How to Use the Youzan / 有赞 MCP in Google ADK

Q: How do I use Youzan / 有赞 with the Google ADK?

You initialize your toolset using McpToolset and pass it to your LlmAgent. Because the Google ADK supports native BigQuery integration, you'll find these e-commerce tools connect seamlessly.

Run enterprise e-commerce logic on Google Cloud with the Google ADK.

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Connect Youzan / 有赞 MCP to Google ADK

Create your Vinkius account to connect Youzan / 有赞 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 Youzan / 有赞 with Google ADK

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Analyze sales data using BigQuery integration.

The `get_sales_stats` tool lets your agent pull performance metrics directly into your Google Cloud workflow. Since you're already in the Gemini ecosystem, these numbers can immediately feed into BigQuery for deep analysis. If you need to check specific sales actions, running `list_orders` gives a clean list of sold trades that sync perfectly with existing Google data pipelines.

Map out product hierarchies.

Need to know what types of products are available? Use the `list_categories` tool. This helps your agent build out the full taxonomy of items you sell. For specific item details, running `get_item` provides all necessary attributes. These structured outputs work naturally with Google's typed data models in Vertex AI.

Manage customer lifecycles in one place.

You can manage the entire scope of your user base using `list_customers`. This function helps your agent search and categorize shoppers quickly. When an action is required, calling `get_customer` retrieves specific details. All this data flows natively into Google Cloud infrastructure for long-context reasoning.

Setup guide

Set up Youzan / 有赞 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 Youzan / 有赞 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="Youzan / 有赞_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Youzan / 有赞 tools via MCP.",
    tools=mcp_tools,
)

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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 Youzan / 有赞. 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 Youzan / 有赞 MCP in Google ADK

You initialize your toolset using `McpToolset` and pass it to your `LlmAgent`. Because the Google ADK supports native BigQuery integration, you'll find these e-commerce tools connect seamlessly.

Yes. The underlying Gemini models handle 1M+ tokens of context. This means your agent can process a massive amount of sales or customer history gathered from Youzan / 有赞 in one go.

The server touches core transactional and profile data, including details retrieved via `get_order` and `list_orders`. Since it's built for enterprise use, every piece of data is designed to be scalable within BigQuery.

It’s designed precisely for that. The native integration means you can run your e-commerce agents alongside other services in Vertex AI or BigQuery without worrying about data transfer layers.

The agent framework supports both Stdio and HTTP transports, making it highly resilient. By using it with your existing BigQuery setup, you ensure that e-commerce actions are recorded in a trusted, long-term cloud store.

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