Google Analytics

Google Analytics

Google Analytics 4 (GA4) exposes two OAuth-authenticated APIs — the Data API for reporting and the Admin API for configuration — plus the Measurement Protocol for sending events. This connector wraps all three: run and explore analytics reports, discover the dimensions and metrics a property supports, walk the account → property tree, manage key events (conversions) and custom dimensions/metrics, and send server-side events. It is reporting-first — runReport is the core tool, with getMetadata and checkCompatibility underneath so you can compose a valid report without guessing field names.

Every property-scoped tool takes propertyId — the numeric GA4 property id (e.g. 123456), not the G-XXXXXXX measurement id. Resolve it once with listAccountSummaries.

Independent, unofficial connector for Google Analytics. Not affiliated with, endorsed by, or sponsored by Google Analytics. "Google Analytics" is a trademark of its owner, used only to identify the service this connector works with.

When to use this

• Reporting — run historical (runReport) or realtime (runRealtimeReport) reports, discover valid dimension/metric names (getMetadata), and check whether a field combination is valid (checkCompatibility).
• Navigation — find which property to operate on and read its configuration (listAccountSummaries, getProperty, listDataStreams).
• Key events (conversions) — list, get, create, and delete the events GA4 counts as conversions.
• Custom definitions — list, create, and archive custom dimensions and custom metrics.
• Measurement Protocol — manage a data stream's send secrets and send server-side events (listMeasurementProtocolSecrets, createMeasurementProtocolSecret, sendEvent).

Setup

This is an agentskills.io skill.

If the connector has not been installed as a skill yet, install it first with npx skills add zapier/connectors --skill google-analytics (or your harness's own skill-install mechanism), then continue here. Installing the skill copies these files, not dependencies. Before running the CLI, a local MCP server, or zapier-sdk auth commands, run npm install --omit=dev here once. Importing the published package as a dependency in your own project instead? That npm install already resolves everything — see references/use-as-sdk.md.

Want the actual repo source instead — to browse references/, run this connector's tests, or hack on it? See README.md for a scoped git clone.

The connector runs on Node.js 22.18+. Pick the reference that matches how you're running it, and load it before doing anything else:

Scripts

Every script uses the single google-analytics connection. Most take a numeric propertyId from listAccountSummaries.

Measurement Protocol secrets — create and list only. This connector can create and list Measurement Protocol secrets, but cannot delete or rotate them. To delete a secret, use the GA4 Admin UI: Admin → Data streams → (select stream) → Measurement Protocol API secrets.

Disambiguation & refusals

Resolving a property by name. Tools take a numeric propertyId, not a name. Resolve it with listAccountSummaries and count exact (case-insensitive) matches on propertySummaries[].displayName: exactly one match → use its propertyId and act; two or more that tie → stop, list the candidates with their propertyId (and parent account), and ask which one. Never silently pick. The same rule applies to resolving a keyEventId / customDimensionId / customMetricId / dataStreamId from the matching list* tool.

Unsupported operations — say so and stop; don't substitute another tool. This connector does not create or delete GA4 accounts or properties, manage user access/permissions, or read Universal Analytics (UA) data — and it exposes no funnel, pivot, cohort, or audience-export reports, and no audience or calculated-metric management. If asked for one of these, say it isn't supported rather than repurposing a different tool or reporting a success you didn't perform. (For a report the flat runReport can't express, say so — don't fake a pivot by post-processing rows.)

Auth

Every shape passes auth as one connection selector, not the secret — a [<resolver>:]<value> string. Every connector accepts zapier:<connection-id> (Zapier-managed auth — routes through Zapier's auth, retries, and governance layer); some also accept one or more direct-token resolvers (naming and count vary per connector) — check this connector's own resolvers rather than assuming. The <resolver>: prefix is optional; a bare value goes to the first resolver that claims it — a UUID-shaped bare value always claims zapier:. Each script declares the connections it needs and the resolvers each accepts. The exact syntax for passing a connection (and how to see this connector's resolver list) differs by shape — see the reference you loaded above.

Checking what's already configured first? Don't dump environment values to do it — env or env | grep <name> prints the value along with the name, leaking a live credential into the transcript if one is set. Check names only (env | cut -d= -f1 | grep -i <name>) or test a known name directly ([ -n "$VAR_NAME" ]).

No connection yet? Pick one — and follow the reference's own flow to obtain it; never just ask the user for a connection id or token as if they already have one memorized:

Output format

Every script returns a { data, meta } envelope:

• data — the script's result (the shape its outputSchema declares; see the reference you loaded above for how to inspect a script's exact schema in your shape).
• meta.outputDataValidation — what validating data did:
  • { skipped: false, droppedPaths: null } — validated, nothing removed.
  • { skipped: false, droppedPaths: [...], instruction } — validated, but those paths were stripped from data: fields the script returned from the API that the outputSchema doesn't declare. If you need them, re-run with output validation skipped.
  • { skipped: true } — validation was bypassed; data is the raw, unchecked script output.

Reading dropped fields / skipOutputDataValidation. To receive the raw, unvalidated result, opt out of output validation (the exact syntax differs by shape — see the reference you loaded above). Input validation is never skipped.

Trimming the result / filterOutputData. To shrink a large result down to the fields you need, pass a jq expression that post-processes data (again, exact syntax per shape). The jq runs against data only, NOT the { data, meta } envelope, so write it rooted at data (run the script's --help — or your shape's equivalent — to see its output schema). The transformed value replaces data, meta is preserved, and the result is NOT re-validated against the output schema.

References