google-analytics-mcp

google-analytics-mcp

Connects to Google Analytics 4 to run reports, manage configurations, and retrieve admin data using natural language.

Category
Visit Server

README

Google Analytics (GA4) MCP Server

An MCP server that connects an MCP client (Claude Desktop, etc.) to Google Analytics 4. You log into your Google account once; after that every tool reports on the GA4 properties that login can access.

Built with the official google-analytics-data and google-analytics-admin Python clients and FastMCP. Reporting, intelligence, charts, admin reads, and write/management tools (creating/updating key events, custom dimensions/metrics, and data streams).

Simpler than the Google Ads server: GA4 needs no developer token — just an OAuth client and your login.


Tools (45)

Reporting

Tool Purpose
ga4_run_report Core report: metrics, dimensions, date range, filters, export to CSV/XLSX
ga4_compare_periods Compare a current vs previous period with % change
ga4_run_pivot_report Cross-tabulate dimensions (rows × columns)
ga4_run_cohort_report Retention by acquisition cohort (daily/weekly/monthly)
ga4_run_funnel_report Step-by-step funnel completion / drop-off
ga4_run_realtime_report Realtime activity (last ~30 min)
ga4_check_compatibility Which metrics + dimensions can be queried together
ga4_get_metadata Discover valid metric & dimension names
ga4_batch_run_reports Run up to 5 reports in one batched call
ga4_property_overview One-call snapshot: totals, top channels & pages, devices, new vs returning

Preset shortcuts (zero-config reports)

Tool Purpose
ga4_top_pages Top pages by views
ga4_traffic_by_channel Sessions & users by default channel group
ga4_conversions_summary Conversions by event name
ga4_trend A single metric over time (daily/weekly/monthly)

Accounts & configuration (admin reads)

Tool Purpose
ga4_list_account_summaries Accounts + their properties (find property IDs)
ga4_list_properties Properties under an account
ga4_list_data_streams Data streams (web measurement ID, app streams)
ga4_list_custom_dimensions Custom dimensions on a property
ga4_list_custom_metrics Custom metrics on a property
ga4_list_key_events Key events (conversions)
ga4_list_audiences Audiences
ga4_list_google_ads_links Linked Google Ads accounts
ga4_get_data_retention_settings Event-data retention settings
ga4_search_change_history Who changed what, and when
ga4_list_channel_groups Channel groups and their grouping rules

Audience export (pull the actual users in an audience — async create → query)

Tool Purpose
ga4_create_audience_export Start an export for an audience (waits for it to finish)
ga4_list_audience_exports List exports and their state (CREATING/ACTIVE)
ga4_query_audience_export Read the exported user rows

Intelligence

Tool Purpose
ga4_what_changed Top gainers/losers driving a metric's change between two periods
ga4_detect_anomalies Flag days a metric deviated from its baseline (z-score)
ga4_forecast_metric Project a metric forward with a linear trend

Charts — ga4_chart_report: render a bar/line PNG of a metric by a dimension (saved to exports/).

More admin reads

Tool Purpose
ga4_list_access_bindings Who has access (and roles) to an account/property
ga4_list_bigquery_links BigQuery export links
ga4_list_firebase_links Firebase project links
ga4_list_measurement_protocol_secrets MP secrets for a data stream
ga4_get_property_details Full property settings (industry, tz, currency, tier)
ga4_get_enhanced_measurement_settings Enhanced-measurement toggles for a stream

Write / management ⚠️ these modify your GA4 configuration

Tool Purpose
ga4_create_key_event / ga4_update_key_event Create / update a key event (conversion)
ga4_create_custom_dimension / ga4_update_custom_dimension Create / update a custom dimension
ga4_create_custom_metric / ga4_update_custom_metric Create / update a custom metric
ga4_create_data_stream Create a web data stream (returns its measurement ID)

Filtering (in ga4_run_report)

Pass dimension_filters / metric_filters — a list of conditions. Set filter_logic to AND (default) or OR; set negate: true on a condition for NOT. Each condition has field, operator, and value (or values for IN_LIST, or value + value_to for BETWEEN):

  • String operators: EXACT, CONTAINS, BEGINS_WITH, ENDS_WITH, REGEXP, IN_LIST
  • Numeric operators (metrics): EQUAL, LESS_THAN, LESS_EQUAL, GREATER_THAN, GREATER_EQUAL, BETWEEN

Example: country is India and sessions > 100 → dimension filter country EXACT India plus metric filter sessions GREATER_THAN 100.

More ga4_run_report options

  • Sort by dimension: order_by_dimension (+ order_desc: false for ascending) — e.g. chronological by date.
  • Totals: include_totals: true appends a totals row (and computes min/max).
  • Metadata: results note the currency, time zone, and warn if data is sampled or thresholded.

Export

Set export_path on ga4_run_report (e.g. report.csv or report.xlsx). Bare filenames are written to an exports/ folder next to the server. CSV works out of the box; XLSX needs openpyxl (already in requirements.txt).


Setup

0. Requirements

  • Python 3.9+
  • A GA4 property and a Google account with at least Viewer access to it.

1. Install dependencies

cd google-analytics-mcp
python -m pip install -r requirements.txt

2. Create an OAuth client (Desktop app)

In Google Cloud Console:

  1. Create/select a project.
  2. APIs & Services → Library → enable both Google Analytics Data API and Google Analytics Admin API.
  3. APIs & Services → Credentials → Create credentials → OAuth client ID.
  4. Application type: Desktop app. Copy the client ID and client secret. (If the OAuth consent screen is in "Testing", add your Google account as a Test user.)

3. Log in to get your refresh token

python get_refresh_token.py

A browser opens — choose the Google account with access to your GA4 property and approve. The script writes the client ID/secret + refresh token into .env.

4. Fill in .env

cp .env.example .env   # Windows: copy .env.example .env

Required:

GOOGLE_ANALYTICS_CLIENT_ID=...        # from step 2 (also written by step 3)
GOOGLE_ANALYTICS_CLIENT_SECRET=...    # from step 2 (also written by step 3)
GOOGLE_ANALYTICS_REFRESH_TOKEN=...    # from step 3
# Optional convenience:
GOOGLE_ANALYTICS_DEFAULT_PROPERTY_ID=...   # numeric, e.g. 123456789

Find your Property ID in GA4: Admin → Property Settings → Property ID (a number like 123456789).

5. Smoke-test

python -c "import server; print('server imports OK')"

Then verify credentials end-to-end (lists your accounts/properties):

python -c "import asyncio, server; from server import AccountSummariesInput; \
print(asyncio.run(server.ga4_list_account_summaries(AccountSummariesInput())))"

6. Connect to Claude Desktop

Edit claude_desktop_config.json (macOS: ~/Library/Application Support/Claude/, Windows: %APPDATA%\Claude\) — use the absolute path to server.py:

{
  "mcpServers": {
    "google-analytics": {
      "command": "python",
      "args": ["/ABSOLUTE/PATH/TO/google-analytics-mcp/server.py"]
    }
  }
}

The server reads .env from its own folder, so no secrets go in this config. Restart Claude Desktop.


Example prompts

  • "List my GA4 accounts and properties."
  • "Run a GA4 report of sessions and active users by country for the last 28 days."
  • "Show screenPageViews by pagePath for last 7 days, top 20 by views."
  • "What metrics and dimensions are available on property 123456789?"
  • "How many active users are on the site right now, by country?"
  • "Compare sessions and conversions for the last 28 days vs the prior 28 days."
  • "Sessions from India only where sessions > 100, by city." (uses filters)
  • "Export last month's traffic by channel to channel.xlsx."
  • "Build a funnel: session_start → view_item → add_to_cart → purchase."
  • "Weekly retention cohorts for the last 6 weeks."
  • "Pivot sessions by country (rows) and device category (columns)."

Common GA4 names

  • Metrics: activeUsers, sessions, screenPageViews, conversions, totalRevenue, engagementRate, bounceRate, averageSessionDuration.
  • Dimensions: date, country, city, deviceCategory, pagePath, sessionDefaultChannelGroup, firstUserSource, eventName.

Use ga4_get_metadata to see everything (including custom fields) for a property.


Troubleshooting

Symptom Fix
Missing Google Analytics credentials: ... Fill the named vars in .env.
invalid_grant / RefreshError Refresh token expired/revoked — re-run get_refresh_token.py.
Permission denied The login lacks access to that property, or the Data/Admin APIs aren't enabled in your Cloud project.
Not found Check the numeric property_id (Admin → Property Settings).
Invalid request Check metric/dimension names (ga4_get_metadata) and date formats (YYYY-MM-DD or NdaysAgo).

Security

  • .env holds secrets and is git-ignored — never commit it.
  • Scopes: analytics.readonly (reporting + config reads), analytics.edit (config writes — the create/update tools), and analytics.manage.users.readonly (reading access bindings). The edit scope lets the server change GA4 configuration, so treat the refresh token accordingly. After changing scopes you must re-run get_refresh_token.py and re-consent.

Project layout

google-analytics-mcp/
├── server.py             # FastMCP server + 6 tools
├── ga_client.py          # credentials, client factories, error handling
├── get_refresh_token.py  # one-time OAuth login -> refresh token
├── requirements.txt
├── .env.example          # copy to .env and fill in
├── .gitignore
└── README.md

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured