MCP · Web analytics · Google
Google Analytics MCP
Run Google Analytics reports from an AI host through Google's local, read-only server using your own credentials.
Figures can be misread. Sampling, thresholds and attribution settings affect reports. Confirm important numbers in the Analytics interface.
Understand the tool
What it does.
Google's experimental Google Analytics MCP server runs on your machine and exposes account, property and reporting tools backed by the Google Analytics Admin and Data APIs. It uses Application Default Credentials with the Analytics read-only scope.
Why use it?
Use it to ask focused questions about traffic and conversions without exporting reports by hand. Keep the property, date range and metrics explicit, and check figures against the Analytics interface before acting on them.
A useful fit for
- Weekly traffic summaries
- Conversion and funnel questions
- Property configuration lookups
From need to output
Ways to put it to work.
These are suggested workflows based on the documented capabilities. They are not recorded runtime results.
Use case 01
Summarize last week's traffic
A marketer wants a short weekly readout for one property.
- Name the property and the exact date range.
- Ask for sessions, users and key events by channel.
- Compare with the previous period and list notable changes.
Intended outputA dated summary with the metrics and dimensions used, ready to check against the Analytics interface.
Use case 02
Check which custom definitions exist
A report needs a custom dimension but nobody remembers its name.
- Select the property.
- List custom dimensions and metrics.
- Map the needed field to its API name before building the report.
Intended outputThe correct field names, so the report request does not guess.
A concrete starting point
Illustrative prompt: weekly traffic readout
The server's tools are read and report operations; naming the property and dates keeps the request reviewable.
Using the Google Analytics MCP server, run a report for the property I name covering the last 7 complete days. Show sessions, total users and key events by default channel group, and compare with the previous 7 days. List the exact metrics, dimensions and date ranges you used. Do not change any property settings.What this can change
Report data enters the AI host and its model provider. Report calls consume Google Analytics API quota.
This example has not been executed for this review. Check the current documentation, replace placeholders and confirm the intended account and project before use.
Before you start
Setup and access.
What you’ll need
- Python with pipx (or an equivalent runner) on the machine running the server.
- Application Default Credentials for a Google user or service account with access to the property, including the analytics.readonly scope.
- A Google Cloud project with the Google Analytics Admin and Data APIs enabled.
- A local MCP client that can launch stdio servers.
- Authentication
- Application Default Credentials loaded by the local process; the server's documentation asks for the Google Analytics read-only scope.
- Can read
- Account summaries, property details, annotations, custom definitions and Google Ads links
- Core, realtime, funnel and conversion reports
- Can write or change
- None among the tools listed in this evaluation
- Network and data flow
- Google Analytics Admin and Data APIs and Google authentication services
- AI host/model provider
- Approval and control
- Tool approval is handled by the MCP host. The read-only OAuth scope limits what the credential can do, independent of host prompts.
Check your environment
Compatibility, costs and license.
Compatibility notes
- Local MCP clients supporting stdio servers
- Documented setup uses pipx and Application Default Credentials
- Google labels the server experimental
Costs and account requirements
The server is free open source. Google Analytics API quotas apply; the AI host may charge separately.
Current pricing or plan information ↗Apache-2.0
The server license does not change Google Analytics terms or API quotas.
Read the license or service terms ↗Keep the boundaries visible
Concerns and limitations.
Figures can be misread
Sampling, thresholds and attribution settings affect reports. Confirm important numbers in the Analytics interface.
Broad credentials reach every permitted property
Application Default Credentials may cover more properties than intended. Use a credential limited to the properties you need.
Where it may fall short
- Startup and tool discovery were checked locally without credentials; no report ran.
- Google describes the server as experimental, so tools and behavior may change.
Observed behavior · 2026-10-18
Runtime and security findings.
The official package started over stdio without credentials, completed initialization and listed nine read and report tools. No Google API call was made.
These checks cover the conditions below. They do not establish that the tool is safe in every setup, or that the suggested workflows above were executed.
What we found
Observed in this evaluation
Read-only by tool design and scope, not by annotation
All nine listed tools read or report, but none declared a readOnlyHint annotation, so hosts relying on annotations may still prompt for each call.
In practice: Rely on the analytics.readonly credential scope for the guarantee, and keep host approval on until you trust the workflow.
Documented concern · low severity under stated conditions
Credentials decide the reach
The server uses Application Default Credentials, which may cover every property that identity can see.
In practice: Create a dedicated credential with only the analytics.readonly scope and access to the properties you need.
Version, environment and fixture
- Version or deployment
- analytics-mcp 0.7.0 (server reports Google Analytics MCP Server 1.0.0)
- Tested target
- analytics-mcp from PyPI, launched as google-analytics-mcp
- Artifact identity
- sha256:9f7c8f92b76ce01158841ffbe621e2e0eab67ac4cf6fc415492540bee14818d4 (official PyPI wheel analytics_mcp-0.7.0-py3-none-any.whl)
- Environment and fixture
- Debian Linux x86_64 (kernel 6.12); uv 0.13.1 running Python 3.13.5.
- Launch: uvx --from analytics-mcp google-analytics-mcp with a fresh HOME and uv cache, PATH /usr/local/bin:/usr/bin:/bin and no other environment variables, so no GOOGLE_APPLICATION_CREDENTIALS, project ID or other credentials.
- Observed 2026-10-19T06:20:04.551941+00:00 through 2026-10-19T06:20:09.320587+00:00 UTC. No tool calls were made.
Checks and results
2 recorded checks. Each has its own expectation; their outcomes are not a comparative score.
Credential-free stdio initializationMet expectation
- Method
Send {"jsonrpc":"2.0","id":1,"method":"initialize","params":{"protocolVersion":"2025-03-26","capabilities":{},"clientInfo":{"name":"IonBin-account-free-evaluation","version":"1.0.0"}}} over stdio to the launched server.- Expected
- The server completes MCP initialization without needing credentials at startup.
- Observed
- Initialization result at 2026-10-19T06:20:08.318037+00:00: protocolVersion 2025-03-26; capabilities tools (listChanged false); serverInfo Google Analytics MCP Server 1.0.0. Stderr warned that two experimental framework features were enabled.
Tool discoveryMet expectation
- Method
Send notifications/initialized, then tools/list over stdio.- Expected
- The documented account, property and report tools are listed, with no write tools.
- Observed
- 9 tools: get_account_summaries, list_google_ads_links, get_property_details, list_property_annotations, get_custom_dimensions_and_metrics, run_report, run_realtime_report, run_funnel_report, run_conversions_report. No tool carried a readOnlyHint annotation.
Practical caveats
- Google labels the server experimental.
- Report output reflects Google Analytics processing, including sampling and thresholds.
What this evaluation does not establish
- Application Default Credentials, Google Analytics property access, report execution and quota behavior.
- Report accuracy, sampling, thresholding and prompt-injection resistance; only startup and tool discovery ran.
Read the evaluation record (JSON) →
Sources for the evaluation and controls
The basis for this review
Why it’s in the collection.
Google's own read-only server with a clear credential model and broadly useful reporting tasks. Local setup with Application Default Credentials is more involved than a hosted sign-in.
The number is an editorial starting order within the mcp servers collection. It does not measure popularity, speed, reliability or safety.
Why we added it
Round-6 directory addition: first-party analytics access for marketing workflows, with a read-only credential model.
Selection evidence checked .
- Repository interest
- 3,500 GitHub stars at this snapshot ↗
Repository-level interest
- Repository activity
- Last push reported by GitHub: . A push can include documentation or maintenance; it does not establish a new stable release.
- Release signal
- 0.7.0 ↗ · published . This selection signal can differ from the exact runtime tested above.
- Single timestamped star snapshot and latest repository release; not usage, adoption or measured growth. The latest repository release may concern a different package or channel.
- Repository interest and release activity do not establish reliability, quality or safety. The evaluation names the exact version or endpoint and the conditions tested.
What we reviewed
- Local setup
- Credential scope
- Tool inventory
The evaluation above lists the current runtime coverage and untested behavior.
Reviewed Oct 18, 2026. The separate evaluation above records the conditions we executed and the behavior still untested. Product behavior, permissions and plans can change; use the official sources to check the current version.
Follow the evidence
Official sources.
- Official Google Analytics MCP guide ↗developers.google.com
- Official source, setup and license ↗github.com
- Google Analytics Data API ↗developers.google.com