Connect Google Analytics 4 to Claude Desktop with an MCP Server – A Complete Guide

Perfect for non-coders, marketers, analysts, and founders who want to integrate GA4 insights into Claude Desktop using a Python-powered MCP server — all locally and securely.

What is an MCP Server?

MCP (Model Context Protocol) servers allow AI tools like Claude to interact with real-world data and tools via a standard protocol. Think of it like a bridge between your local data (like GA4 or Shopify) and Claude’s chat interface — so Claude can ask for data and act on it using well-defined tools, all running securely on your machine.

If you want to know more about How Marketers can use  MCP servers, here’s a detailed guide, The End-to-End Model Context Protocol (MCP) Guide for Marketers

What You’ll Achieve

• Pull GA4 reports via Claude (e.g., “Show traffic for the last 7 days”)
• Run everything locally (no cloud or third-party hosting)
• Use Claude as a smart assistant connected to your actual GA4 data

Tools You’ll Need 🛠️

If you find the setup too technical, feel free to reach out to us for help. 

Step 1: Install Python + Add to PATH

1. Download Python from: https://www.python.org/downloads
2. Run the installer
3. Important: ✅ Check “Add Python to PATH”
4. Click Install Now

To confirm it’s installed:

Open your command line:

• Windows: Press Win + R, type cmd, and press Enter
• macOS: Press Cmd + Space, type Terminal, and hit Enter
• Linux: Press Ctrl + Alt + T, or open Terminal from your applications menu

Then run this text below:

python --version

If installed correctly, you should see it return something like: Python 3.10.13

( Note: the number next to python might differ based on the version you have downloaded )

Step 2: Download the GA4 MCP Project

Option A: Clone with Git (Recommended)

git clone <https://github.com/smacient/mcp-ga4.git>
cd mcp-ga4

Option B: Download ZIP

• Visit: https://github.com/smacient/mcp-ga4
• Click Code → Download ZIP
• Extract to a folder (e.g., Documents/mcp-ga4)

Step 3: Set Up Python Virtual Environment

1. Open Command Prompt (CMD)
2. Navigate to the project folder:

cd C : \\Users\\YourName\\Documents\\mcp-ga4\\mcp-ga4-main

1. Create a virtual environment by using the line below:

python -m venv .venv

2. Activate it:

.venv\\Scripts\\activate

Your CMD should now show: (.venv) before the prompt

Step 4: Install MCP + Dependencies

Inside the same activated terminal:

pip install uv
uv sync

You should see a lot of dependencies being downloaded, and the sync would have given

Step 5: Get Your GA4 Credentials

Getting your credentials is the only step where you’ll need to log into the Google Cloud Console. Follow this carefully — it’s easier than it sounds!

1. Visit https://console.cloud.google.com and log in with your Google account.
2. Click “Select a project” (top menu) → “New Project”, and give it a name like “Claude GA4 MCP”
3. After it’s created, click “APIs & Services → Library” in the sidebar
4. Search for “Google Analytics Data API”, click it, and press Enable
5. Next, go to “Credentials” in the sidebar
6. Click “Create Credentials → Service Account”, and fill in a name like “Claude GA4 Bot”
7. Skip roles/permissions for now (you can click Done)
8. After creation, click into your new service account → Go to the “Keys” tab → Click “Add Key → Create New Key” → Choose JSON and download the file
9. Rename this downloaded file to credentials.json
10. Move this file into the main folder of your project (where ga4_server.py is located)
11. Then in your Google Analytics property settings, share access with the email address shown in the JSON file (it ends with @<project>.iam.gserviceaccount.com) and give it Viewer or Analyst access

Step 6: Add a .env File

1. Open the mcp-ga4-main folder where you extracted or cloned the project.
2. Go inside the localserver folder.
3. Right-click in the folder → choose New → Text Document → name it exactly .env (delete the .txt extension if it appears).
4. Open this file and paste the following line:

GOOGLE_APPLICATION_CREDENTIALS=C:\\Users\\YourName\\Documents\\mcp-ga4\\mcp-ga4-main\\credentials.json

Tip: On Windows, this line works as-is. You don’t need to double the slashes like you would in Python scripts.

Step 7: Install the Server into Claude

Run this in your terminal (with the virtual env still active):

uv run mcp install localserver/ga4_server.py

This registers the server with Claude Desktop.

Step 8: Configure Claude Desktop

Open Claude → Settings → Developer → Edit Config

1. A folder will open and Add this script below inside claude.json under “mcpServers”:

Step 9 : Ask Claude!

( Pro Tip : After saving the claude.json document, close Claude completely. Make sure you remove any instance of Claude running. You can use the task manager to ensure this. )

Launch Claude Desktop and ask:

Get a GA4 report for the last 7 days.

“Google Analytics 4”: {
  “command”: “uv”,
  “args”: [
    “run”,
    “–with”,
    “mcp[cli]”,
    “mcp”,
    “run”,
    “C:\\Users\\YourName\\Documents\\mcp-ga4\\mcp-ga4-main\\localserver\\ga4_server.py”
  ],
  “env”: {
    “VIRTUAL_ENV”: “C:\\Users\\YourName\\Documents\\mcp-ga4\\mcp-ga4-main\\.venv”,
    “PATH”: “C:\\Users\\YourName\\Documents\\mcp-ga4\\mcp-ga4-main\\.venv\\Scripts;${PATH}”,
    “GOOGLE_APPLICATION_CREDENTIALS”: “C:\\Users\\YourName\\Documents\\mcp-ga4\\mcp-ga4-main\\credentials.json”
  }
}

Claude will:

• Detect the GA4 MCP server
• Ask for permission to use it
• Fetch your data using tools like get_report, compare_report_metrics, etc.

Troubleshooting Tips

❌ No tools visible in Claude? → Double-check your claude.json paths and restart Claude

❌ Env not loaded? → Confirm .env is in the right folder and dotenv.config() is in the script

❌ Permission error from GA4? → Make sure your service account has correct GA4 access in GA settings

That’s It!

You now have a fully running local Python-powered GA4 analytics server talking to Claude. Secure, private, and easy to modify — no cloud hosting required.

Check out our other blogs for more information on MCP servers and various other tools that will end up making your life easy:

• The End-to-End Model Context Protocol (MCP) Guide for Marketers
• Top AI Tool Libraries To Find the Best AI Tools
• Notebook LM: A Guide with Use Cases and Examples

FAQs

1. What is an MCP Server, and how does it support GA4 integration with Claude Desktop?

The Model Context Protocol (MCP) Server acts as a bridge between Google Analytics 4 and Claude Desktop, enabling seamless context-aware data flow for enhanced tracking and analysis.

2. Do I need coding experience to connect GA4 with Claude Desktop via MCP Server?

 Not necessarily. While basic familiarity with APIs and configuration files is helpful, this guide breaks down the integration steps in a user-friendly, non-technical manner.

3. What kind of data can I expect to see in Claude Desktop after integrating GA4?

You’ll be able to access behavioral insights, user events, traffic sources, and engagement metrics, all contextualised within Claude Desktop’s AI-driven interface.

4. Is this setup secure and compliant with data privacy regulations?

Yes, when configured properly, the integration follows GA4’s data privacy standards and MCP’s secure data transfer protocols, ensuring compliance with GDPR and similar regulations.