3,400+ MCP servers ready to use
Vinkius

Google Analytics 4 MCP Server for Pydantic AIGive Pydantic AI instant access to 12 tools to Batch Run Reports, Check Compatibility, Get Conversions, and more

Built by Vinkius GDPR 12 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Google Analytics 4 through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.

Ask AI about this App Connector for Pydantic AI

The Google Analytics 4 app connector for Pydantic AI is a standout in the Industry Titans category — giving your AI agent 12 tools to work with, ready to go from day one.

Vinkius delivers Streamable HTTP and SSE to any MCP client

python
import asyncio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")

    agent = Agent(
        model="openai:gpt-4o",
        mcp_servers=[server],
        system_prompt=(
            "You are an assistant with access to Google Analytics 4 "
            "(12 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in Google Analytics 4?"
    )
    print(result.data)

asyncio.run(main())
Google Analytics 4
Fully ManagedVinkius Servers
60%Token savings
High SecurityEnterprise-grade
IAMAccess control
EU AI ActCompliant
DLPData protection
V8 IsolateSandboxed
Ed25519Audit chain
<40msKill switch
Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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 4 MCP Server

Connect your Google Analytics 4 property to any AI agent and access web analytics through natural conversation.

Pydantic AI validates every Google Analytics 4 tool response against typed schemas, catching data inconsistencies at build time. Connect 12 tools through Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code. full type safety, structured output guarantees, and dependency injection for testable agents.

What you can do

  • Custom Reports — Run fully customizable GA4 reports with any combination of dimensions, metrics, and date ranges
  • Real-Time Analytics — Monitor active users and current page views in real time
  • Page Performance — Retrieve the top 25 pages ranked by views for any time period
  • Traffic Sources — Analyze session sources and mediums to understand where visitors come from
  • User Demographics — View user distribution by country for geographic insights
  • Device Breakdown — See user distribution across desktop, mobile, and tablet
  • Conversions — Track conversion events with counts and revenue data
  • Advanced Reporting — Run pivot reports and batch multiple reports in a single request
  • Metadata & Compatibility — List all available dimensions and metrics, and verify compatibility before building reports

The Google Analytics 4 MCP Server exposes 12 tools through the Vinkius. Connect it to Pydantic AI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 12 Google Analytics 4 tools available for Pydantic AI

When Pydantic AI connects to Google Analytics 4 through Vinkius, your AI agent gets direct access to every tool listed below — spanning web-analytics, event-tracking, conversion-analysis, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.

batch_run_reports

Batch run reports

check_compatibility

Check report compatibility

get_conversions

Get conversions

get_device_breakdown

Get device breakdown

get_metadata

Get available dimensions and metrics

get_page_views

Get top pages by views

get_traffic_sources

Get traffic sources

get_user_demographics

Get user demographics

list_audience_exports

List audience exports

run_pivot_report

Run pivot report

run_realtime_report

Run realtime report

run_report

Data JSON must include dateRanges, dimensions, and metrics arrays. Run a custom report

Connect Google Analytics 4 to Pydantic AI via MCP

Follow these steps to wire Google Analytics 4 into Pydantic AI. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.

01

Install Pydantic AI

Run pip install pydantic-ai
02

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token
03

Run the agent

Save to agent.py and run: python agent.py
04

Explore tools

The agent discovers 12 tools from Google Analytics 4 with type-safe schemas

Why Use Pydantic AI with the Google Analytics 4 MCP Server

Pydantic AI provides unique advantages when paired with Google Analytics 4 through the Model Context Protocol.

01

Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application

02

Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your Google Analytics 4 integration code

03

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

04

Dependency injection system cleanly separates your Google Analytics 4 connection logic from agent behavior for testable, maintainable code

Google Analytics 4 + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the Google Analytics 4 MCP Server delivers measurable value.

01

Type-safe data pipelines: query Google Analytics 4 with guaranteed response schemas, feeding validated data into downstream processing

02

API orchestration: chain multiple Google Analytics 4 tool calls with Pydantic validation at each step to ensure data integrity end-to-end

03

Production monitoring: build validated alert agents that query Google Analytics 4 and output structured, schema-compliant notifications

04

Testing and QA: use Pydantic AI's dependency injection to mock Google Analytics 4 responses and write comprehensive agent tests

Example Prompts for Google Analytics 4 in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with Google Analytics 4 immediately.

01

"Show me the top 10 pages by views this month and where the traffic is coming from."

02

"How many conversions did we get this week and which pages drove them?"

03

"What devices are our users on and which countries are generating the most traffic?"

Troubleshooting Google Analytics 4 MCP Server with Pydantic AI

Common issues when connecting Google Analytics 4 to Pydantic AI through the Vinkius, and how to resolve them.

01

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Google Analytics 4 + Pydantic AI FAQ

Common questions about integrating Google Analytics 4 MCP Server with Pydantic AI.

01

How does Pydantic AI discover MCP tools?

Create an MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.
02

Does Pydantic AI validate MCP tool responses?

Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.
03

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer. your Google Analytics 4 MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.