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Google Search Console MCP "Intel Engine" 🚀

PyPI version PyPI Downloads GitHub stars GitHub forks License: MIT

The Authority-Based Visibility Governance Tool for the Evolving Search Landscape.

This is not just a data wrapper. It is a strategic "Intel" engine that transforms raw Google Search Console signals into actionable marketing insights. It is designed for marketers who need to understand their performance in a search landscape increasingly defined by AI Overviews and conversational search. Compatible with any MCP-compliant AI Agent.

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🎯 Authoritative "Intel" Tools

Tool Name Actionable Marketing Intel Provided
get_search_appearance_audit Cannibalization Intel. Detects if you are being used as a "Silent Reference" (high visibility but no clicks) in specialized SERP features.
get_intent_segmentation Strategic Audience Intel. Segments traffic into "Searchers" (Traditional Keywords) vs. "Prompters" (Natural Language/AI Prompts).
identify_citation_opportunities Growth Intel. Finds content that satisfies user intent so well that users don't click. Recommends "Click-Triggers."
get_technical_citation_audit Technical Health Overlay. Cross-checks high-visibility pages with the URL Inspection API to find disqualifying crawl errors.
get_brand_visibility_summary Brand Health Intel. Measures your Brand's "Reference Value" vs its "Destination Value."
calculate_intent_efficiency Conversion Intel. Shows which search intent (Informational/Navigational) is most effectively driving site visits.

🚀 Getting Started

1. Google Search Console Setup

Before installing the MCP server, you must configure Google Cloud and Search Console access:

A. Create Service Account:

  1. Go to the Google Cloud Console.
  2. Create a new project and enable the Google Search Console API.
  3. Go to APIs & Services > Credentials and create a Service Account.
  4. Create a JSON Key for the service account and download it (save as gsc-key.json).

B. Grant Access in Search Console:

  1. Open your JSON key file and copy the client_email address.
  2. Go to Google Search Console.
  3. Select your property and go to Settings > Users and Permissions.
  4. Click Add User, paste the service account email, and select Full permissions.

C. Identify Your Property URL:

  • For Domain properties, use the format: sc-domain:example.com
  • For URL-prefix properties, use the full URL: https://example.com/

2. Installation

pip install google-search-console-mcp

3. Configuration (Universal AI Agent)

Add this to your agent's MCP settings file:

{
  "mcpServers": {
    "gsc-search": {
      "command": "gsc-mcp",
      "env": {
        "GOOGLE_APPLICATION_CREDENTIALS": "/path/to/your/gsc-key.json",
        "GSC_SITE_URL": "sc-domain:example.com"
      }
    }
  }
}

🛠️ Project Philosophy

This project focuses on high-leverage data analysis for modern search:

  • Simplicity First: Minimum code for maximum insight.
  • Token Efficiency: Server-side aggregation prevents "Context Length" issues.
  • Authoritative Data: We only use official Google Search Console API signals. No speculative "AI SEO" hacks.

Telemetry & Privacy

This server sends anonymous usage telemetry (server version, OS, Python version, MCP client name, tool name, latency, error category) to help improve it. It never collects PII, your Search Console data, credentials, or file paths. Opt out any time by setting DISABLE_TELEMETRY=1, DO_NOT_TRACK=1, NO_TELEMETRY=1, or GSC_MCP_TELEMETRY=false.

License

MIT License

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  • Released:
Newer release available (0.10.1)

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Credits

Author: Surendran B

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MIT
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Requires

Python >=3.10

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