What is Measure Tracking QA MCP?

Measurement is a hand-off chain: analytics writes a guide → developers implement the dataLayer → analytics validates it → GTM sends events → GA4 collects them → someone audits quality and documents the gaps. This MCP automates and assists that whole flow. It reads your implementation guide, opens the real site, compares what fires against what was specified, and produces a QA report, a developer checklist, a stakeholder summary and a Tracking Coverage Score.

"Read this tracking guide and validate if it is complete."
"Audit this website dataLayer against this Google Sheets guide."
"Find missing events in the checkout flow."
"Validate if add_to_cart includes all required ecommerce parameters."
"Compare dataLayer events vs GA4 network hits."
"Generate a QA report for development."
"Generate a GTM implementation plan from this tracking guide."
"Calculate the Tracking Coverage Score."

Try it instantly (demo mode)

No site or sheet yet? Every tool works against realistic sample data:

MEASURE_TQA_DEMO=true measure-tracking-qa

Relationship to Measure SDK

Like every Measure product, this depends on only measure-sdk — never on other MCPs (if Analytics/Paid-Media MCPs are also connected, the model composes them client-side; they never call each other).

Result types — AuditFinding, Report, HealthScore, Recommendation, ExecutionPlan, ValidationResult — come from the SDK and are never redefined.

Install

pip install measure-tracking-qa-mcp          # pulls measure-sdk automatically
pip install "measure-tracking-qa-mcp[web]"   # + Playwright for live dataLayer QA
playwright install chromium                  # one-time browser download (web extra)
measure login                                # Google OAuth (Sheets, GTM, GA4)
measure-tracking-qa                          # start the MCP server (stdio)

MCP tools (49)

Tools accept a guide three ways: an inline spec (JSON), a Google Sheet (sheet_id or MEASURE_TQA_DEFAULT_SHEET_ID), or demo mode. dataLayer events come from a live url (Playwright), an inline events list, or demo.

Tracking Coverage Score

A standard 0-100 score (SDK HealthScore) weighting Guide completeness 20%, DataLayer compliance 30%, GA4 collection accuracy 20%, GTM implementation quality 20%, Documentation quality 10% — comparable across the ecosystem.

What it validates

• Event-level: event exists, fires once, snake_case naming, documented trigger.
• Parameter-level: required present, correct type, non-empty, allowed enum values.
• Ecommerce-level: items array, item_id/item_name, transaction_id on purchase, duplicate-purchase detection (dataLayer and GA4 hits).
• Collection: dataLayer event → GA4 /collect hit (parsed from the network), spec → GA4 collection, dataLayer vs GA4 parity, GA4 property collected events.
• Journey-level: checkout-funnel event order across a multi-step journey.

Supported sources

Architecture (Clean Architecture)

src/measure_tracking_qa/
├── core/          # domain: TrackingSpec, EventSpec, DataLayerEvent, Ga4Hit, enums
├── config/        # settings (extends SDK CoreSettings; optional, non-secret)
├── connectors/    # infrastructure: google_sheets, web (Playwright), google_docs,
│                  #   google_slides, google_drive, gtm, ga4, figma, pdf
├── engines/       # application (pure): guides, datalayer, ga4_validation,
│                  #   gtm_planning, documentation, design, recommendations,
│                  #   alerts, health_score, web_qa
├── services/      # orchestration (connectors → engines)
├── validators/    # input validation → SDK ValidationResult
├── mcp/           # interface: server.py + tools/
└── cli/           # the measure-tracking-qa entry point

See docs/architecture/overview.md.

Security & disclaimer

This MCP is read-only by default: it reads, audits, recommends and documents. Write actions are gated: writing a guide to a Sheet requires confirm=true, and it never publishes to GTM — generate_gtm_implementation_plan only ever returns a proposed ExecutionPlan for you to apply manually. Any future write action follows preview → dry-run → confirmation → audit. See SECURITY.md.

Develop

git clone https://github.com/measure-mcp/measure-tracking-qa-mcp.git
cd measure-tracking-qa-mcp
uv sync --all-extras
uv run ruff check . && uv run mypy . && uv run pytest

Ecosystem

See CHANGELOG.md · ROADMAP.md · SECURITY.md · CONTRIBUTING.md · CODE_OF_CONDUCT.md.

License

Apache-2.0.