How I Connected Google Search Console to Claude Code with MCP

I wanted to analyze Google Search Console data without jumping between GSC, spreadsheets, and my codebase. So I connected GSC to Claude Code using Amin Forou's open-source mcp-gsc server. Now I can ask: Which high-impression queries are close to page one? Which ranking pages have low CTR? Are multiple pages competing for the same keyword? Which important URLs have indexing problems? Claude retrieves the relevant data, analyzes it alongside my code, and helps me decide what to change. How it works Claude Code ↓ MCP over stdio mcp-gsc running locally ↓ OAuth 2.0 Google Search Console API The MCP server converts Search Console operations into tools Claude can call. It supports performance analysis, URL inspection, sitemap management, period comparisons, and property discovery. I used OAuth so the server could access the same GSC properties as my Google account. 1. Create the Google Cloud test app Open the Google Cloud Console and create a dedicated project. Then: Go to APIs & Services → Library. Find and enable the Google Search Console API. Open Google Auth Platform. Configure the app name and support email under Branding. Set the audience to External and keep the app in Testing. Add your Google account under Test users. The authorized Google account must already have access to the Search Console property. The server requests this scope: https://www.googleapis.com/auth/webmasters This is the read/write Search Console scope. Destructive mcp-gsc operations remain disabled unless GSC_ALLOW_DESTRUCTIVE=true is explicitly set. Important: for an external app in Testing, Google normally expires the authorization and refresh token after seven days. If authentication suddenly stops, run the reauthentication tool and approve access again. 2. Download the OAuth client In Google Auth Platform → Clients: Create an OAuth client. Select Desktop app. Download the JSON file. Store it in a permanent private location. Example: /Users/yourname/Documents/credentials/gsc-client-secrets.json Never commit this file to Git. 3. Install mcp-gsc The simplest method uses uvx, which runs the package in an isolated Python environment. Install uv using its official installation guide, then verify it: uv --version uvx --version which uvx Keep the full path returned by which uvx. Claude Code may not inherit your terminal's PATH, so using only uvx can cause a spawn uvx ENOENT error. 4. Connect it to Claude Code Replace the example paths with absolute paths from your machine: claude mcp add-json --scope user gscServer '{ "type": "stdio", "command": "/Users/yourname/.local/bin/uvx", "args": ["mcp-search-console"], "env": { "GSC_OAUTH_CLIENT_SECRETS_FILE": "/Users/yourname/Documents/credentials/gsc-client-secrets.json" } }' I used user scope so the integration was available across my local projects without committing credential paths to a repository. Verify the configuration: claude mcp list claude mcp get gscServer 5. Authorize and test Start Claude Code and ask: Call the GSC get_capabilities tool and report the authentication status. The first request opens Google's OAuth flow in your browser. Sign in with the test-user account and approve access. Then ask: List every Search Console property I can access and show its exact identifier. Use the identifier returned by the API. Search Console has two formats: Domain property: sc-domain:example.com URL-prefix property: https://www.example.com/ The protocol, hostname, and trailing slash must match exactly for URL-prefix properties. Useful tools The server exposes tools including: get_performance_overview get_search_analytics get_advanced_search_analytics compare_search_periods get_search_by_page_query inspect_url_enhanced batch_url_inspection check_indexing_issues list_sitemaps_enhanced reauthenticate For recent dashboard-like data, keep the default GSC_DATA_STATE=all. For stable reporting with a short delay, use GSC_DATA_STATE=final. Prompts I use Find quick SEO opportunities For sc-domain:example.com, find non-branded queries with at least 500 impressions and positions from 11 to 20 in the last 28 days. Group them by ranking page and recommend whether to update an existing page or create a new one. Diagnose low CTR Find pages ranking in positions 1 to 10 with at least 1,000 impressions and CTR below 2%. Show their leading queries and suggest accurate title improvements. Compare performance Compare the latest 28 complete days with the previous 28 days. Separate changes caused by impressions, CTR, and position. Show the ten biggest winning and losing pages. Check indexing Inspect the ten highest-click landing pages. Flag canonical mismatches, robots restrictions, crawl failures, and pages missing from Google's index. Common problems Authentication fails after seven days: Your external OAuth app is still in Testing. Call reauthenticate and approve access again. spawn uvx ENOENT: Use the complete path returned by which uvx. Credentials file not found: Use an absolute path in GSC_OAUTH_CLIENT_SECRETS_FILE. Property returns 404: Run list_properties and copy the exact sc-domain: or URL-prefix value. No MCP tools appear: Check claude mcp list. Manual repository installations also require Python 3.11 or newer. Security notes Keep the client JSON and cached OAuth token outside your repository. Never publish or share their contents. Leave destructive operations disabled. Review MCP tool calls before approving them. Revoke the OAuth app from your Google Account if credentials are exposed. The result My SEO workflow changed from: GSC → CSV export → spreadsheet → codebase to: Search data → opportunity → page → code change → measurement The biggest benefit is not generating more SEO content. It is giving the coding assistant real search data so it can investigate the correct page before making a change. References mcp-gsc repository Search Console API documentation Google OAuth test-user documentation Claude Code MCP documentation Disclosure: I used AI to help edit this article. The setup is based on my own implementation and was manually verified.