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ahonn

A Model Context Protocol (MCP) server providing access to Google Search Console

Publisherahonn
Repositorymcp-server-gsc
LanguageTypeScript
Forks
48
Stars
218
Available tools
0
Transport typestdio
Categories
LicenseMIT
Links
  • Connect tools to AI workflows

    Google Search Console exposes MCP capabilities that can be used by compatible AI clients and agents.

  • 0 available tools

    Browse the callable actions below, including names and descriptions when provided by the server.

  • Ready-to-copy setup

    Use the installation snippets to configure this server in your preferred MCP client.

  • Open source signals

    218 stars and 48 forks from the linked repository.

Google Search Console MCP Server

A Model Context Protocol (MCP) server providing comprehensive access to Google Search Console data with enhanced analytics capabilities.

Features

  • Enhanced Search Analytics: Retrieve up to 25,000 rows of performance data
  • Advanced Filtering: Support for regex patterns and multiple filter operators
  • Quick Wins Detection: Automatically identify optimization opportunities
  • Rich Dimensions: Query, page, country, device, and search appearance analysis
  • Flexible Date Ranges: Customizable reporting periods with historical data access

Sponsored by

macuse.app is a native macOS application that gives your AI superpowers by integrating AI assistants with macOS apps like Calendar, Mail, and Notes, plus universal UI control for any application. Supports Claude Desktop, Cursor, and Raycast with one-click setup. Privacy-first, runs locally.

Prerequisites

  • Node.js 18 or later
  • Google Cloud Project with Search Console API enabled
  • Service Account credentials with Search Console access

Installation

bash
npm install mcp-server-gsc

Authentication Setup

To obtain Google Search Console API credentials:

  1. Visit the Google Cloud Console
  2. Create a new project or select an existing one
  3. Enable the API:
  1. Create credentials:
  • Navigate to "APIs & Services" > "Credentials"
  • Click "Create Credentials" > "Service Account"
  • Fill in the service account details
  • Create a new key in JSON format
  • The credentials file (.json) will download automatically
  1. Grant access:

Usage

Claude Desktop Configuration

json
{
  "mcpServers": {
    "gsc": {
      "command": "npx",
      "args": ["-y", "mcp-server-gsc"],
      "env": {
        "GOOGLE_APPLICATION_CREDENTIALS": "/path/to/credentials.json"
      }
    }
  }
}

Available Tools

search_analytics

Get comprehensive search performance data from Google Search Console with enhanced analytics capabilities.

Required Parameters:

  • siteUrl: Site URL (format: http://www.example.com/ or sc-domain:example.com)
  • startDate: Start date (YYYY-MM-DD)
  • endDate: End date (YYYY-MM-DD)

Optional Parameters:

  • dimensions: Comma-separated list (query, page, country, device, searchAppearance, date)
  • type: Search type (web, image, video, news, discover, googleNews)
  • aggregationType: Aggregation method (auto, byNewsShowcasePanel, byProperty, byPage)
  • rowLimit: Maximum rows to return (default: 1000, max: 25000)
  • dataState: Data freshness (all or final, default: final)

Filter Parameters:

  • pageFilter: Filter by page URL (supports regex with regex: prefix)
  • queryFilter: Filter by search query (supports regex with regex: prefix)
  • countryFilter: Filter by country ISO 3166-1 alpha-3 code (e.g., USA, CHN)
  • deviceFilter: Filter by device type (DESKTOP, MOBILE, TABLET)
  • searchAppearanceFilter: Filter by search feature (e.g., AMP_BLUE_LINK, AMP_TOP_STORIES)
  • filterOperator: Operator for filters (equals, contains, notEquals, notContains, includingRegex, excludingRegex)

Quick Wins Detection:

  • detectQuickWins: Enable automatic detection of optimization opportunities (default: false)
  • quickWinsConfig: Configuration for quick wins detection:
    • positionRange: Position range to consider (default: [4, 20])
    • minImpressions: Minimum impressions threshold (default: 100)
    • minCtr: Minimum CTR percentage (default: 1)

Example - Basic Query:

json
{
  "siteUrl": "https://example.com",
  "startDate": "2024-01-01",
  "endDate": "2024-01-31",
  "dimensions": "query,page",
  "rowLimit": 5000
}

Example - Advanced Filtering with Regex:

json
{
  "siteUrl": "https://example.com",
  "startDate": "2024-01-01",
  "endDate": "2024-01-31",
  "dimensions": "page,query",
  "queryFilter": "regex:(AI|machine learning|ML)",
  "filterOperator": "includingRegex",
  "deviceFilter": "MOBILE",
  "rowLimit": 10000
}

Example - Quick Wins Detection:

json
{
  "siteUrl": "https://example.com",
  "startDate": "2024-01-01",
  "endDate": "2024-01-31",
  "dimensions": "query,page",
  "detectQuickWins": true,
  "quickWinsConfig": {
    "positionRange": [4, 15],
    "minImpressions": 500,
    "minCtr": 2
  }
}

License

MIT

Contributing

Contributions are welcome! Please read our contributing guidelines before submitting pull requests.

Installation

TypingMind
Prerequisites:

Node.js 18+

{
  "mcpServers": {
    "gsc": {
      "command": "npx",
      "args": [
        "-y",
        "mcp-server-gsc"
      ],
      "env": {
        "GOOGLE_APPLICATION_CREDENTIALS": "/path/to/credentials.json"
      }
    }
  }
}

Use Google Search Console MCP with multiple AI models

TypingMind connects MCP tools at the workspace level, so once Google Search Console is connected, you can use it with different AI models in TypingMind instead of setting it up separately for each model. This MCP runs locally through the TypingMind MCP connector on your device.

Setup guide to use the local connector

Use this when the MCP server needs access to local files, apps, or private resources on your computer.

1

Open the MCP settings

In TypingMind, go to Settings, Advanced Settings, then Model Context Protocol and choose Setup Connector.

  1. Open TypingMind in your browser.
  2. Click the Settings icon.
  3. Go to Advanced Settings.
  4. Open the Model Context Protocol section.
  5. Click Setup Connector and choose This Device.
TypingMind MCP connector setup screen with This Device selected
2

Run the connector command

Choose This Device, copy the command from TypingMind, and run it in Terminal. Keep the process running while you use MCP.

  1. Copy the setup command shown by TypingMind.
  2. Open Terminal on macOS or Windows Terminal on Windows.
  3. Paste and run the command.
  4. Approve the package install if Terminal asks you to proceed.
  5. Keep the Terminal window running while using MCP tools.
3

Add Google Search Console as a server

When the connector status is Ready, click Edit Servers and paste the MCP server configuration.

  1. Wait until the connector status shows Ready.
  2. Click Edit Servers.
  3. Paste the Google Search Console MCP server configuration.
  4. Save the server list.
  5. Refresh if you want to confirm the connector is still ready.
TypingMind MCP settings showing active server and Edit Servers button
{
  "mcpServers": {
    "google-search-console": {
      "command": "npx",
      "args": [
        "-y",
        "mcp-server-gsc"
      ]
    }
  }
}
4

Use it across models

Save the server list, open Plugins, enable the Google Search Console MCP tools, then select any supported AI model in TypingMind and use the tools in chat or assign them to an AI agent.

  1. Open the Plugins page in TypingMind.
  2. Enable the Google Search Console MCP tools.
  3. Start a chat and choose the AI model you want to use.
  4. Use the MCP tools in chat or assign them to an AI agent.
  5. Switch to another AI model whenever needed without reconnecting MCP.
TypingMind chat using enabled MCP tools with a selected AI model
Can you use Google Search Console to help me with this task?
Google Search Console
Sure. I read it.
Here is what I found using Google Search Console.

Frequently asked questions

What is the Google Search Console MCP server used for?

Google Search Console is an MCP server that lets compatible AI clients connect to external tools and context. In TypingMind, you can add this MCP server once and make its tools available in your AI workspace.

Can I use Google Search Console MCP with multiple AI models in TypingMind?

Yes. TypingMind connects MCP tools at the workspace level, so you can use Google Search Console with different AI models such as Claude, ChatGPT, Gemini, or other models you have configured in TypingMind without setting up the MCP server separately for each model.

Why use Google Search Console MCP with TypingMind?

TypingMind is one of the best frontends for LLM chat because it brings multiple AI models, prompts, plugins, AI agents, API keys, and MCP tools into one workspace. With Google Search Console connected, you can use its MCP tools across your preferred models while keeping your chat workflow organized in TypingMind.

How do I connect Google Search Console MCP to TypingMind?

Google Search Console runs through the TypingMind local MCP connector. This is best when the MCP server needs access to local files, desktop apps, command-line tools, or private resources on your computer.

What tools does Google Search Console MCP provide in TypingMind?

Google Search Console exposes MCP capabilities that can be enabled from the TypingMind Plugins page and used in chat or assigned to AI agents.

Do I need to share my API keys with TypingMind to use Google Search Console MCP?

No. TypingMind is local-first and lets you keep your model providers, API keys, prompts, and MCP configuration under your control. If Google Search Console requires authentication, add the required headers, OAuth settings, or local configuration for that MCP server when you create the connection.

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