How to Use the Lead Time Analyzer MCP in AutoGen

Q: How do I connect the Lead Time Analyzer tools to my AutoGen agents?

Use the mcpservertools function with your server's URL. This function fetches the tools from the MCP and prepares them for use. Just pass the resulting tool list into your AssistantAgent's constructor.

Q: Do I need to handle the tool schemas myself?

No, the McpToolAdapter handles it automatically. It converts the MCP's tool definitions into a format that AutoGen agents can understand and execute directly.

Let your AutoGen agents debate supply chain strategy and converge on the best way to reduce lead times.

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Arm Your Agents for a Real Debate

This isn't about one agent finding one answer. This is about giving multiple agents the data they need to argue effectively. One agent, the 'Aggressor,' can use `analyze_lead_time_composition` to find the longest stage and demand action. But another agent, the 'Stabilizer,' can counter by calling `evaluate_process_volatility`. It might argue that the longest stage is predictable, but the shortest stage has wild swings causing all the stockouts. The data doesn't lie, and now your agents can have a debate grounded in it.

Simulate and Challenge Scenarios

Once a course of action is proposed, an agent can use `calculate_reduction_impacts` to model the outcome. For example, 'A 10% cut in manufacturing saves 5 days.' This becomes a hard fact in the conversation. Here's the kicker: another agent can challenge that simulation. It could argue, 'Yes, but what's the cost of that 10% cut? Let's simulate a smaller, cheaper change to the transit stage instead.' The agents use the tool to test competing hypotheses until they reach a consensus you can trust.

Consensus-Driven Analysis in AutoGen

This MCP provides the vocabulary for a structured supply chain discussion between your agents. Instead of just guessing, they use the tools to bring evidence to the table. This MCP server acts as the impartial source of truth they all consult. You can design a conversation where a 'Finance' agent pushes for cost-effective changes, while an 'Operations' agent pushes for the biggest time savings. They use the same tools to model their respective proposals, and the final plan is a negotiated compromise based on the data this MCP provides.

Setup guide

Set up Lead Time Analyzer 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 Lead Time Analyzer 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="Lead Time Analyzer_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Lead Time Analyzer 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="Lead Time Analyzer_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Lead Time Analyzer 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 Lead Time Analyzer. 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 Lead Time Analyzer MCP in AutoGen

Use the `mcp_server_tools` function with your server's URL. This function fetches the tools from the MCP and prepares them for use. Just pass the resulting tool list into your AssistantAgent's constructor.

Yes. You can create multiple agents and provide each with a different subset of the tools from this MCP. For instance, give one agent the analysis tools and another agent only the simulation tool.

One agent might initiate by calling a tool to get data. It presents the findings, and another agent can then critique the finding or call a different tool to get countervailing evidence. They go back and forth until they agree on a conclusion.

No, the `McpToolAdapter` handles it automatically. It converts the MCP's tool definitions into a format that AutoGen agents can understand and execute directly.

Your lead time component and volatility data is processed ephemerally by this MCP. The data is sent securely for each tool call and is not stored or logged by Vinkius. The conversation history, including tool outputs, is managed within your own AutoGen environment.

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