How to Use the Upper Route Planner MCP in AutoGen

Q: What data does Upper Route Planner provide to AutoGen for debate?

It provides operational logistics records—driver lists (listupperdrivers) and full route schedules. These tools serve as facts that opposing agents must argue around, reaching a final decision.

Achieve consensus on complex scheduling decisions with AutoGen and the Upper Route Planner MCP Server.

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Connect Upper Route Planner MCP to AutoGen

Create your Vinkius account to connect Upper Route Planner 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 Upper Route Planner with AutoGen

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Perplexity

Debating Delivery Task Creation

You can set up a debate where one agent suggests using `create_upper_delivery_task`. A second agent reviews the feasibility by calling `check_upper_status`, and they negotiate on whether to proceed with the task.

Comparing Driver Lists and Routes

Multiple agents can challenge each other’s assumptions. One might call `list_upper_drivers` while another calls `list_upper_routes`, forcing a deliberation on which combination of personnel and routes is optimal for the job.

Validating Stop Details in Consensus

Need to know if a stop detail is correct? Agent A can call `get_upper_stop_details` to get the data, while Agent B independently calls `get_upper_route_stop`. They debate which source of information should be trusted.

Setup guide

Set up Upper Route Planner 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 Upper Route Planner 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="Upper Route Planner_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Upper Route Planner 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="Upper Route Planner_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Upper Route Planner 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 Upper Route Planner. 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 Upper Route Planner MCP in AutoGen

It forces agents to deliberate. For example, one agent suggests using `create_upper_delivery_task`, but a performance agent challenges it by calling `list_upper_routes` first, leading to a consensus on the best time to execute.

Yes. You can set up competing agents: one focused on maximizing stops (calling `get_upper_stop_details`), and another focused on minimizing time, debating the best sequence of actions.

It provides operational logistics records—driver lists (`list_upper_drivers`) and full route schedules. These tools serve as facts that opposing agents must argue around, reaching a final decision.

It allows multiple specialized agents to work together. They don't just run steps; they debate the results of tool calls like `get_upper_route_stop` until a definitive conclusion is reached.

The MCP Server provides delivery routes, driver information, and stop details. These varied datasets allow agents to argue over the most accurate or efficient plan of action.

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