How to Use the Duoplane MCP in Google ADK

Q: How does Duoplane handle large vendor catalogs within Google ADK?

It uses the listsyncedproducts tool to fetch paginated batches of products. Gemini's massive context window easily ingests these large payloads to find matching SKUs across systems.

Connect your Google ADK agents to Duoplane to manage multi-vendor supply chains directly alongside your BigQuery warehouse.

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Connect Duoplane MCP to Google ADK

Create your Vinkius account to connect Duoplane to Google ADK 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 Duoplane with Google ADK

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Google ADK Supply Chain Diagnostics

The `list_unfulfilled_purchase_orders` tool provides the raw status data your Gemini-powered agents need to identify shipping bottlenecks using this MCP Server. Because the Google ADK handles long contexts, your agent can process hundreds of open purchase orders in a single run. The agent checks this list against your historical shipping logs to find which suppliers are lagging. It uses `get_purchase_order_details` to pinpoint the exact line items causing the delay.

Enterprise Vendor Directory Synchronization

The `list_active_vendors` tool pulls your entire dropship supplier roster into your Google Cloud agent system. You can feed this vendor data straight into BigQuery to run performance evaluations. When an agent notices a drop in fulfillment rates, it calls `get_vendor_profile` to pull contract terms. The Google ADK then matches these terms against real-time operational data to flag non-compliant suppliers.

Cross-Channel Catalog Audits

The `list_synced_products` tool outputs current SKU configurations and inventory counts across all connected storefronts. Your enterprise agent runs this tool to verify that your database matches your active vendor listings. If a discrepancy pops up, the agent triggers `quick_vendor_inventory_audit` to see where the sync broke down. This direct integration keeps your Google ADK agents from making decisions based on stale warehouse numbers over this MCP link.

Setup guide

Set up Duoplane MCP in Google ADK

Prerequisites

Python 3.10+ installed
google-adk package (pip install google-adk)
Active Vinkius subscription with a valid endpoint token

1

Install Google ADK

Run pip install google-adk to install the Agent Development Kit. MCP support is included via the McpToolset class.
2

Connect via SSE transport

Use McpToolset.from_server() with SseServerParams pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create an LlmAgent

Pass the returned mcp_tools list directly to LlmAgent(tools=mcp_tools). The ADK maps each MCP tool to a native Gemini function call — no manual schema definitions required.
4

Run with any Gemini model

The agent works with any Gemini model (gemini-2.0-flash, gemini-2.5-pro, etc.). Copy the full example on the right to get started with Duoplane tools in your ADK agent.

agent.py

from google.adk.agents import LlmAgent
from google.adk.tools.mcp_tool.mcp_toolset import McpToolset
from google.adk.tools.mcp_tool.mcp_session_manager import SseServerParams

# Connect to the MCP via SSE
mcp_tools, exit_stack = await McpToolset.from_server(
    connection_params=SseServerParams(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    )
)

# Create your agent with auto-discovered tools
agent = LlmAgent(
    name="Duoplane_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Duoplane tools via MCP.",
    tools=mcp_tools,
)

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Common questions about Duoplane MCP in Google ADK

You initialize the toolset in Python using the Streamable HTTP server parameters and pass it to your LlmAgent. This makes tools like `list_ecommerce_orders` instantly accessible to Gemini.

No, this server acts as a read-and-monitor tool, exposing endpoints like `quick_vendor_inventory_audit` to analyze stock status. Your agent uses these insights to trigger downstream automation workflows inside Google Cloud.

It uses the `list_synced_products` tool to fetch paginated batches of products. Gemini's massive context window easily ingests these large payloads to find matching SKUs across systems.

Yes, you can write agents that query BigQuery sales trends and then use `get_order_details` to check fulfillment status. This lets you build closed-loop agents that run on both warehouse data and live operations.

All credentials and API requests passing through the server are executed in ephemeral, zero-trust V8 isolates. Your purchase order details and supplier profiles are processed entirely in memory and never written to disk.

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