How to Use the Kissmetrics MCP in Google ADK

Q: How do I filter tools when using Kissmetrics with Google ADK?

You can pass a toolnames filter to the McpToolset constructor. This restricts your agent to only the Kissmetrics tools you explicitly want it to access.

Q: Can I use Google ADK to query Kissmetrics metric data?

You can use the querymetricdata tool to fetch specific metric results. It integrates with your agent's toolset just like any other native Google Cloud service.

Bring Kissmetrics into your Google ADK environment. Manage event tracking and user properties alongside your BigQuery data workflows.

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Connect Kissmetrics MCP to Google ADK

Create your Vinkius account to connect Kissmetrics 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 Kissmetrics with Google ADK

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Update user properties in Google ADK

Keep your user attributes current as your agent learns more about them. Use `set_person_properties` to update profiles without leaving your agent environment. This allows for highly personalized agent behavior based on the latest user data. It keeps your records accurate without extra database queries.

Audit your events with Google ADK

Don't guess which events are available to track. Use `list_event_types` to pull the full list of defined events directly into your agent's working memory. This ensures your agent uses the correct event names every time. It prevents the common issue of sending data to non-existent event categories.

Run complex queries in Google ADK

Your agent can now answer questions about your growth metrics directly. Use `query_people_count` to get exact figures for your target segments. This turns your agent into an analytics analyst that works 24/7. It provides the hard numbers you need to justify your next growth experiment.

Setup guide

Set up Kissmetrics 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 Kissmetrics 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="Kissmetrics_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Kissmetrics 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 Kissmetrics. 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 Kissmetrics MCP in Google ADK

You can pass a tool_names filter to the McpToolset constructor. This restricts your agent to only the Kissmetrics tools you explicitly want it to access.

Yes, the transport is configurable. You can run the server locally via Stdio or connect to our managed HTTP endpoint depending on your deployment environment.

You can use the `query_metric_data` tool to fetch specific metric results. It integrates with your agent's toolset just like any other native Google Cloud service.

It is. You can feed the output of your Kissmetrics queries into your prompt to provide the model with massive amounts of historical context.

We enforce strict isolation for every connection. Your event data and user properties are processed in an ephemeral sandbox, meaning no trace of your information remains on our servers once the request finishes.

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