Google Analytics MCP Server for Google ADK 12 tools — connect in under 2 minutes
Google Agent Development Kit (ADK) is Google's framework for building production AI agents. Add Google Analytics as an MCP tool provider through the Vinkius and your ADK agents can call every tool with full schema introspection.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
from google.adk.agents import Agent
from google.adk.tools.mcp_tool import McpToolset
from google.adk.tools.mcp_tool.mcp_session_manager import (
StreamableHTTPConnectionParams,
)
# Your Vinkius token — get it at cloud.vinkius.com
mcp_tools = McpToolset(
connection_params=StreamableHTTPConnectionParams(
url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
)
)
agent = Agent(
model="gemini-2.5-pro",
name="google_analytics_agent",
instruction=(
"You help users interact with Google Analytics "
"using 12 available tools."
),
tools=[mcp_tools],
)
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About Google Analytics MCP Server
Connect your Google Analytics 4 (GA4) account to any AI agent and take full control of web and app analytics through natural conversation.
Google ADK natively supports Google Analytics as an MCP tool provider — declare the Vinkius Edge URL and the framework handles discovery, validation, and execution automatically. Combine 12 tools with Gemini's long-context reasoning for complex multi-tool workflows, with production-ready session management and evaluation built in.
What you can do
- Custom Reports — Run reports with any combination of metrics (activeUsers, screenPageViews, sessions, eventCount) and dimensions (city, country, deviceCategory, channel grouping)
- Realtime Data — Monitor what's happening on your site right now with live user counts, events, and traffic sources from the last 30-60 minutes
- Batch Reports — Execute multiple report configurations in a single API call for efficient dashboard loading
- Metadata Discovery — List all available metrics and dimensions for your property, including custom definitions
- Compatibility Checks — Validate metric/dimension combinations before running reports to avoid errors
- Audience Exports — List and monitor audience export jobs for user segmentation and activation
- User Activity — Retrieve event history for specific users for journey analysis and support investigations
- Funnel Analysis — Visualize user progression through conversion steps and identify drop-off points
The Google Analytics MCP Server exposes 12 tools through the Vinkius. Connect it to Google ADK in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect Google Analytics to Google ADK via MCP
Follow these steps to integrate the Google Analytics MCP Server with Google ADK.
Install Google ADK
Run pip install google-adk
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Create the agent
Save the code above and integrate into your ADK workflow
Explore tools
The agent will discover 12 tools from Google Analytics via MCP
Why Use Google ADK with the Google Analytics MCP Server
Google ADK provides unique advantages when paired with Google Analytics through the Model Context Protocol.
Google ADK natively supports MCP tool servers — declare a tool provider and the framework handles discovery, validation, and execution
Built on Gemini models, ADK provides long-context reasoning ideal for complex multi-tool workflows with Google Analytics
Production-ready features like session management, evaluation, and deployment come built-in — not bolted on
Seamless integration with Google Cloud services means you can combine Google Analytics tools with BigQuery, Vertex AI, and Cloud Functions
Google Analytics + Google ADK Use Cases
Practical scenarios where Google ADK combined with the Google Analytics MCP Server delivers measurable value.
Enterprise data agents: ADK agents query Google Analytics and cross-reference results with internal databases for comprehensive analysis
Multi-modal workflows: combine Google Analytics tool responses with Gemini's vision and language capabilities in a single agent
Automated compliance checks: schedule ADK agents to query Google Analytics regularly and flag policy violations or configuration drift
Internal tool platforms: build self-service agent platforms where teams connect their own MCP servers including Google Analytics
Google Analytics MCP Tools for Google ADK (12)
These 12 tools become available when you connect Google Analytics to Google ADK via MCP:
batch_run_reports
Provide property_id and an array of report configurations. Each report can have different metrics, dimensions, and date ranges. This is efficient for dashboard loading or comparative analysis. The reports parameter should be a JSON array of report objects with metrics, dimensions, and dateRanges. Run multiple reports in a single API call
check_compatibility
Before running complex reports, use this to ensure compatibility between your chosen metrics and dimensions. This prevents errors and wasted API calls. Provide property_id and the metrics/dimensions you plan to use. Returns compatibility status and any conflicts that would prevent the report from running successfully. Check if metrics and dimensions can be combined in a report
get_audience_export
Audience exports allow you to extract user lists matching specific audience criteria. Use this to monitor the progress of audience extraction jobs. Provide property_id and the audience_export_id from list_audience_exports. Get status of a specific audience export
get_metadata
This includes both standard and custom metrics/dimensions with their descriptions, types, and compatibility information. Use this to discover what data is available before building reports. The propertyId is required and can be found in your GA4 admin settings. Get available metrics and dimensions for a GA4 property
get_property
Use the property_id obtained from list_properties to inspect property configuration. Get detailed information about a specific GA4 property
get_user_activity
This shows all interactions a user has had with your property, including pageviews, events, and conversions. Use this for user-level analysis, journey mapping, or support investigations. The userId must match the one sent with your tracking events. Get activity history for a specific user
list_accounts
This is the top-level container for properties. Each account can contain multiple properties. Use this to discover what accounts are available before drilling down into properties. List all Google Analytics accounts accessible to the user
list_audience_exports
Audience exports are used to extract user lists matching specific audience criteria for activation in other platforms. Shows status (CREATING, ACTIVE, FAILED) and configuration of each export job. List all audience export jobs for a property
list_properties
Properties represent individual websites, apps, or measurement streams. Each property has a unique ID needed for running reports. Use this to find the correct property_id for report queries. List all GA4 properties in an account
run_funnel_report
This helps identify where users drop off in conversion paths like checkout flows or signup processes. Provide property_id and a funnelSpec object defining the steps and breakdown settings. The funnelSpec should be a JSON object with steps array containing stepName, filterExpression, and optional breakdown settings. Run a funnel analysis report
run_realtime_report
Unlike standard reports, this shows what's happening on your site/app right now. Provide property_id and the metrics/dimensions you want to monitor in realtime. Common realtime metrics: activeUsers, eventCount, screenPageViews. Common realtime dimensions: city, country, deviceCategory, streamId. Get realtime analytics data (last 30-60 minutes)
run_report
You must provide the property_id, metrics (e.g., 'activeUsers', 'screenPageViews', 'eventCount'), and dimensions (e.g., 'city', 'pageTitle', 'sessionDefaultChannelGrouping'). Date ranges use YYYY-MM-DD format. Optional filter expression can narrow results. Common metrics: activeUsers, screenPageViews, sessions, eventCount, engagementRate, averageSessionDuration. Common dimensions: city, country, deviceCategory, sessionDefaultChannelGrouping, pageTitle, pagePath. Run a custom Google Analytics report
Example Prompts for Google Analytics in Google ADK
Ready-to-use prompts you can give your Google ADK agent to start working with Google Analytics immediately.
"Show me the number of active users and pageviews by country for the last 7 days for property 123456789."
"What's happening on the site right now? Show me realtime users by traffic source."
"Run a funnel analysis for our checkout flow: step 1 = viewed product, step 2 = added to cart, step 3 = started checkout, step 4 = completed purchase. Show me where users drop off."
Troubleshooting Google Analytics MCP Server with Google ADK
Common issues when connecting Google Analytics to Google ADK through the Vinkius, and how to resolve them.
McpToolset not found
pip install --upgrade google-adkGoogle Analytics + Google ADK FAQ
Common questions about integrating Google Analytics MCP Server with Google ADK.
How does Google ADK connect to MCP servers?
Can ADK agents use multiple MCP servers?
Which Gemini models work best with MCP tools?
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Connect Google Analytics to Google ADK
Get your token, paste the configuration, and start using 12 tools in under 2 minutes. No API key management needed.