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Vrealmatic

Google Search Console MCP Server

by Vrealmatic

Google Search Console MCP Server

An MCP server that gives any MCP-compatible AI client (Claude Desktop, Claude Code, Cursor, …) read-only access to your Google Search Console data. Ask questions in plain language — "why did my traffic drop last week?" — and the assistant pulls the numbers, compares periods, and surfaces SEO opportunities for you.

Read-only. The server only ever reads Search Analytics data; it cannot change anything in your Search Console property.

What it does

It exposes six tools to the AI client:

Tool

What it answers

search_analytics

Raw clicks / impressions / CTR / position for a date range, grouped by query, page, country, device, or date.

compare_periods

Which pages or queries gained or lost the most clicks/impressions between two date ranges. Great for diagnosing traffic drops.

top_opportunities

"Low-hanging fruit" — pages/queries ranking 4–20, or high-impression pages with low CTR that are worth optimizing.

page_details

Deep dive on one page: its top queries and day-by-day trend.

query_details

For one query: which of your pages rank for it and how.

list_sites

Lists the configured properties — used when you have several sites and haven't said which one to analyze.

Related MCP server: gsc-mcp

Requirements

  • Node.js 18+

  • A Google account with access to a Search Console property

  • A Google Cloud OAuth client (free — steps below)

Quick start

# 1. Get an OAuth refresh token (interactive, one-time)
npx github:Vrealmatic/gsc-mcp-server get-token

# 2. Save the printed JSON as config.json, then point your MCP client at the server (see below)

That's it — the assistant can now query your Search Console.

Getting credentials

You need four values: CLIENT_ID, CLIENT_SECRET, REFRESH_TOKEN, and SITE_URL. Step 1 creates the OAuth client (the CLIENT_ID / CLIENT_SECRET); in step 2 you exchange those for a REFRESH_TOKEN — pick either method, both produce the same result.

Step 1 — Create an OAuth client

  1. Open the Google Cloud Console and create (or pick) a project.

  2. Enable the Google Search Console API: APIs & Services → Library → search "Search Console API" → Enable.

  3. Configure the OAuth consent screen (External is fine). Add yourself as a Test user so you can authorize without app verification.

  4. APIs & Services → Credentials → Create credentials → OAuth client ID.

    • Application type: Web application

    • Add both of these as Authorized redirect URIs (so either method below works):

      • http://localhost:5858/oauth2callback — for the helper script

      • https://developers.google.com/oauthplayground — for the OAuth Playground

  5. Copy the generated Client ID and Client secret.

Step 2 — Get a refresh token (pick one method)

npx github:Vrealmatic/gsc-mcp-server get-token

It asks for your Client ID, Client secret, and site URL, opens a browser for you to grant access, then prints a ready-to-paste config.json. Uses the http://localhost:5858/oauth2callback redirect URI.

Method B — Google OAuth Playground (no local helper)

Handy if you can't or don't want to run the script — everything happens in the browser:

  1. Open the OAuth Playground.

  2. Click the ⚙️ gear (top right) → check Use your own OAuth credentials → paste your Client ID and Client secret.

  3. In the left panel, scroll to the bottom field "Input your own scopes" and enter: https://www.googleapis.com/auth/webmasters.readonly

  4. Click Authorize APIs, sign in, and grant access.

  5. Click Exchange authorization code for tokens — copy the Refresh token.

Then assemble config.json by hand (next step) with that refresh token.

SITE_URL (needed by both methods) must match the property exactly as it appears in Search Console:

  • URL-prefix property: https://example.com/ (note the trailing slash)

  • Domain property: sc-domain:example.com

Step 3 — Save config.json

{
  "CLIENT_ID": "…",
  "CLIENT_SECRET": "…",
  "REFRESH_TOKEN": "…",
  "SITE_URL": "https://example.com/"
}

Save it anywhere outside the repo and point the server at it with --config (e.g. ~/.gsc/config.json). Keep it private — it grants read access to your Search Console data. If you do keep it inside the project folder, it's already covered by .gitignore.

Multiple sites

One config can hold several properties. Replace SITE_URL with a SITES array (the OAuth account must have access to each one):

{
  "CLIENT_ID": "…",
  "CLIENT_SECRET": "…",
  "REFRESH_TOKEN": "…",
  "SITES": ["https://example.com/", "sc-domain:another-site.com"]
}

How site selection works:

  • Every tool takes an optional siteUrl argument. Just name the site in your question — "compare last month for another-site.com" — and the assistant passes it through. A partial match is enough (another-site resolves to sc-domain:another-site.com).

  • If you don't specify a site and several are configured, the tool returns the list of available sites and the assistant will ask you which one to use. It never silently picks one.

  • The list_sites tool lets the assistant enumerate the configured properties at any time.

  • With only one site configured (SITE_URL or a single-entry SITES), siteUrl is optional and that site is always used.

To keep properties fully isolated instead (separate tokens, separate clients), register multiple MCP server entries, each with its own --config.

Connecting your MCP client

The server speaks MCP over stdio. Pass your credentials with --config:

Claude Desktop

Edit claude_desktop_config.json (macOS: ~/Library/Application Support/Claude/, Windows: %APPDATA%\Claude\):

{
  "mcpServers": {
    "search-console": {
      "command": "npx",
      "args": [
        "-y",
        "github:Vrealmatic/gsc-mcp-server",
        "--config",
        "/absolute/path/to/config.json"
      ]
    }
  }
}

Claude Code

claude mcp add search-console -- npx -y github:Vrealmatic/gsc-mcp-server --config /absolute/path/to/config.json

Local clone

git clone https://github.com/Vrealmatic/gsc-mcp-server.git
cd gsc-mcp-server
npm install
node index.js --config ./config.json

You can also pass credentials via environment variables (CLIENT_ID, CLIENT_SECRET, REFRESH_TOKEN, SITE_URL) instead of --config.

Example

Once connected, just talk to your assistant:

You: My organic traffic feels lower this month. What dropped between May and June?

The assistant calls compare_periods and replies:

Comparing 2026-05-01 → 2026-05-31 vs 2026-06-01 → 2026-06-23, the biggest click losses are:

Page

May clicks

June clicks

Δ

/guides/onboarding

1,240

410

−830

/pricing

980

720

−260

/blog/seo-basics

540

360

−180

/guides/onboarding lost two-thirds of its clicks and its average position slipped from 3.1 to 7.8 — that single page explains most of the drop. Want me to pull page_details for it to see which queries fell?

You: Yes, and show me where the easy wins are.

It then runs page_details and top_opportunities to point you at queries sitting at positions 4–20 (a small ranking gain there yields a big click jump) and high-impression pages with weak CTR.

How it works

  • Built on the official @modelcontextprotocol/sdk.

  • Authenticates to Google with the googleapis OAuth2 client and a long-lived refresh token, scoped to webmasters.readonly.

  • One or more properties per server instance (SITE_URL or SITES); see Multiple sites above.

Security

  • The OAuth scope is read-only (webmasters.readonly).

  • Your config.json / refresh token are stored locally and never leave your machine except to talk to Google's API. Do not commit them.

  • Revoke access anytime at Google Account → Security → Third-party access.

License

MIT © Vrealmatic.com

A
license - permissive license
-
quality - not tested
C
maintenance

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