Google E-commerce (GA4, Search Console, Merchant Center, Ads)

google-ecommerce-mcp

One MCP server for the data an online shop decides from, for one shop or for many clients: GA4, Search Console, Merchant Center, Tag Manager, Indexing API, PageSpeed, the ad platforms Google Ads, Meta Ads and ChatGPT Ads, and the Meta pixel, catalog, Instagram and Page. It reads by default, and can also prepare controlled changes that you approve (pause a campaign, change a budget, submit a sitemap, add a tag in a workspace).

Ask your AI assistant "how much organic traffic did we get this month?", "which products are disapproved in Merchant Center?", "is GA4 loaded twice on my site?" or "what did each ad platform claim last month, and what does GA4 say?" and it answers from your own accounts. Out of the box it reads and reports and changes nothing. If you turn writing on for a client, the assistant can propose a change as a plan; nothing is sent until you approve it, and anything that costs money needs your approval in a terminal, outside the chat.

Built by MoonEyes, a small French shop selling 3D-printed tabletop terrain, because no existing MCP server covered GA4, Search Console and Merchant Center together.

Writing is off by default and has never been tested on a real account. The write tools exist in this version, but they were checked offline only, against fake answers written from each platform's documentation. Turning them on is opt-in per client and per platform, creations are always paused, and some risks cannot be removed (for example a Google Ads token or a ChatGPT Ads key cannot be limited to reading). Read docs/SECURITY.md and docs/WRITE.md before you turn it on, and try it first on a test account. New here? [docs/QUICKSTART.md](https://github.com/MoonEyes/google-ecommerce-mcp/blob/main/docs/QUICKSTART.md): your first client in 10 minutes.

The paid media connectors are new and tested offline only. The Google Ads, Meta Ads and ChatGPT Ads tools were checked against fake responses written from each platform's documentation. They have not been run against real ad accounts yet: compare the first figures with each platform's own interface. Details: docs/ADS.md.

Documentation

Why this one

• One server for the whole picture. Traffic and sales (GA4), organic search (Search Console), the product feed (Merchant Center), the tracking setup (Tag Manager), site speed, and what the ad platforms say they delivered. Other MCP servers cover one or two of these.
• Several clients, kept apart. An agency registers each client once (ids in a file, secrets in the OS keyring). Every call names its client, a foreign account id is refused, and one server process can be pinned to one client.
• Read by default, controlled writing on request. Reading uses a per-platform allow-list with no write endpoint. Writing is off until you enable it per client and per platform, and then goes through one path only: plan (diff, dry run, signed token), your approval (in a terminal for anything that costs money, is irreversible or touches personal data), apply, and a journal. Creations are paused; there is no activation, deletion or publishing in this version.
• Secrets kept out of the way. The Google token goes to your OS keyring (Windows Credential Manager, macOS Keychain or Secret Service). The Google Ads token is a separate keyring entry because its scope can write. Meta and ChatGPT Ads secrets go to the OS keyring from a hidden prompt (an environment variable also works), never on the command line or in a URL.
• Answers a model can read correctly. Reports return the top rows plus totals over everything, the unit and definition of each metric, dates resolved in the account's timezone with a flag when the last days can still change, and the attribution windows each ad platform used.
• Honest about what it does not know. Ad platforms count conversions their own way. The tools say so in every answer instead of adding up numbers that should not be added.
• No third party. Requests go straight from your machine to Google, Meta and OpenAI. Nothing goes through a MoonEyes server.

How it compares

Checked on 2026-10-18 from each project's public page; they change fast, so check before you decide.

Where this one fits: you run several shops or clients from one self-hosted server and want every change shown as a diff and approved before it is sent. If you need one Google product only, or a hosted service with nothing to install, the official servers above are the better choice.

What you can ask

Each case gives the question, the tools the assistant usually calls, what you learn, and the decision it supports. The decision stays yours: by default the server shows data and changes nothing, and any change it prepares needs your approval. Ready-to-paste prompts are in examples/PROMPTS.md.

Traffic, search, feed, tracking

1. Where do visits and sales come from? *"Sessions, purchases and revenue by channel, this month vs. last month."* Tools: ga4_report. You learn which channels bring revenue and which only bring visits. Decision: where to put the next hour or euro.
2. Which searches are one push away from page one? *"Queries ranking 5 to 15 with more than 100 impressions, and their landing page."* Tools: gsc_performance. You learn which pages already earn impressions but few clicks. Decision: which titles, descriptions and internal links to rewrite first.
3. Which disapproved products still get visits? *"Products disapproved in Merchant Center that still receive organic clicks."* Tools: merchant_product_issues, gsc_performance. You learn which feed errors hit pages people still visit. Decision: fix those products before the rest.
4. Is the tracking trustworthy? *"Is GA4 loaded twice? Does the purchase tag fire once? Is the workspace the same as the live version?"* Tools: gtm_inventory, ga4_realtime. You learn whether purchases or page views may be double counted and whether unpublished changes exist. Decision: publish, remove a duplicate tag, or leave it.
5. Preparing a redesign. *"Which landing pages earn money and organic clicks, which will need a 301, and what is today's speed baseline?"* Tools: ga4_report (dimension landingPage), gsc_performance, gsc_moves, gsc_opportunities, gsc_inspect_url, pagespeed. You learn which URLs to preserve, which redirects to plan, and the before-numbers to compare with after. Decision: the redirect map and what must not change.

Paid media (needs the c