ShortlistFirst-party MCP

Google Analytics

by github:googleanalytics

Updated October 21, 2026

Data & DatabasesMedia & MarketingSoftware & Technology

MCP100 verdict

Not currently recommended. Official read-only Google Analytics MCP server for retrieving Analytics reporting and property context. Capabilities: Query supported Google Analytics reporting data; Inspect supported Analytics properties/metadata; Use Analytics data in AI-assisted analysis

MCP100 Assessment

Editorial verdict

Official read-only Google Analytics MCP server for retrieving Analytics reporting and property context. Capabilities: Query supported Google Analytics reporting data; Inspect supported Analytics properties/metadata; Use Analytics data in AI-assisted analysis

Reviewed October 21, 2026

Task Fit

Mapped

Working with structured data

Trust

Status warning

maintenance_source_health; client_coverage; tool_contract; install_supply_chain; advisory_freshness; adoption_evidence_presence

Maintenance

Date unavailable

No dated repository or package update is currently stored.

Popularity

Signals available

Visible usage signals are shown for discovery only, not as proof of safety.

Best for

Analytics teams that need read-only Google Analytics reporting/context inside MCP-capable AI workflows.

Not ideal for

Users who expect the MCP to change Google Analytics property/admin settings.

Avoid if

Do not grant broader Google credentials than the read scopes/account access required for the intended Analytics properties.

Trade-offs

Promising signal, but it ranks below the current Recommended/Shortlist admission cohort on maturity, uniqueness, publisher trust, security clarity, or MCP-native evidence.

Evidence scope

Evidence

Current source snapshot

Popularity

3.5k MCP repository stars

61,755 package downloads · PyPI Stats last_month · Third-party

Repository identity: googleanalytics/google-analytics-mcp

Package identity: analytics-mcp

PyPI Stats last_month · third-party estimate
Package evidence: exact. Exact current MCP implementation/distribution. Canonical package is analytics-mcp. Do not confuse it with unrelated similarly named packages.
Observed 2026-10-21; source: https://pypistats.org/api/packages/analytics-mcp/recent

Stars observed October 21, 2026 · Downloads observed October 21, 2026

Repository evidence: exact. Exact current MCP implementation/distribution. Canonical package is analytics-mcp. Do not confuse it with unrelated similarly named packages.

Package evidence: exact. Exact current MCP implementation/distribution. Canonical package is analytics-mcp. Do not confuse it with unrelated similarly named packages.

Maintenance

Publisher activity observed October 21, 2026

Current source snapshot

Trust review

Source relationship: First-party MCP

Reviewed October 21, 2026

Sources

GitHub repository ↗Official documentation ↗Package registry ↗

Supporting evidence (1)

Evidence source ↗

Evidence-backed setup

Install & Agents

Choose your MCP client. A client connects to the MCP server; the language model is selected inside that client. Only stored, source-backed configurations are shown.

Claude Code

Transport not recorded

Publisher documented

Enable the Google Analytics Admin API and Data API, configure ADC with the Analytics read-only scope, then add the server in Claude Code with `pipx run analytics-mcp` plus `GOOGLE_APPLICATION_CREDENTIALS` and `GOOGLE_PROJECT_ID` as documented by Google.

The publisher provides client-specific setup instructions.

Verify safely: Confirm the MCP client lists `analytics-mcp`; Google documents `/mcp` in its client setup/try-it-out flow. Claude Code can additionally use `claude mcp list`.

Uninstall and revoke

Claude Code: `claude mcp remove <name>`; also revoke OAuth/device/API credentials in the vendor account when the vendor provides such a control.

Evidence & methodology

Publisher-documented setup is not the same as MCP100 execution testing. “MCP100 logic checked” means the stored configuration shape was reviewed, not that third-party MCP software was run.

Evidence checked 2026-09-20T00:00:00.000Z

Evidence 1 ↗

Reviewed setup

Type-appropriate, source-backed setup for this mcp server profile.

Setup notes: Source rechecked October 21, 2026: Official Google Analytics MCP server. Lifecycle: current experimental beta. Canonical package is analytics-mcp. Do not confuse it with unrelated similarly named packages.

Read additional publisher installation details

From the publisher README

Publisher installation details

Original client setup and configuration retained from the publisher documentation.

View original README ↗

Publisher-documented clients

Claude CodeGemini CLI

These names appear in the publisher's installation documentation. MCP100-verified configurations are shown separately above when available.

Setup instructions 🔧

✨ Watch the Google Analytics MCP Setup Tutorial on YouTube for a step-by-step walkthrough of these instructions.

Setup involves the following steps:

Configure Python.
Configure credentials for Google Analytics.
Configure Gemini.

Configure Python 🐍

Install pipx.

Enable APIs in your project ✅

Follow the instructions to enable the following APIs in your Google Cloud project:

Configure credentials 🔑

Configure your Application Default Credentials (ADC). Make sure the credentials are for a user with access to your Google Analytics accounts or properties.

Credentials must include the Google Analytics read-only scope:

https://www.googleapis.com/auth/analytics.readonly

If you plan to enable write tools (such as create_property_annotation) using the --allow-write flag, your credentials must also include the edit scope:

https://www.googleapis.com/auth/analytics.edit

Check out Manage OAuth Clients for how to create an OAuth client.

Here are some sample gcloud commands you might find useful:

Set up ADC using user credentials and an OAuth desktop or web client after downloading the client JSON to YOUR_CLIENT_JSON_FILE.

gcloud auth application-default login \
  --scopes https://www.googleapis.com/auth/analytics.readonly,https://www.googleapis.com/auth/cloud-platform \
  --client-id-file=YOUR_CLIENT_JSON_FILE

Set up ADC using service account impersonation.

gcloud auth application-default login \
  --impersonate-service-account=SERVICE_ACCOUNT_EMAIL \
  --scopes=https://www.googleapis.com/auth/analytics.readonly,https://www.googleapis.com/auth/cloud-platform

When the gcloud auth application-default command completes, copy the PATH_TO_CREDENTIALS_JSON file location printed to the console in the following message. You'll need this for the next step!

Credentials saved to file: [PATH_TO_CREDENTIALS_JSON]

Configure Gemini

Install Gemini CLI or Gemini Code Assist.
Create or edit the file at ~/.gemini/settings.json, adding your server to the mcpServers list.

Replace PATH_TO_CREDENTIALS_JSON with the path you copied in the previous step.

We also recommend that you add a GOOGLE_CLOUD_PROJECT attribute to the env object. Replace YOUR_PROJECT_ID in the following example with the project ID of your Google Cloud project.
```
{
  "mcpServers": {
    "analytics-mcp": {
      "command": "pipx",
      "args": ["run", "analytics-mcp"],
      "env": {
        "GOOGLE_APPLICATION_CREDENTIALS": "PATH_TO_CREDENTIALS_JSON",
        "GOOGLE_CLOUD_PROJECT": "YOUR_PROJECT_ID"
      }
    }
  }
}
```
To enable write tools (e.g. create_property_annotation), append "--allow-write" to "args": ["run", "analytics-mcp", "--allow-write"].

Configure Claude Code

Add the MCP server with the following command:

Replace PATH_TO_CREDENTIALS_JSON with the path you copied in the previous step, and replace YOUR_PROJECT_ID with the project ID of your Google Cloud project.
```
claude mcp add analytics-mcp \
  --scope user \
  -e "GOOGLE_APPLICATION_CREDENTIALS=PATH_TO_CREDENTIALS_JSON" \
  -e "GOOGLE_CLOUD_PROJECT=YOUR_PROJECT_ID" \
  -- pipx run analytics-mcp
```

Loading optional publisher installation details…

Show source-catalog configuration

Enable the Google Analytics Admin API and Data API, configure ADC with the Analytics read-only scope, then add the server in Claude Code with `pipx run analytics-mcp` plus `GOOGLE_APPLICATION_CREDENTIALS` and `GOOGLE_PROJECT_ID` as documented by Google.

Read publisher documentation

Publisher documentation

Publisher README

Original product, capability, tool, and usage documentation from the MCP publisher. Installation sections appear under Install & Agents.

View original README ↗

Google Analytics MCP Server

This repo contains the source code for running a local MCP server that interacts with APIs for Google Analytics.

Join the discussion and ask questions in the 🤖-analytics-mcp channel on Discord.

Tools 🛠️

The server uses the Google Analytics Admin API and Google Analytics Data API to provide several Tools for use with LLMs.

Retrieve account and property information 🟠

get_account_summaries: Retrieves information about the user's Google Analytics accounts and properties.
get_property_details: Returns details about a property.
list_google_ads_links: Returns a list of links to Google Ads accounts for a property.
list_property_annotations: Returns annotations for a property.
create_property_annotation: Creates an annotation for a property (requires passing the --allow-write flag and the analytics.edit scope).

Run core reports 📙

run_report: Runs a Google Analytics report using the Data API.
run_funnel_report: Runs a Google Analytics funnel report using the Data API.
get_custom_dimensions_and_metrics: Retrieves the custom dimensions and metrics for a specific property.

Run realtime reports ⏳

run_realtime_report: Runs a Google Analytics realtime report using the Data API.

Multi-tenant HTTP & End-User OAuth 🌐

To host analytics-mcp as a shared multi-tenant HTTP service (where each end user signs in with their own Google account via OAuth 2.0 rather than using server-side Application Default Credentials), start the server with --transport http:

pipx run analytics-mcp \
  --transport http --stateless-http --host 0.0.0.0 --port 8080

Agent Framework OAuth (e.g. Google ADK): Configure per-user Google OAuth on McpToolset so end users are automatically prompted with a Sign in button in the chat UI, and can even combine Google Analytics MCP alongside other MCP servers in the same agent. Paired with --stateless-http, this mode is completely stateless and horizontally scalable across multiple replicas.
Native MCP OAuth 2.1 Server (--oauth): Pass --oauth (with GOOGLE_OAUTH_CLIENT_ID, GOOGLE_OAUTH_CLIENT_SECRET, and optional ANALYTICS_MCP_ISSUER_URL set) to enable the built-in MCP OAuth 2.1 Authorization Server:
```
export GOOGLE_OAUTH_CLIENT_ID="your-client-id.apps.googleusercontent.com"
export GOOGLE_OAUTH_CLIENT_SECRET="your-client-secret"
export ANALYTICS_MCP_ISSUER_URL="https://analytics-mcp.yourdomain.com"

pipx run analytics-mcp \
  --transport http --stateless-http --oauth --host 0.0.0.0 --port 8080
```
Note: The built-in --oauth provider stores dynamic client registrations, pending authorization state, and refresh tokens in process memory (run as a single instance or with sticky sessions; restarts require re-authentication).

See the complete walkthrough, Dockerfile, and runnable agent code in examples/multi_tenant_adk_agent/README.md.

Try it out 🥼

Launch Gemini Code Assist or Gemini CLI and type /mcp. You should see analytics-mcp listed in the results.

Here are some sample prompts to get you started:

Ask what the server can do:
```
what can the analytics-mcp server do?
```

Ask about a Google Analytics property

Give me details about my Google Analytics property with 'xyz' in the name

Prompt for analysis:

what are the most popular events in my Google Analytics property in the last 180 days?

Ask about signed-in users:

were most of my users in the last 6 months logged in?

Ask about property configuration:

what are the custom dimensions and custom metrics in my property?

Contributing ✨

Contributions welcome! See the Contributing Guide.

Troubleshooting

See the Troubleshooting Guide for common issues and workarounds.

Loading optional publisher documentation…

FAQ

Is this an official MCP?

github:googleanalytics is listed as First-party MCP in MCP100’s current evidence.

Current official resources:

Publisher documentation ↗

Google Analytics MCP Server

This repo contains the source code for running a local MCP server that interacts with APIs for Google Analytics.

Join the discussion and ask questions in the 🤖-analytics-mcp channel on Discord.

Tools 🛠️

The server uses the Google Analytics Admin API and Google Analytics Data API to provide several Tools for use with LLMs.

Retrieve account and property information 🟠

get_account_summaries: Retrieves information about the user's Google Analytics accounts and properties.
get_property_details: Returns details about a property.
list_google_ads_links: Returns a list of links to Google Ads accounts for a property.
list_property_annotations: Returns annotations for a property.
create_property_annotation: Creates an annotation for a property (requires passing the --allow-write flag and the analytics.edit scope).

Run core reports 📙

run_report: Runs a Google Analytics report using the Data API.
run_funnel_report: Runs a Google Analytics funnel report using the Data API.
get_custom_dimensions_and_metrics: Retrieves the custom dimensions and metrics for a specific property.

Run realtime reports ⏳

run_realtime_report: Runs a Google Analytics realtime report using the Data API.

Multi-tenant HTTP & End-User OAuth 🌐

pipx run analytics-mcp \
  --transport http --stateless-http --host 0.0.0.0 --port 8080

Agent Framework OAuth (e.g. Google ADK): Configure per-user Google OAuth on McpToolset so end users are automatically prompted with a Sign in button in the chat UI, and can even combine Google Analytics MCP alongside other MCP servers in the same agent. Paired with --stateless-http, this mode is completely stateless and horizontally scalable across multiple replicas.
Native MCP OAuth 2.1 Server (--oauth): Pass --oauth (with GOOGLE_OAUTH_CLIENT_ID, GOOGLE_OAUTH_CLIENT_SECRET, and optional ANALYTICS_MCP_ISSUER_URL set) to enable the built-in MCP OAuth 2.1 Authorization Server:
```
export GOOGLE_OAUTH_CLIENT_ID="your-client-id.apps.googleusercontent.com"
export GOOGLE_OAUTH_CLIENT_SECRET="your-client-secret"
export ANALYTICS_MCP_ISSUER_URL="https://analytics-mcp.yourdomain.com"

pipx run analytics-mcp \
  --transport http --stateless-http --oauth --host 0.0.0.0 --port 8080
```
Note: The built-in --oauth provider stores dynamic client registrations, pending authorization state, and refresh tokens in process memory (run as a single instance or with sticky sessions; restarts require re-authentication).

See the complete walkthrough, Dockerfile, and runnable agent code in examples/multi_tenant_adk_agent/README.md.

Try it out 🥼

Launch Gemini Code Assist or Gemini CLI and type /mcp. You should see analytics-mcp listed in the results.

Here are some sample prompts to get you started:

Ask what the server can do:
```
what can the analytics-mcp server do?
```

Ask about a Google Analytics property

Give me details about my Google Analytics property with 'xyz' in the name

Prompt for analysis:

what are the most popular events in my Google Analytics property in the last 180 days?

Ask about signed-in users:

were most of my users in the last 6 months logged in?

Ask about property configuration:

what are the custom dimensions and custom metrics in my property?

Contributing ✨

Contributions welcome! See the Contributing Guide.

Troubleshooting

See the Troubleshooting Guide for common issues and workarounds.

Official read-only Google Analytics MCP server for retrieving Analytics reporting and property context. Capabilities: Query supported Google Analytics reporting data; Inspect supported Analytics properties/metadata; Use Analytics data in AI-assisted analysis

Best for

Not ideal for

Avoid if

Trade-offs

Evidence

Popularity

Maintenance

Trust review

Sources

Install & Agents

Claude Code

Reviewed setup

Publisher installation details

Setup instructions 🔧

Configure Python 🐍

Enable APIs in your project ✅

Configure credentials 🔑

Configure Gemini

Configure Claude Code

What it does

Representative uses

Important limits

Context Footprint

Access & risk

Other options

Google MCP Toolbox for Databases

Redis MCP

Supabase MCP

Publisher README

Google Analytics MCP Server

Tools 🛠️

Retrieve account and property information 🟠

Run core reports 📙

Run realtime reports ⏳

Multi-tenant HTTP & End-User OAuth 🌐

Try it out 🥼

Contributing ✨

Troubleshooting

FAQ

Publisher installation details

Setup instructions 🔧

Configure Python 🐍

Enable APIs in your project ✅

Configure credentials 🔑

Configure Gemini

Configure Claude Code

Publisher README

Google Analytics MCP Server

Tools 🛠️

Retrieve account and property information 🟠

Run core reports 📙

Run realtime reports ⏳

Multi-tenant HTTP & End-User OAuth 🌐

Try it out 🥼

Contributing ✨

Troubleshooting