the sales team. This keeps your cash flow healthy without requiring manual billing audits.

Setup guide

Set up Giddyup 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 Giddyup 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="Giddyup_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

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

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Giddyup. 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 Giddyup MCP in AutoGen

Use the MCP server tools adapter to fetch the schemas from your endpoint. Pass the resulting tool list directly to your assistant agents so they can begin collaborating on jobs.

Yes, your agents share access to the MCP tools. One agent can query customer profiles using `get_customer` while another updates job details in the same conversation thread.

Agents exchange messages to propose schedules based on `list_jobs` data. They only execute the final `create_job` call once they reach a consensus on the technician and time slot.

The integration supports both stdio and streamable HTTP transports. This gives you the flexibility to run your multi-agent system locally or deploy it in a cloud environment.

All invoice records and customer profiles are processed in sandbox environments. This secure MCP Server runs inside isolated containers, ensuring your credentials and database records are never exposed to external LLM providers during agent debates.

Use it with your favorite AI tools

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