analytics-data

Google Search Console

ahonn

by ahonn

Analyze your site's SEO metrics and search performance data with Google Search Console webmaster tools for improved visi

Analyze SEO metrics and search performance data.

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    what it does

    Analyze SEO metrics and search performance data.

    about

    Google Search Console is a community-built MCP server published by ahonn that provides AI assistants with tools and capabilities via the Model Context Protocol. Analyze your site's SEO metrics and search performance data with Google Search Console webmaster tools for improved visi It is categorized under analytics data.

    how to install

    You can install Google Search Console in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.

    license

    MIT

    Google Search Console is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.

    readme

    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

    <a href="https://macuse.app?ref=mcp-server-gsc"> <img src="https://macuse.app/logo-pill.png" width="200" alt="macuse.app"> </a>

    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:
    • Open Search Console
    • Add the service account email (format: [email protected]) as a property administrator

    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.

    FAQ

    What is the Google Search Console MCP server?
    Google Search Console is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
    How do MCP servers relate to agent skills?
    Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
    How are reviews shown for Google Search Console?
    This profile displays 45 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.6 out of 5—verify behavior in your own environment before production use.

    Use Cases

    Extended AI Capabilities

    Add new capabilities to Claude beyond text generation

    Example

    Access external data sources, execute code, interact with tools and services

    Transform Claude from chatbot to action-taking agent

    Context Enhancement

    Provide Claude with access to relevant context and data

    Example

    Load project documentation, access knowledge bases, query databases

    Get more accurate, context-aware responses

    Workflow Automation

    Automate multi-step workflows combining AI and external tools

    Example

    Research → Summarize → Create document → Send notification

    Complete complex tasks end-to-end without manual steps

    Implementation Guide

    Prerequisites

    • Claude Desktop 0.7.0+ or Cursor IDE with MCP support
    • Basic understanding of MCP architecture and capabilities
    • Access credentials for integrated services (if required)
    • Willingness to experiment and iterate on configuration

    Time Estimate

    15-60 minutes depending on server complexity

    Installation Steps

    1. 1.Install MCP server: npm install -g [package-name] or via GitHub
    2. 2.Add server configuration to ~/.claude/mcp.json
    3. 3.Provide required credentials and configuration
    4. 4.Restart Claude Desktop to load new server
    5. 5.Test basic functionality with simple prompts
    6. 6.Explore capabilities and experiment with use cases
    7. 7.Document successful patterns for reuse

    Troubleshooting

    • MCP server not loading: Check config syntax, verify installation
    • Connection errors: Check network, firewall, credentials
    • Feature not working: Read server docs, check required parameters
    • Performance issues: Monitor resource usage, check for network latency
    • Conflicts with other servers: Check port assignments, namespace collisions

    Best Practices

    ✓ Do

    • +Read server documentation thoroughly before setup
    • +Start with simple use cases to validate functionality
    • +Test in non-production environment first
    • +Monitor resource usage and performance
    • +Keep servers updated for bug fixes and new features
    • +Document configuration for team members
    • +Use environment variables for sensitive configuration

    ✗ Don't

    • Don't grant overly permissive access to MCP servers
    • Don't skip reading security considerations in docs
    • Don't expose sensitive data without proper controls
    • Don't run untrusted MCP servers without code review
    • Don't ignore error messages—investigate root cause

    💡 Pro Tips

    • Combine multiple MCP servers for powerful workflows
    • Create custom MCP servers for your specific needs
    • Share successful configurations with team
    • Use MCP inspector for debugging
    • Join MCP community for tips and troubleshooting

    Technical Details

    Architecture

    Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.

    Protocols

    • Model Context Protocol (MCP)
    • JSON-RPC 2.0
    • stdio or HTTP transport

    Compatibility

    • Claude Desktop
    • Cursor IDE
    • Custom MCP clients

    When to Use This

    ✓ Use When

    Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.

    ✗ Avoid When

    Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.

    Integration

    • Tool composition: Chain multiple MCP tools in workflows
    • Context augmentation: Provide AI with relevant external data
    • Action delegation: Let AI execute tasks on external systems
    • Bidirectional sync: Keep AI context and external systems in sync

    Discussion

    Product Hunt–style comments (not star reviews)
    • No comments yet — start the thread.

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    Ratings

    4.645 reviews
    • Rahul Santra· Dec 24, 2024

      We evaluated Google Search Console against two servers with overlapping tools; this profile had the clearer scope statement.

    • Tariq Zhang· Dec 20, 2024

      Google Search Console has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.

    • Noor Sharma· Dec 8, 2024

      According to our notes, Google Search Console benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.

    • Dev Liu· Nov 27, 2024

      We wired Google Search Console into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.

    • Shikha Mishra· Nov 15, 2024

      Useful MCP listing: Google Search Console is the kind of server we cite when onboarding engineers to host + tool permissions.

    • Isabella Mensah· Nov 11, 2024

      Google Search Console is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.

    • Daniel Chawla· Nov 11, 2024

      Strong directory entry: Google Search Console surfaces stars and publisher context so we could sanity-check maintenance before adopting.

    • Alexander Park· Oct 18, 2024

      Google Search Console is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.

    • Sakshi Patil· Oct 6, 2024

      Google Search Console reduced integration guesswork — categories and install configs on the listing matched the upstream repo.

    • Isabella Kim· Oct 2, 2024

      We wired Google Search Console into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.

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