How to Use the KuaiDi100 MCP in AutoGen

Q: Can I have one AutoGen agent track a package and another handle exceptions?

Yes, that's a perfect use case. You can have a UserProxyAgent that kicks off the process, an AssistantAgent that calls trackpackage, and a separate NotifierAgent that only gets activated when the tracking status shows an error. The agents communicate to solve the problem.

Q: What's the setup for using the KuaiDi100 MCP server with AutoGen?

First, install the AutoGen MCP extension. Then, use the mcpservertools function, passing it your Vinkius server URL. This function fetches all the available KuaiDi100 tools and makes them ready to be assigned to your AssistantAgent's llmconfig.

Let your AutoGen agents debate the best way to ship and track packages using KuaiDi100.

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Setup KuaiDi100 with AutoGen

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Negotiate Shipping Routes

With AutoGen, you don't just call a tool; you start a discussion. Create a "Cost Agent" that only has permission to use `query_shipping_price` and an "Express Agent" that can only use `estimate_delivery_time`. When a new order comes in, both agents present their findings in a group chat. They debate the trade-offs between the cheapest and fastest options, using data from KuaiDi100 as evidence. A manager agent then makes the final call before `submit_shipping_order` is executed.

Create a Collaborative Watchdog Team

Set up a team of agents to monitor shipments. A `TrackerAgent` calls `track_package` daily for all active shipments. If it detects a package is stalled, it doesn't just fail silently—it posts a message to the group chat. A `SupportAgent` sees the message and can use `get_map_tracking` to visualize the last known location. It might then decide to use `subscribe_tracking` to get more frequent updates. It's a proactive team that solves problems before customers even notice.

Let Agents Choose the Carrier with this MCP Server

You can build a sophisticated carrier selection system with AutoGen. A user just provides a destination address. One agent is tasked with running `check_carrier_availability` for the route to see who is viable. Meanwhile, another agent might review historical performance data if you've integrated a database. They present their findings, and a `PlannerAgent` makes the final decision. This multi-agent setup for the MCP server ensures you're not relying on a single point of logic.

Setup guide

Set up KuaiDi100 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 KuaiDi100 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="KuaiDi100_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent KuaiDi100 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="KuaiDi100_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent KuaiDi100 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 KuaiDi100. 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 KuaiDi100 MCP in AutoGen

You create multiple agents, giving each one a specific role and access to different KuaiDi100 tools. One agent might argue for the cheapest option using `query_shipping_price`, while another argues for speed using `estimate_delivery_time`. They present their findings as messages until they reach a consensus or a manager agent decides.

Yes, that's a perfect use case. You can have a `UserProxyAgent` that kicks off the process, an `AssistantAgent` that calls `track_package`, and a separate `NotifierAgent` that only gets activated when the tracking status shows an error. The agents communicate to solve the problem.

First, install the AutoGen MCP extension. Then, use the `mcp_server_tools` function, passing it your Vinkius server URL. This function fetches all the available KuaiDi100 tools and makes them ready to be assigned to your AssistantAgent's `llm_config`.

Not at all. You can feed your team of agents a list of existing tracking numbers. One agent can use `identify_carrier` to figure out the shipper for each one, then pass the work to other specialized agents for tracking.

Each agent only has access to the data for the tools you give it. The data itself—tracking numbers, phone numbers, addresses for `submit_shipping_order`—is sent through a secure, isolated sandbox for each API call. The conversation history between agents, which may contain this data, is managed by your AutoGen setup.

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