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How to Use the Xiaomi Push Service / 小米推送 MCP in Google ADK

Act on deep business data to push targeted alerts using the Google ADK.

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Google ADK

Connect Xiaomi Push Service / 小米推送 MCP to Google ADK

Create your Vinkius account to connect Xiaomi Push Service / 小米推送 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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Triggering Xiaomi Push Service / 小米推送 from BigQuery Data

Your agent runs a complex query in BigQuery and, when the result meets criteria, it executes `push_to_topic`. This means business intelligence directly triggers customer-facing alerts. The system uses this mechanism to alert users on specific topics defined by your enterprise data models.

Enterprise Broadcasts with Xiaomi Push Service / 小米推送

If BigQuery analysis shows a global issue, the agent can trigger `push_to_all`. This ensures every connected device gets an immediate notification about the critical event. The Google ADK handles this scale by integrating cloud infrastructure directly into the tool call.

Managing Device State in the MCP Server

The agent can manage user permissions through topic management. When a department changes, your workflow calls `unsubscribe_from_topic`, removing access immediately. Conversely, calling `subscribe_to_topic` grants new users immediate access to relevant device updates.

Setup guide

Set up Xiaomi Push Service / 小米推送 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 Xiaomi Push Service / 小米推送 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="Xiaomi Push Service / 小米推送_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Xiaomi Push Service / 小米推送 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 Xiaomi Push Service / 小米推送. 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 Xiaomi Push Service / 小米推送 MCP in Google ADK

The agent uses the push service as a final action step. After long-context reasoning on 1M+ tokens of data, it triggers a push to notify users about the findings.
Yes. You can pinpoint delivery by calling `push_to_regid`. This is critical for compliance, ensuring alerts go only to authorized or monitored hardware.
It does. The agent can handle both `subscribe_to_topic` and `unsubscribe_from_topic`, allowing your internal workflows to govern who receives updates.
Yes. The `push_to_all` tool allows for immediate, high-scale communication whenever your BigQuery models detect a systemic change.
This server manages device identifiers (regIDs) and topic names. The agent logs these parameters, allowing you to trace exactly which topics were used for a push.

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