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How to Use the Loyverse MCP in Google ADK

Run long-context retail analytics on Loyverse data using the Google ADK and Gemini models.

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Google ADK

Connect Loyverse MCP to Google ADK

Create your Vinkius account to connect Loyverse 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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Multi-store analytics with Google ADK

Stop wrestling with manual CSV exports from your registers. By linking this MCP server with the Google ADK, your Gemini agents can query `l_list_locations` to map your entire retail footprint. This setup lets you feed store locations and sales data directly into your Google Cloud pipelines. Your agent can coordinate complex queries across multiple stores without you writing custom ETL scripts.

Long-context inventory auditing

Gemini models handle massive context windows, making them perfect for scanning huge catalogs. The Google ADK lets your agent call `l_list_items` to pull your entire inventory list into memory for deep analysis. Instead of processing catalogs in tiny chunks, you can feed thousands of items directly to the model. The agent can flag stock anomalies or suggest reorder points by comparing live listings against historical trends.

BigQuery-ready receipt processing

Connect your physical store transactions to your enterprise data warehouse. By using `l_list_receipts` through this MCP server, your agent can fetch raw transaction logs filtered by specific date ranges. You can easily pipe this raw transaction data into BigQuery for advanced reporting. It bridges the gap between your on-the-ground POS registers and your cloud-based business intelligence tools.

Setup guide

Set up Loyverse 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. 1

    Install Google ADK

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

  2. 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. 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. 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 Loyverse 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="Loyverse_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Loyverse tools via MCP.",
    tools=mcp_tools,
)

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Loyverse. 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 Loyverse MCP in Google ADK

Run pip install google-adk to get started. Use McpToolset with StreamableHttpServerParameters pointing to your Vinkius endpoint, and pass it to your LlmAgent tools list.
Yes. You can use the optional tool_names filter when initializing your toolset to expose only l_list_items, hiding other endpoints like customer lists from the agent.
Yes. The MCP toolset supports both transport mechanisms, but for cloud-hosted deployments on Google Cloud, the streamable HTTP transport is highly recommended.
Yes. Because the toolset is fully compatible with Google Cloud's Python ecosystem, you can deploy these agents inside Vertex AI to automate your retail operations.
The MCP server runs in an ephemeral V8 sandbox on Vinkius. No store coordinates or inventory counts are persisted on our servers; they are piped directly to your Google ADK agent in real-time.

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