How to Use the Duoplane MCP in AutoGen
Let AutoGen agents debate inventory discrepancies and coordinate purchase orders using live Duoplane data.
Works with every AI agent you already use
…and any MCP-compatible client
Connect Duoplane MCP to AutoGen
Create your Vinkius account to connect Duoplane 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.
AutoGen agents debate Duoplane purchase orders
`list_unfulfilled_purchase_orders` triggers a multi-agent debate when a vendor misses a critical shipping deadline. A logistics agent extracts the late PO details, while a vendor relations agent reviews the supplier's historical performance. The agents negotiate the best course of action—whether to cancel the PO or issue a warning—using data from `get_purchase_order_details`. This collaborative approach prevents rash automated cancellations that could damage supplier relationships.
AutoGen agents audit Duoplane stock levels
`quick_vendor_inventory_audit` provides the raw data for an automated stock reconciliation conversation. Your inventory agent flags discrepancies, while a sales agent analyzes recent order volumes to determine the urgency of a sync. If they agree a stockout is imminent, they call `list_synced_products` to verify the SKU mapping across your sales channels. The agents reach a consensus on the correct stock level before updating your ecommerce database.
Resolve Duoplane order issues via AutoGen debate
`get_order_details` retrieves the complete history of a disputed customer order for your AutoGen customer service swarm. A finance agent checks payment status while a fulfillment agent checks the corresponding purchase order status. By sharing these details in their conversation thread, the agents verify if the delay occurred at your storefront or the vendor's warehouse. They resolve the dispute and construct a clear timeline for your support team.
Set up Duoplane 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 includesmcp_server_toolsfor 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
AssistantAgentand callagent.run(). The agent invokes Duoplane tools and returns structured results.
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="Duoplane_assistant",
model_client=OpenAIChatCompletionClient(model="gpt-4o"),
tools=tools,
)
result = await agent.run("List recent Duoplane data")
print(result.messages[-1].content) 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.
McpWorkbenchis 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=workbenchto your agent. State is preserved across multiple tool calls within the same session.
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="Duoplane_assistant",
model_client=OpenAIChatCompletionClient(model="gpt-4o"),
workbench=workbench,
)
result = await agent.run("List recent Duoplane data")
print(result.messages[-1].content) Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Duoplane. 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 Duoplane MCP in AutoGen
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