How to Use the Google Analytics MCP in Google ADK

Q: Can google-adk run multiple Google Analytics reports at once?

Yes, the agent calls batchrunreports to execute multiple query configurations in a single API request. This reduces latency and keeps your Google Cloud infrastructure costs down by avoiding sequential calls.

Q: How do I discover available metrics in Google Analytics with google-adk?

Your agent runs getmetadata to retrieve all standard and custom dimensions for a specific property. This lets the model dynamically adapt its queries to your custom tracking setup without hardcoded schemas.

Feed real-time GA4 metrics directly into your Gemini long-context models using the Google ADK framework.

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Connect Google Analytics MCP to Google ADK

Create your Vinkius account to connect Google Analytics 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 Google Analytics with Google ADK

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Query GA4 properties via the Google ADK MCP Server

This MCP Server connects Gemini models directly to your live GA4 data streams, bypassing the need for manual CSV exports. Your agent executes `list_properties` to locate the target property ID before pulling real-time metrics. Because the Google ADK handles 1M+ token contexts, your agent can ingest raw JSON payloads from `run_report` to analyze long-term acquisition trends. The model parses months of traffic data in one pass, identifying patterns without external database steps.

Monitor live traffic metrics in real time

The `run_realtime_report` tool pulls active user counts and screen pageviews from the last 30 to 60 minutes. Your agent monitors these metrics during product launches to catch sudden traffic spikes or broken checkout paths immediately. When anomalies occur, the MCP Server runs `list_accounts` to verify permissions across your portfolio. This allows multi-property operations to scale without configuring separate API keys for each analytics dashboard.

Extract audience lists for marketing campaigns

The `list_audience_exports` tool retrieves the status of your GA4 audience extraction jobs directly into your Python workflow. Your agent checks whether the export is active, failed, or still creating without opening the GA4 admin panel. Once ready, the agent calls `get_audience_export` to fetch the user lists for activation in Google Ads. This direct bridge allows your Google ADK pipelines to automate audience targeting based on live site behavior.

Setup guide

Set up Google Analytics 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 Google Analytics 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="Google Analytics_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Google Analytics 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 Google Analytics 4. 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 Google Analytics MCP in Google ADK

Use McpToolset with your Vinkius HTTP endpoint URL and pass it to your LlmAgent tools list. The Gemini model automatically detects tools like `run_report` and generates the correct parameters.

Yes, the agent calls `batch_run_reports` to execute multiple query configurations in a single API request. This reduces latency and keeps your Google Cloud infrastructure costs down by avoiding sequential calls.

Your agent runs `get_metadata` to retrieve all standard and custom dimensions for a specific property. This lets the model dynamically adapt its queries to your custom tracking setup without hardcoded schemas.

No, while the agent framework integrates with BigQuery, this setup queries the GA4 API directly via the Vinkius endpoint. This direct hook gets you real-time data without waiting for daily export tables to sync.

Your GA4 property configurations and audience export files are protected by Vinkius's zero-trust infrastructure. The server runs in an ephemeral isolate, ensuring your OAuth tokens and user activity logs are never cached or exposed to the LLM provider.

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