Google Analytics MCP Server for CrewAI 12 tools — connect in under 2 minutes
Connect your CrewAI agents to Google Analytics through Vinkius, pass the Edge URL in the `mcps` parameter and every Google Analytics tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.
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Vinkius supports streamable HTTP and SSE.
from crewai import Agent, Task, Crew
agent = Agent(
role="Google Analytics Specialist",
goal="Help users interact with Google Analytics effectively",
backstory=(
"You are an expert at leveraging Google Analytics tools "
"for automation and data analysis."
),
# Your Vinkius token. get it at cloud.vinkius.com
mcps=["https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"],
)
task = Task(
description=(
"Explore all available tools in Google Analytics "
"and summarize their capabilities."
),
agent=agent,
expected_output=(
"A detailed summary of 12 available tools "
"and what they can do."
),
)
crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)
* 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.
When paired with CrewAI, Google Analytics becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Google Analytics tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.
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 CrewAI 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 CrewAI via MCP
Follow these steps to integrate the Google Analytics MCP Server with CrewAI.
Install CrewAI
Run pip install crewai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com
Customize the agent
Adjust the role, goal, and backstory to fit your use case
Run the crew
Run python crew.py. CrewAI auto-discovers 12 tools from Google Analytics
Why Use CrewAI with the Google Analytics MCP Server
CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Google Analytics through the Model Context Protocol.
Multi-agent collaboration lets you decompose complex workflows into specialized roles, one agent researches, another analyzes, a third generates reports, each with access to MCP tools
CrewAI's native MCP integration requires zero adapter code: pass Vinkius Edge URL directly in the `mcps` parameter and agents auto-discover every available tool at runtime
Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls
Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports
Google Analytics + CrewAI Use Cases
Practical scenarios where CrewAI combined with the Google Analytics MCP Server delivers measurable value.
Automated multi-step research: a reconnaissance agent queries Google Analytics for raw data, then a second analyst agent cross-references findings and flags anomalies. all without human handoff
Scheduled intelligence reports: set up a crew that periodically queries Google Analytics, analyzes trends over time, and generates executive briefings in markdown or PDF format
Multi-source enrichment pipelines: chain Google Analytics tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow
Compliance and audit automation: a compliance agent queries Google Analytics against predefined policy rules, generates deviation reports, and routes findings to the appropriate team
Google Analytics MCP Tools for CrewAI (12)
These 12 tools become available when you connect Google Analytics to CrewAI 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 CrewAI
Ready-to-use prompts you can give your CrewAI 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 CrewAI
Common issues when connecting Google Analytics to CrewAI through the Vinkius, and how to resolve them.
MCP tools not discovered
Agent not using tools
Timeout errors
Rate limiting or 429 errors
Google Analytics + CrewAI FAQ
Common questions about integrating Google Analytics MCP Server with CrewAI.
How does CrewAI discover and connect to MCP tools?
tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.Can different agents in the same crew use different MCP servers?
mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.What happens when an MCP tool call fails during a crew run?
Can CrewAI agents call multiple MCP tools in parallel?
process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.Can I run CrewAI crews on a schedule (cron)?
crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.Connect Google Analytics with your favorite client
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Connect Google Analytics to CrewAI
Get your token, paste the configuration, and start using 12 tools in under 2 minutes. No API key management needed.