Google Search Console MCP Server

A tool for accessing Google Search Console using the Model Context Protocol (MCP) server.

Features

• Retrieve search analytics data (with dimension support)
• Detailed data analysis with customizable reporting periods

Prerequisites

• Python 3.10 or higher
• Google Cloud project with Search Console API enabled
• Service account credentials with access to Search Console

Installation

pip install mcp-server-google-search-console

Or install from source:

git clone https://github.com/yourusername/mcp-server-google-search-console.git
cd mcp-server-google-search-console
pip install -e .

Setting Up Development Environment (uv)

This project uses uv for faster package management and installation.

Installing uv and uvx

First, install uv and uvx:

pip install uv uvx

Creating and Managing Virtual Environments

To create a new virtual environment using uv:

uv venv
source .venv/bin/activate  # Linux/macOS
.venv\Scripts\activate     # Windows

Installing Dependencies

After cloning the repository, install dependencies:

git clone https://github.com/yourusername/mcp-server-google-search-console.git
cd mcp-server-google-search-console
pip install -e .

To install the MCP package separately:

pip install "mcp[cli]"

Installing Development Dependencies

To install additional tools needed for development, run:

pip install -e ".[dev]"

Authentication Setup

To obtain Google Search Console API credentials:

1. Access the Google Cloud Console
2. Create a new project or select an existing one
3. Enable the API:
   • Go to "APIs & Services" > "Library"
   • Search for and enable "Search Console API"
4. Create credentials:
   • Go to "APIs & Services" > "Credentials"
   • Click "Create Credentials" > "Service Account"
   • Enter service account details
   • Create a new key in JSON format
   • The credentials file (.json) will be automatically downloaded
5. Grant access:
   • Open Search Console
   • Add the service account email address (format: name@project.iam.gserviceaccount.com) as a property administrator

Usage

Set an environment variable to specify the path to your Google Search Console credentials file:

export GOOGLE_APPLICATION_CREDENTIALS=/path/to/credentials.json

Starting the MCP Server

Standard Method

mcp-server-gsc

Using uvx

With uvx, you can automate virtual environment and package installation:

# Run directly without installation
uvx run mcp-server-gsc

# Run with a specific Python version
uvx --python=3.11 run mcp-server-gsc

# Run with specified environment variables
uvx run -e GOOGLE_APPLICATION_CREDENTIALS=/path/to/credentials.json mcp-server-gsc

Configuration for Claude Desktop Application

Standard Configuration

{
  "mcpServers": {
    "gsc": {
      "command": "mcp-server-gsc",
      "env": {
        "GOOGLE_APPLICATION_CREDENTIALS": "/path/to/credentials.json"
      }
    }
  }
}

Configuration Using uvx

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

Available Tools

search_analytics

Retrieve search performance data from Google Search Console:

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)
• type: Search type (web, image, video, news)
• aggregationType: Aggregation method (auto, byNewsShowcasePanel, byProperty, byPage)
• rowLimit: Maximum number of rows to return (default: 1000)

Example usage:

{
  "siteUrl": "https://example.com",
  "startDate": "2024-01-01",
  "endDate": "2024-01-31",
  "dimensions": "query,country",
  "type": "web",
  "rowLimit": 500
}

Release Procedure

This project is automatically published to PyPI when a GitHub release tag is created.

To release a new version:

1. Run the version update script:

   python scripts/bump_version.py [major|minor|patch]
   

2. Follow the displayed instructions to push to GitHub:

   git add pyproject.toml
   git commit -m "Bump version to x.y.z"
   git tag vx.y.z
   git push origin main vx.y.z
   

3. Create a release on the GitHub repository page:

   • Select tag: vx.y.z
   • Enter title: vx.y.z
   • Fill in release notes
   • Click "Publish"

4. GitHub Actions will be triggered and automatically publish the package to PyPI.

License

MIT

Contributions

Contributions are welcome! Please read the contribution guidelines before submitting a pull request.