Google Search Console MCP Server
This MCP server provides LLMs with programmatic access to Google Search Console data and functionality, including search analytics, sitemap management, site management, and URL inspection.
README
Google Search Console MCP Server
A Model Context Protocol (MCP) server that provides LLMs with programmatic access to Google Search Console data and functionality. Built with FastMCP.
Features
🛠️ Tools (13 Actions)
Search Analytics
query_search_analytics- Query search traffic data with filters and dimensions
Sitemap Management
list_sitemaps- List all sitemaps for a siteget_sitemap- Get details about a specific sitemapsubmit_sitemap- Submit a sitemap to Googledelete_sitemap- Remove a sitemap
Site Management
list_sites- List all sites in your Search Console accountget_site- Get information about a specific siteadd_site- Add a site to Search Consoledelete_site- Remove a site from Search Console
URL Inspection
inspect_url- Inspect the Google index status of a specific URL
📊 Resources (6 Data Sources)
gsc://sites- List all available sitesgsc://config- Server configuration and statusgsc://sites/{site_url}/analytics/summary- Recent analytics summary (28 days)gsc://sites/{site_url}/sitemaps- Site sitemapsgsc://sites/{site_url}/top-queries- Top 10 queries (7 days)gsc://sites/{site_url}/top-pages- Top 10 pages (7 days)
💬 Prompts (4 Templates)
analyze_search_performance- Generate SEO performance analysis promptseo_recommendations- Generate SEO recommendations promptcompare_periods- Generate period-over-period comparison promptindexing_health_check- Generate indexing health check prompt
Installation
Prerequisites
- Python 3.10 or higher
- Google Cloud Project with Search Console API enabled
- OAuth 2.0 credentials from Google Cloud Console
Install Dependencies
# Clone the repository
git clone https://github.com/damupi/mcp-gsc.git
cd mcp-gsc
# Install with uv (recommended)
uv sync
# Or install in development mode
uv pip install -e .
Authentication Setup
This server uses FastMCP's built-in Google OAuth integration.
Step 1: Create Google OAuth 2.0 Credentials
- Go to Google Cloud Console
- Create a new project or select an existing one
- Enable the Google Search Console API
- Go to Credentials → Create Credentials → OAuth 2.0 Client ID
- Configure OAuth consent screen if prompted
- Choose Web application as application type
- Add Authorized Javascript origins:
http://localhost - Add authorized redirect URI:
http://localhost:8000/auth/callback - Save your Client ID and Client Secret
Step 2: Configure Environment Variables
Create a .env file in the project root:
cp .env.example .env
Edit .env and add your credentials:
FASTMCP_SERVER_AUTH=fastmcp.server.auth.providers.google.GoogleProvider
FASTMCP_SERVER_AUTH_GOOGLE_CLIENT_ID=your-client-id.apps.googleusercontent.com
FASTMCP_SERVER_AUTH_GOOGLE_CLIENT_SECRET=GOCSPX-your-client-secret
FASTMCP_SERVER_AUTH_GOOGLE_REQUIRED_SCOPES=openid,https://www.googleapis.com/auth/userinfo.email,https://www.googleapis.com/auth/webmasters
Usage
Running the Server
Development Mode (STDIO)
fastmcp dev src/mcp_gsc/server.py
Production Mode (HTTP Transport)
# Run with HTTP transport for remote access
fastmcp run src/mcp_gsc/server.py --transport http
# Specify custom host and port
fastmcp run src/mcp_gsc/server.py --transport http --host 0.0.0.0 --port 8080
The server will start on http://localhost:8000 by default (HTTP mode).
Running with Docker
Quick Start:
# Build the Docker image
make build
# Start the server
make up
# View logs
make logs
# Stop the server
make down
Available Make Commands:
make build- Build the Docker imagemake up- Start the MCP server in backgroundmake down- Stop the MCP servermake restart- Restart the servermake logs- View server logs (follow mode)make logs-tail- View last 100 lines of logsmake status- Check server statusmake clean- Remove all Docker resourcesmake shell- Open a shell in the running containermake rebuild- Rebuild and restartmake dev- Run with live logsmake test- Test server health endpoint
Docker Configuration:
The server runs in a Docker container with:
- Python 3.12 slim base image
- UV for fast dependency management
- HTTP transport on port 8000
- Automatic restart on failure
- Health checks every 30 seconds
Make sure your .env file is configured before running make up.
Authentication Flow
- Start the server
- Connect with an MCP client (e.g., Claude Desktop)
- You'll be redirected to Google OAuth login
- Grant permissions to access Search Console data
- You'll be redirected back and authenticated
Using with Claude Desktop
Option 1: STDIO Transport (Local)
Add to your Claude Desktop configuration (~/Library/Application Support/Claude/claude_desktop_config.json on macOS):
{
"mcpServers": {
"gsc-mcp-server": {
"command": "fastmcp",
"args": ["run", "src/mcp_gsc/server.py"],
"env": {
"FASTMCP_SERVER_AUTH": "fastmcp.server.auth.providers.google.GoogleProvider",
"FASTMCP_SERVER_AUTH_GOOGLE_CLIENT_ID": "your-client-id.apps.googleusercontent.com",
"FASTMCP_SERVER_AUTH_GOOGLE_CLIENT_SECRET": "GOCSPX-your-client-secret",
"FASTMCP_SERVER_AUTH_GOOGLE_REQUIRED_SCOPES": "openid,https://www.googleapis.com/auth/userinfo.email,https://www.googleapis.com/auth/webmasters"
}
}
}
}
Option 2: HTTP Transport (Remote)
First, start the server with HTTP transport:
fastmcp run src/mcp_gsc/server.py --transport http
Then configure Claude Desktop to connect via HTTP:
{
"mcpServers": {
"gsc-mcp-server": {
"command": "npx",
"args": [
"-y",
"mcp-remote@latest",
"http://localhost:8000/mcp"
]
}
}
}
Debugging with MCP Inspector
You can use the MCP Inspector to test and debug the server.
For Local Development:
npx @modelcontextprotocol/inspector fastmcp dev src/mcp_gsc/server.py
For Docker/Remote Server:
npx @modelcontextprotocol/inspector http://localhost:8000/mcp
Example Usage
Query Search Analytics
# Ask Claude:
"Show me the top 10 search queries for https://example.com/
from 2024-01-01 to 2024-01-31"
# Claude will use:
query_search_analytics(
site_url="https://example.com/",
start_date="2024-01-01",
end_date="2024-01-31",
dimensions=["query"],
row_limit=10
)
Get Analytics Summary
# Ask Claude:
"What's the recent search performance for https://example.com/?"
# Claude will access the resource:
gsc://sites/https%3A%2F%2Fexample.com%2F/analytics/summary
SEO Analysis
# Ask Claude:
"Analyze the search performance for https://example.com/
and give me SEO recommendations"
# Claude will use the prompt:
analyze_search_performance(
site_url="https://example.com/",
time_period="last 30 days"
)
Available Dimensions for Analytics
When using query_search_analytics, you can group data by:
query- Search queriespage- Landing pagescountry- Countriesdevice- Device types (desktop, mobile, tablet)searchAppearance- How the result appeared in searchdate- Dates
API Scopes
The server requires these OAuth scopes:
openid- User identificationhttps://www.googleapis.com/auth/userinfo.email- User emailhttps://www.googleapis.com/auth/webmasters- Full Search Console access
For read-only access, modify src/mcp_gsc/auth.py to use webmasters.readonly scope.
Development
Project Structure
mcp-gsc/
├── src/mcp_gsc/
│ ├── __init__.py # Package initialization
│ ├── server.py # Main FastMCP server
│ ├── auth.py # Google OAuth authentication
│ ├── tools.py # MCP tools (13 actions)
│ ├── resources.py # MCP resources (6 data sources)
│ ├── prompts.py # MCP prompts (4 templates)
│ └── utils.py # Utility functions
├── examples/ # Usage examples
├── pyproject.toml # Project configuration
├── .env.example # Environment variables template
└── README.md # This file
Running Tests
# Install dev dependencies
uv sync --all-extras
# Run tests
pytest
# Run linting
ruff check src/
Troubleshooting
Authentication Errors
Problem: "Authentication failed" or "401 Unauthorized"
Solution:
- Verify your OAuth credentials are correct
- Check that the redirect URI matches exactly:
http://localhost:8000/auth/callback - Ensure the Search Console API is enabled in your Google Cloud project
Permission Denied (403)
Problem: "Permission denied" when accessing a site
Solution:
- Verify you have access to the site in Google Search Console
- Check that you're using the correct site URL format (e.g.,
https://example.com/) - Ensure your OAuth token has the required scopes
Rate Limiting (429)
Problem: "Rate limit exceeded"
Solution:
- Google Search Console API has a limit of 1,200 queries per minute
- Reduce the frequency of requests
- Implement exponential backoff in your client
Site URL Encoding
When using resources with site URLs, the URL must be URL-encoded:
# Correct
gsc://sites/https%3A%2F%2Fexample.com%2F/analytics/summary
# Incorrect
gsc://sites/https://example.com//analytics/summary
Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
License
MIT License - see LICENSE file for details.
Resources
Support
For issues and questions:
- Open an issue on GitHub
- Check the FastMCP Discord
- Review Google Search Console API docs
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