MCP Google Search Console

Name: MCP Google Search Console
Author: crunchtools

by crunchtoolsversion 0.1.0i★ –iRuns on your computer

Registry nameio.github.crunchtools/google-search-console

Install

Overview

Description from the maker (original English)

Secure MCP server for Google Search Console analytics, sitemaps, and URL inspection

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

User voiceiNo reviews yetReviews open together with accounts in a later step
Our basic checksi1 of 1 passedChecked from public information; code not scanned yet
UsageiNot measured yet★ –

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

Connection: Runs on your computer
Transport: stdio
Category: Search & AI memory

Install

Pick the AI app you use, then copy the settings.

Before you install

Basic checks: 1 of 1 passed
Runs on your computer with your user’s permissions (files, network, apps).
The registry lists no key to fill in.

You need

PyPIPython’s uv installed (for the uvx command)

Which app do you use?

ClaudeClaude CodeCursorVS CodeChatGPT

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "google-search-console": {
      "command": "uvx",
      "args": [
        "mcp-google-search-console-crunchtools"
      ]
    }
  }
}

Run this in your terminal

claude mcp add google-search-console -- uvx mcp-google-search-console-crunchtools

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "google-search-console": {
      "command": "uvx",
      "args": [
        "mcp-google-search-console-crunchtools"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "google-search-console": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "mcp-google-search-console-crunchtools"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026

✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account crunchtools, which owns the repo
… Not checked yet
Still maintained
We have not read this repo from GitHub yet
… Not checked yet
Has a licence
We have not read this repo from GitHub yet
– Not applicable
Endpoint responds
This one runs on your computer; there is no internet endpoint
– Not applicable
Sign-in with OAuth
Runs on your computer and uses local settings instead
… Not checked yet
No hidden instructions in tool descriptions
Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Search & AI memoryi

More stars than 0% of the other 7254 servers in this category
Published to the registry more recently than 4% of the other 7254 servers in this category
Basic checks equal to or better than 100% of the other 7254 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is MCP Google Search Console safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.1.0) reached the registry 8 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.

What can I use instead?

In the same category: Context7, Codebase Memory, Exa

Alternatives

Servers in the same category from other makers, sorted by stars.

Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

Context7

by upstash

Feeds AI the latest docs for libraries and frameworks before it answers, so code it writes does not use outdated, removed functions.

Computer or cloud★ 64,224MITUpdated today

Install

Codebase Memory

by DeusData

Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.

Runs on your computer★ 48,148MITUpdated 20 days ago

Install

Exa

by exa-labs

Connect AI agents to Exa for web search, content fetching, and multi-step research.

Runs in the cloud★ 5,213MITUpdated last month

Install

README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

mcp-google-search-console-crunchtools

Secure MCP server for Google Search Console. Query search analytics (clicks, impressions, CTR, position), manage sitemaps, inspect URL indexing status, and manage site properties.

Installation

uvx (recommended, zero-install)

claude mcp add mcp-google-search-console-crunchtools \

--env GSC_CLIENT_ID=your_client_id \ --env GSC_CLIENT_SECRET=your_client_secret \ --env GSC_REFRESH_TOKEN=your_refresh_token \ -- uvx mcp-google-search-console-crunchtools

pip

pip install mcp-google-search-console-crunchtools

Container (Podman/Docker)

podman run -d -p 8017:8017 \

--env-file ~/.config/mcp-env/mcp-google-search-console.env \ quay.io/crunchtools/mcp-google-search-console \ --transport streamable-http --host 0.0.0.0

OAuth Setup

This server supports two authentication methods: browser-based OAuth (recommended) and environment variable (fallback).

Option A: Browser-Based OAuth (Recommended)

Browser-based OAuth handles token exchange automatically. When credentials expire, visit the /auth URL and click through Google's consent screen — no manual code exchange needed.

Step 1: Create a Google Cloud OAuth App

Go to Google Cloud Console
Create a new project (or select an existing one)
Navigate to APIs & Services > Library
Search for Google Search Console API and click Enable
Navigate to APIs & Services > Credentials
Click + CREATE CREDENTIALS > OAuth client ID
If prompted, configure the OAuth consent screen first:

User type: External (or Internal if using Google Workspace)
App name: anything (e.g., "MCP Search Console")
Scopes: add https://www.googleapis.com/auth/webmasters
Test users: add your Google account email

Back on Create OAuth client ID:

Application type: Web application
Name: anything (e.g., "MCP Search Console")
Authorized redirect URIs: add your server's callback URL (e.g., https://mcp-gsc.example.com/oauth2callback)

Click Create — copy the Client ID and Client Secret

Step 2: Configure and Start

Create an env file:

cat > ~/.config/mcp-env/mcp-google-search-console.env << 'EOF'

GSC_CLIENT_ID=your_client_id GSC_CLIENT_SECRET=your_client_secret GSC_CREDENTIALS_DIR=/data GSC_OAUTH_REDIRECT_URI=https://mcp-gsc.example.com/oauth2callback EOF chmod 600 ~/.config/mcp-env/mcp-google-search-console.env

Start the server with a persistent volume for credentials:

podman run -d -p 8017:8017 \

--env-file ~/.config/mcp-env/mcp-google-search-console.env \ -v mcp-gsc-data:/data:Z \ quay.io/crunchtools/mcp-google-search-console \ --transport streamable-http --host 0.0.0.0

Step 3: Authenticate

Visit https://mcp-gsc.example.com/auth in your browser. You'll be redirected to Google's consent screen. Grant access and the server will save credentials automatically.

When tokens expire, any tool call will return the /auth URL. Click it to re-authenticate — no container restart needed.

Option B: Environment Variable (Fallback)

If you prefer static credentials or can't expose a callback URL, set GSC_REFRESH_TOKEN in your env file. See the manual OAuth flow below.

Manual OAuth flow

export GSC_CLIENT_ID="your_client_id_here"

export GSC_CLIENT_SECRET="your_client_secret_here"

echo "https://accounts.google.com/o/oauth2/v2/auth?client_id=${GSC_CLIENT_ID}&redirect_uri=http://127.0.0.1&response_type=code&scope=https://www.googleapis.com/auth/webmasters&access_type=offline&prompt=consent"

Open the URL in your browser, sign in, and click Allow
Copy the code= value from the redirect URL
Exchange the code:

curl -s -X POST https://oauth2.googleapis.com/token \

-d "client_id=${GSC_CLIENT_ID}" \ -d "client_secret=${GSC_CLIENT_SECRET}" \ -d "code=PASTE_CODE_HERE" \ -d "grant_type=authorization_code" \ -d "redirect_uri=http://127.0.0.1" | python3 -m json.tool

Copy the refresh_token from the response and add GSC_REFRESH_TOKEN=... to your env file.

How it works at runtime

The server checks for credentials in this order:

File-based credentials from GSC_CREDENTIALS_DIR/credentials.json (written by the browser-based flow)
Environment variable GSC_REFRESH_TOKEN (fallback)

On each API call, the server exchanges the refresh token for a short-lived access token (~1 hour), cached in memory and refreshed automatically. Updated tokens are persisted to the credentials file for reuse across container restarts.

Available Tools (10)

Category	Count	Tools
Sites	4	list_sites, get_site, add_site, delete_site
Search Analytics	1	query_search_analytics
Sitemaps	4	list_sitemaps, get_sitemap, submit_sitemap, delete_sitemap
URL Inspection	1	inspect_url

Security

OAuth2 credentials stored as SecretStr (never logged)
File-based credentials written with 0o600 permissions (atomic writes)
Automatic token scrubbing from error messages
Pydantic input validation with extra="forbid"
No filesystem access, shell execution, or code evaluation
TLS certificate validation (httpx default)
Request timeouts and response size limits
Built on Hummingbird container images

See SECURITY.md for the full security design document.

Development

uv sync --all-extras

uv run ruff check src tests uv run mypy src uv run pytest -v gourmand --full . podman build -f Containerfile .

License

AGPL-3.0-or-later

MCP Google Search Console

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

What it can do

Basic checksi

Maker matches the repo

Still maintained

Has a licence

Endpoint responds

Sign-in with OAuth

No hidden instructions in tool descriptions

Compared with others in Search & AI memoryi

Common questions

Alternatives

Context7

Codebase Memory

Exa

README from the maker

mcp-google-search-console-crunchtools

Installation

uvx (recommended, zero-install)

pip

Container (Podman/Docker)

OAuth Setup

Option A: Browser-Based OAuth (Recommended)

Step 1: Create a Google Cloud OAuth App

Step 2: Configure and Start

Step 3: Authenticate

Option B: Environment Variable (Fallback)

How it works at runtime

Available Tools (10)

Security

Development

License