Field-by-field comparison

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MCPs in this comparison

Google AnalyticsGoogle MCP Toolbox for Databases

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Comparable alternatives

Azure MCP ServerMCP100 SelectedChrome DevTools MCPMCP100 SelectedContext7 MCPMCP100 SelectedGrafana Cloud MCPMCP100 SelectedGoogle Search Console MCP Server for SEOsMCP100 SelectedExcel MCP ServerMCP100 Selected

Shown only when capability or industry context overlaps.

Side-by-side MCP evidence comparison
Evidence field	Google AnalyticsWatchlist candidate	Google MCP Toolbox for DatabasesMCP100 Selected
Task fit
Best for	Analytics teams that need read-only Google Analytics reporting/context inside MCP-capable AI workflows.	Schema exploration and database-aware coding in development environments Connecting one MCP layer to supported Google Cloud and third-party databases Defining structured, parameterized database tools with integrated authentication and observability
Not ideal for	Users who expect the MCP to change Google Analytics property/admin settings.	Unrestricted natural-language SQL against production data Teams unwilling to operate and secure a local or hosted Toolbox process
Avoid when	Do not grant broader Google credentials than the read scopes/account access required for the intended Analytics properties.	The configured database user can modify production data or schema beyond the approved task Sensitive query results cannot be sent to the AI client Credentials would be committed in tools.yaml or MCP configuration
Provenance
Provenance details	First-party MCP github:googleanalytics · Publisher source ↗	First-party MCP Google · Publisher source ↗
Maintenance
Maintenance details	Stale Repo: Not documented Package: Not documented	Repo: Aug 14, 2026 Package: Aug 14, 2026
Popularity evidence
GitHub stars	Not documented	16,173 GitHub stars · checked 2026-08-14T18:46:26.000Z
Package downloads / 30 days	No reliable download data	61,660 package downloads / 30 days · checked 2026-08-14T18:46:26.000Z
External adoption evidence	Not documented	npm: package downloads: 61,660Exact attributable signal.npm: package downloads · Rolling 30 days · checked 2026-08-14T18:46:26.000ZEvidence source ↗
Client coverage
Client coverage details	Not documented	Claude Code✓ Local stdio Claude Desktop✓ Local stdio Codex✓ Local stdio VS Code✓ Local stdio Cursor✓ Local stdio OpenCode✓ Local stdio
Client coverage note	Local stdio runs on your computer. Streamable HTTP connects to a remotely hosted MCP server.
Access and data
Authentication	Uses Google authentication/credentials documented by the official server; exact credential flow must be bound from current official/local evidence.	Authentication depends on the database source and can include database username/password, Google Cloud IAM, or other source-specific mechanisms. Use a dedicated read-only identity and secret manager or protected environment variables.
Cost	Google Analytics/API quotas and model/provider costs apply; no extra MCP entitlement should be inferred without publisher evidence.	The Apache-licensed Toolbox and npm server have no documented MCP usage fee. Database services, Google Cloud resources, network transfer, observability backends, hosting, and the AI client may incur normal charges.
Permissions	Read-only according to current Google Analytics MCP documentation; it does not edit Analytics settings.	Effective permissions come from each configured database identity and the enabled prebuilt or custom tools. Generic prebuilt sets can include schema discovery and execute_sql; custom tools can constrain statements, parameters, and accessible sources.
Data handling	Analytics reporting/property data can be shared with the connected AI client/provider.	The Toolbox process connects directly to configured databases and returns selected schemas, rows, query results, and errors to the MCP client. Credentials may be supplied through environment variables or configuration; integrated cloud authentication and OpenTelemetry are available.
Limitations
Tradeoffs	Promising signal, but it ranks below the current Selected/Watchlist admission cohort on maturity, uniqueness, publisher trust, security clarity, or MCP-native evidence.	Prebuilt tools are quick to adopt but may expose generic execute_sql capability; custom tools require more design but provide a narrower contract. The npx path is convenient but the publisher recommends binary or container installation for standard reliable deployments. Supporting many database engines increases configuration flexibility and operational complexity.
Risk context	Main concerns are analytics-data confidentiality and credential scoping; the reviewed server is not a write/admin surface.	Generic SQL tools can expose or mutate large amounts of data and retrieved database text can carry prompt-injection content. Prefer a non-production replica, read-only credentials, allow-listed custom parameterized tools, query limits, audit logs, and no secrets in config. This review does not claim MCP100 execution testing.
Evidence date
Editorial review	2026-09-13T00:00:00Z	2026-07-24
Candidate evidence	2026-09-13T00:00:00Z	2026-08-14T18:46:26.000Z

Popularity, maintenance, fit, permissions, and client support are independent evidence fields.

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