Score breakdown
Popularity is tracked separately. Support, ads, sponsorships, and tips never affect these signals.
Why it matters
Most marketers / growth analysts / product managers today who want an AI agent (Gemini CLI / Claude Code / Cursor / Windsurf) to query Google Analytics have been either (a) writing custom google-analytics-admin + google-analytics-data wrappers by hand (no canonical MCP surface), (b) reaching for non-MCP analytics libraries that require custom agent integration, or (c) asking the agent to hallucina
Who should use it
Who should skip it
Skip Analytics MCP: Official Google Analytics MCP Server from the `googleanalytics` GitHub Org (13+ MCP Tools, Apache-2.0) if the source repository or demo is inactive, unmaintained, or no longer matches the description shown here.
About this signal
Analytics MCP: Official Google Analytics MCP Server from the `googleanalytics` GitHub Org (13+ MCP Tools, Apache-2.0) is tracked by RepoRadar as a tool in the Radar section. It was first seen on 2026-07-08 and last updated on 2026-07-08. The current verdict is 'try now' with a Gold tier and moderate setup difficulty. Analytics MCP: Official Google Analytics MCP Server from the `googleanalytics` GitHub Org (13+ MCP Tools, Apache-2.0) leads on workflow potential (9.7) and practical usefulness (9.0); its lowest signal is setup ease (6.4), so factor that in before investing setup time. This page summarizes the evidence RepoRadar has captured from captured source metadata. The score, tier, risk label, and verdict on this page are never influenced by sponsorship, ads, or tips — they reflect only the usefulness, popularity, novelty, momentum, maturity, and evidence signals described in the RepoRadar methodology.
How this item is evaluated
RepoRadar assigned Analytics MCP: Official Google Analytics MCP Server from the `googleanalytics` GitHub Org (13+ MCP Tools, Apache-2.0) a composite score of 8.6 out of 10, placing it in the Gold tier. This score combines weighted sub-signals: usefulness (35%), novelty (18%), momentum (14%), maturity (10%), open-source/build quality (7%), evidence quality (6%), workflow potential (6%), and setup ease (4%). Popularity is tracked separately at 0.0 and never affects the composite score or tier. The risk label of 'low' reflects inherent user-impacting hazards, not generic novelty. Items with no risk flag may still require normal code review before production use.
Putting this into practice? Read How to vet an AI agent or MCP server before you wire it in for the checklist behind this score.
Risk explanation
The 2; 604* / 575-fork / 75-subscriber repo is at active maintenance but the consumer SHOULD note the multi-step setup path: (1) Google Cloud project with Analytics Admin API + Analytics Data API enabled; (2) OAuth client credentials with the `analytics.readonly` scope; (3) `gcloud auth application-default login` to wire the credentials file.
