gsc-mcp
Provides tools for querying Google Analytics 4 data such as organic landing pages, traffic sources, page performance, real-time users, and conversion funnels.
Provides tools for querying search analytics, inspecting URLs, managing sitemaps, submitting URLs for indexing, and running SEO analysis.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@gsc-mcpwhich pages are crawled but not indexed?"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
gsc-mcp
Google Search Console MCP server with 32 tools covering search analytics, URL inspection, the Google Indexing API, Google Analytics 4, and cross-platform GSC+GA4 analysis. Built on Python 3.11+ and FastMCP.
The main workflow it enables: ask Claude "which pages on my site are crawled but not indexed?" then "submit them for indexing", end to end, no manual Google Search Console tabs.
Why this exists
Two solid open-source projects cover parts of this problem:
AminForou/mcp-gsc (Python, 1k+ stars) has excellent search analytics, rich SEO tooling, and solid OAuth + Service Account auth. It does not include the Google Indexing API at all (no submit_url, no submit_batch). You can analyze your traffic but you cannot request reindexing.
Suganthan-Mohanadasan/Suganthans-GSC-MCP (Node.js/TypeScript) adds the Indexing API, but its submit_batch is a sequential for loop with a 100ms delay between requests, not a real HTTP batch. It also mixes plain-text and JSON outputs, hardcodes version strings that diverge from package.json, and has no retry logic.
This project takes the auth patterns and SEO tools from the first, the Indexing API scope from the second, and fixes the gaps in both.
Why Python instead of Go or Rust
The Google API Python client (google-api-python-client) is the official, best-maintained client for these APIs. It ships service.new_batch_http_request() natively, which is what makes true HTTP multipart batching possible without implementing the wire format by hand. The Go and Rust ecosystem for Google APIs relies on unofficial or auto-generated clients that do not expose this method. FastMCP also has first-class Python support with minimal boilerplate. The trade-off is startup latency (a few hundred ms vs near-zero for a compiled binary), but for a local MCP server called interactively by Claude that trade-off is irrelevant.
What changed vs the two inspirations
Feature | AminForou/mcp-gsc | Suganthan | gsc-mcp |
Google Indexing API | No | Yes (fake batch) | Yes (true HTTP batch) |
submit_batch | N/A | Sequential loop |
|
Token storage | pickle | pickle | JSON ( |
Retry on 429/5xx | No | No | Yes, exponential backoff |
Quota tracking | No | No | Yes, warns at 180/200 |
Output format | Mixed text+JSON | Mixed | 100% JSON + |
Related MCP server: mcp-seo-audit
Tools (32)
Category | Tool | Description |
Meta |
| List all available tools |
Properties |
| List all GSC properties |
Properties |
| Get details for a specific property |
Analytics |
| Query search performance data |
Analytics |
| Aggregate totals + top queries |
Analytics |
| Compare two consecutive periods |
Analytics |
| Performance broken down by page and query |
Analytics |
| Flexible query with custom dimensions and filters |
Analytics |
| Z-score anomaly detection on daily clicks |
SEO |
| Pages in positions 4-15 with CTR below benchmark |
SEO |
| Queries with declining clicks, with diagnosis |
SEO |
| Traffic concentration risks and ranking opportunities |
SEO |
| Queries in positions 8-15, one push away from page 1 |
SEO |
| Queries split across multiple pages (HHI conflict score) |
SEO |
| Queries with a click drop >= 80% vs the previous period |
Inspection |
| URL indexing status via URL Inspection API |
Inspection |
| Inspect up to 10 URLs at once |
Inspection |
| Inspect URLs and categorize by issue type |
Indexing |
| Request indexing for a single URL |
Indexing |
| Request indexing for multiple URLs (true HTTP batch) |
Sitemaps |
| List submitted sitemaps |
Sitemaps |
| Submit a sitemap URL |
Sitemaps |
| Fetch details for a single sitemap |
Sitemaps |
| Delete a submitted sitemap (with safety check) |
GA4 |
| Sessions and engagement for organic landing pages |
GA4 |
| Sessions and conversions by channel, source and medium |
GA4 |
| 7 metrics per page path, optional CONTAINS filter |
GA4 |
| Active users right now by screen, country and device |
GA4 |
| Device, country and user-type breakdowns in one batch call |
GA4 |
| Converting pages and event counts, optional event filter |
Cross |
| Ratio sessions GA4 / clics GSC pour détecter les tracking gaps |
Cross |
| Jointure GSC+GA4 par page avec opportunity score, triée par priorité |
Requirements
Python 3.11+
Google Cloud project with these APIs enabled:
Google Search Console API
Web Search Indexing API
Google Analytics Data API (for GA4 tools)
Credentials: OAuth Desktop app OR Service Account JSON
For the Indexing API: your account or service account needs Owner-level access in Search Console (Full access is not enough)
Indexing API default quota: 200 requests per day
Installation
uvx gsc-mcpOr with pip:
pip install gsc-mcpTo run from source:
git clone https://github.com/FlorianBruniaux/google-search-console-mcp
cd google-search-console-mcp
python3 -m venv .venv && source .venv/bin/activate
pip install -e .Configuration
Copy .env.example to .env and fill in the relevant variables.
OAuth (interactive, good for personal use)
export GSC_CREDENTIALS_PATH=/path/to/oauth-client-credentials.json
gsc-mcpThe first run opens a browser for Google login. The token is saved to your OS user data directory (~/.local/share/gsc-mcp/ on Linux, ~/Library/Application Support/gsc-mcp/ on macOS) as JSON files.
Service Account (recommended for automation and Claude Desktop)
export GSC_SERVICE_ACCOUNT_PATH=/path/to/service-account.json
export GSC_SKIP_OAUTH=true
gsc-mcpGA4 setup
GA4 tools use the same Service Account as GSC. Two steps to enable them:
Open GA4 Admin, go to Property Access Management, and add the service account email (the
client_emailfield in your SA JSON) with the Viewer role.Set the
GA4_PROPERTY_IDenvironment variable to your numeric property ID (e.g.123456789, visible in GA4 Admin under Property Settings). Theproperties/prefix is added automatically if omitted.
"env": {
"GSC_SERVICE_ACCOUNT_PATH": "/path/to/service-account.json",
"GA4_PROPERTY_ID": "123456789"
}GSC-only users are not affected: the GA4_PROPERTY_ID check runs lazily on the first GA4 tool call, never at startup.
Claude Desktop
Add to your claude_desktop_config.json:
{
"mcpServers": {
"gsc-mcp": {
"command": "python",
"args": ["-m", "gsc_mcp.server"],
"env": {
"GSC_SERVICE_ACCOUNT_PATH": "/absolute/path/to/service-account.json",
"GSC_SKIP_OAUTH": "true"
}
}
}
}Or, once published to PyPI:
{
"mcpServers": {
"gsc-mcp": {
"command": "uvx",
"args": ["gsc-mcp"],
"env": {
"GSC_SERVICE_ACCOUNT_PATH": "/absolute/path/to/service-account.json",
"GSC_SKIP_OAUTH": "true"
}
}
}
}Development
python3 -m venv .venv && source .venv/bin/activate
pip install -e ".[dev]"
pytest tests/ -v163+ tests, all mocked (no real Google API calls needed).
License
MIT
Maintenance
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