Official · MODEL CONTEXT PROTOCOL

ahonn mcp server gsc

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

连接能力

ahonn mcp server gsc 为 AI Agent 提供什么

  • Search analytics data retrieval with dimensions support
  • Rich data analysis with customizable reporting periods
  • Node.js 18 or later
  • Google Cloud Project with Search Console API enabled
  • Service Account credentials with Search Console access
  • Visit the [Google Cloud Console](https://console.cloud.google.com/)
  • Create a new project or select an existing one
  • Enable the API:
  • Go to "APIs & Services" > "Library"
  • Search for and enable ["Search Console API"](https://console.cloud.google.com/marketplace/product/google/searchconsole.googleapis.com)
  • Create credentials:
  • Navigate to ["APIs & Services" > "Credentials"](https://console.cloud.google.com/apis/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
  • Grant access:
  • Open Search Console
  • Add the service account email (format: name@project.iam.gserviceaccount.com) as a property administrator
  • `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)
  • `dimensions`: Comma-separated list (`query,page,country,device,searchAppearance`)
  • `type`: Search type (`web`, `image`, `video`, `news`)
  • `aggregationType`: Aggregation method (`auto`, `byNewsShowcasePanel`, `byProperty`, `byPage`)
  • `rowLimit`: Maximum rows to return (default: 1000)

安全

MCP 收录不等于安全审核

MCP 服务器可能获得模型上下文、凭据、本地文件或调用外部系统的权限。连接 Agent 前,请检查代码、环境变量、网络行为、软件包来源与维护状态。

README

仓库文档

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

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

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

{
  "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:

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

Example - Advanced Filtering with Regex:

{
  "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:

{
  "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.

在 GitHub 查看 README

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