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How to Use the ChurnZero MCP in Google ADK

Feed ChurnZero data into Google ADK to analyze account health against your BigQuery enterprise datasets.

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Google ADK

Connect ChurnZero MCP to Google ADK

Create your Vinkius account to connect ChurnZero 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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Query Success Metrics with Google ADK

Accessing specific account records starts with the `get_account_success_details` MCP tool. Your Gemini model pulls in churn scores and health metrics to analyze alongside usage logs already stored in BigQuery. Long-context reasoning changes how you handle customer support. You feed thousands of rows of account history into a 1M+ token window and let the agent find hidden retention risks.

Surface Active Customer Alerts

The `list_churnzero_alerts` tool feeds critical warning signs directly to your enterprise agents. Vertex AI pipelines consume these alerts to trigger automated retention workflows across Google Cloud. Combining these warnings with `list_customer_messages` gives your model the full communication history. The agent reads exactly what was said before the alert fired.

Monitor Playbooks via MCP Server

Reviewing standard operating procedures happens through the `list_success_playbooks` tool. Your agent compares actual customer progress against the expected steps defined in your success platform. Native integration with GCP means you map these playbook stages to real cloud usage. If a playbook requires API activation, your agent verifies the BigQuery logs before marking the step complete.

Setup guide

Set up ChurnZero 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 ChurnZero 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="ChurnZero_agent",
    model="gemini-2.0-flash",
    instruction="You have access to ChurnZero 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 ChurnZero. 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.

Why Choose Vinkius

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Common questions about ChurnZero MCP in Google ADK

Install the package and set up `McpToolset` using your Vinkius HTTP endpoint. Pass the toolset directly to your `LlmAgent` initialization. You restrict exposed tools using the optional `tool_names` filter.
Your agent pushes activity records using the `track_account_event` tool. This lets Gemini log product usage milestones directly into your success tracking system.
The server outputs raw JSON that fits easily into massive context windows. You pull complete lists of contacts and journeys to feed deep reasoning tasks.
Your agent executes `list_churnzero_accounts` to grab customer IDs and metadata. It then writes queries against BigQuery to join those IDs with your internal transaction records.
Message logs and contact details process within a zero-trust execution environment. Vinkius requires a single endpoint token for authentication and destroys the runtime state the second the response ships.

Start using the ChurnZero MCP today

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