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Google Search Console MCP Server

Google Search Console MCP Server

Google Search Console MCP Server

npm version npm downloads GitHub stars Licence Node version

MCP server Works with Claude Desktop and Claude Code Google Search Console API 29 tools Privacy: local first

An MCP server for Google Search Console that lets you ask Claude questions about your search data and get real answers. Not raw API rows. Actual analysis.

29 tools. OAuth or service account. Free and open source. Runs on your machine: your data goes straight from this computer to Google, and nothing passes through anyone else's servers.

https://github.com/user-attachments/assets/ef131907-4461-4c6a-8080-770f8162dbf2

Also on YouTube.

Full setup guide with screenshots: suganthan.com/blog/google-search-console-mcp-server/

v2.5.0 update (August 2026): new tool image_page_audit closes the image SEO loop. The v2.3 suite tells you which pages fail in image search; this one fetches those pages from your own site and tells you why: alt text, filenames, dimension attributes, lazy loading on the LCP image, formats and weights, the ~250x200 indexing minimum, ImageObject/licensable schema, max-image-preview, and the metadata inside the image files (camera EXIF to strip, IPTC to keep, DigitalSourceType on AI images). It only ever fetches the URLs you give it. Launch post with the whole 8-tool workflow on real client data: "One Page Earned 102,657 Image Impressions and 2 Clicks".

v2.4.0 update (August 2026): new tool genai_conversation_queries finds the AI conversations leaking into your query report. People reply to Google's AI with things like "yes, go on", Google logs every follow-up as a new query, and this tool sorts all of it into seven classified buckets with landing pages and a monthly timeline. Full method and findings: "Yes, Go On": The AI Conversations Leaking Into Your Search Console.

See it in action

"Audit the images on these pages"

Per-image findings from image_page_audit: alt status, filename, loading, weight and metadata per image, with an ordered fix list per page

"Which of my queries are actually AI conversations?"

Reply artefacts like yes and sure classified with impressions, clicks and landing pages

"How is my site doing?"

Site snapshot with period comparison

"What are my quick win keywords?"

Quick wins analysis showing positions 4-15 with opportunity scores

"Which pages are cannibalising each other?"

Cannibalisation detection across the site

"What content is slowly dying?"

Content decay detection over three consecutive periods

"Which pages lost traffic and why?"

Traffic drop diagnosis: ranking loss vs CTR collapse vs demand decline

"How does my CTR compare to benchmarks?"

CTR vs industry benchmarks by position

"How is my blog cluster performing?"

Topic cluster performance for a URL path pattern

Related MCP server: Google Search Console MCP Server

What you can ask

"What are my quick win keywords?"
"Which pages lost traffic this month and why?"
"What content is decaying?"
"Which pages are cannibalising each other?"
"Check for any SEO alerts in the last 7 days"
"Give me content recommendations"
"How does my CTR compare to benchmarks?"
"How is my /blog/ cluster performing?"
"Show me US mobile traffic for the last 90 days"
"Is /blog/my-post/ indexed? If not, why?"
"Generate a full performance report and save it"
"Show me a dashboard across all my sites"
"Submit this URL for indexing: https://mysite.com/new-post/"
"Batch submit all my new blog posts for indexing"
"List my sitemaps and their status"
"Verify that claim about my homepage clicks"

Quick start

One command setup (new in v2.3)

npx -y suganthan-gsc-mcp setup

The wizard signs you in with Google, verifies the connection with a live API call, lets you pick your property from a list, and writes the config for Claude Desktop and Claude Code. No config files to edit.

Read only by default: the standard consent screen asks for a single view permission. Choose full access during setup if you want the sitemap and URL submission tools.

For now you still need your own Google OAuth client JSON one time (steps 1 to 3 under Manual OAuth below); the wizard takes it from there. Built in Google sign in, with no Google Cloud steps at all, ships the moment Google finishes verifying the shared client.

Useful flags: --client desktop|code|both|print, --scopes readonly|full, --site <property>, --secrets <path>, --reauth, --force, --dry-run, --help.

One click desktop install

Prefer no terminal at all? Download the .mcpb bundle from the releases page and double click it. Claude Desktop installs the server with a small settings screen.

Option A: OAuth (manual)

  1. Create a Google Cloud project and enable the Search Console API

  2. Go to Credentials > Create Credentials > OAuth client ID, choose Desktop app

  3. Download the client secrets JSON

  4. Add to your Claude Desktop config (~/Library/Application Support/Claude/claude_desktop_config.json):

{
  "mcpServers": {
    "gsc": {
      "command": "npx",
      "args": ["-y", "suganthan-gsc-mcp"],
      "env": {
        "GSC_AUTH_MODE": "oauth",
        "GSC_OAUTH_SECRETS_FILE": "/path/to/client_secrets.json",
        "GSC_SITE_URL": "sc-domain:yoursite.com",
        "GSC_SCOPES": "readonly"
      }
    }
  }
}

First use opens a browser for Google sign in. Token is cached after that (locally, at ~/.gsc-mcp/). Set GSC_SCOPES to full if you want the submission tools; omit it and you get full access, matching pre 2.3 behaviour. Running from a git checkout instead of npm? Use "command": "node", "args": ["/path/to/Suganthans-GSC-MCP/dist/index.js"].

Option B: Service Account

  1. Create a Google Cloud project and enable the Search Console API

  2. Go to IAM & Admin > Service Accounts, create one, download the JSON key

  3. Add the service account email to your GSC property (Settings > Users and permissions > Full access)

  4. Add to your Claude Desktop config:

{
  "mcpServers": {
    "gsc": {
      "command": "node",
      "args": ["/path/to/Suganthans-GSC-MCP/dist/index.js"],
      "env": {
        "GSC_KEY_FILE": "/path/to/service-account.json",
        "GSC_SITE_URL": "sc-domain:yoursite.com"
      }
    }
  }
}

Generative AI (v2.4)

Google's Generative AI performance report has no API, no BigQuery export, and no searchAppearance value. But Google counts every AI Mode follow-up as a brand-new query and folds AI Mode and AI Overviews into the web search type, so AI-conversation exhaust leaks into the regular query dimension with real impressions, positions and clicks. This tool mines it.

Tool

What it answers

genai_conversation_queries

Which of your queries are actually AI-conversation exhaust: bare replies to the AI ("yes", "go on"), "what about X" pivot follow-ups, conversational questions, AI-visibility tracker probes, and full agent prompts logged as queries. Seven classified buckets with landing pages, plus a monthly timeline showing when reply-artefacts first appeared on your property

Indexing API (optional)

To use submit_url, submit_batch, and submit_sitemap:

  1. Enable the Web Search Indexing API in your Google Cloud console

  2. Your service account (or OAuth credentials) need owner-level access in Search Console

Note: Google officially says the Indexing API is for JobPosting and BroadcastEvent schema types. In practice, it processes requests for all page types.

Multi-site

For multiple properties, add GSC_SITE_URLS:

"env": {
  "GSC_SITE_URL": "sc-domain:primarysite.com",
  "GSC_SITE_URLS": "sc-domain:primarysite.com,sc-domain:secondsite.com"
}

You can also point a single query at any property your credentials can see without touching the config: advanced_search_analytics, genai_conversation_queries, and all 7 image-search analysis tools take an optional site_url parameter. "Which pages get image impressions but no clicks on sc-domain:secondsite.com?" just works.

All 29 tools

Analysis

Tool

What it answers

site_snapshot

How is the site doing overall? Clicks, impressions, CTR, position with period comparison

quick_wins

Keywords at positions 4-15 with high impressions, scored by opportunity

ctr_opportunities

Pages with high impressions but CTR below expected for their position

traffic_drops

What lost traffic, and whether it's a ranking loss, CTR collapse, or demand decline

content_gaps

Topics with search demand but no real content targeting them

cannibalization_check

Keywords where multiple pages compete against each other

content_decay

Pages declining across three consecutive 30-day periods

topic_cluster_performance

Aggregated performance for all pages matching a URL path pattern

ctr_vs_benchmark

Your actual CTR per position vs industry benchmarks

inspect_url

Is this URL indexed? Last crawl date, canonical, robots/noindex issues

check_alerts

Position drops, CTR collapses, click losses, disappeared pages. Severity-rated

content_recommendations

Prioritised actions: pages to update, content to create, pages to consolidate

advanced_search_analytics

Custom queries with flexible dimensions and filters

generate_report

Full markdown report saved to disk

multi_site_dashboard

Health check across all properties in one command

Image SEO (v2.3 + v2.5)

These tools pass type=image to the GSC Search Analytics API, which most third-party tools never expose. They cover the visual-search surface end-to-end.

Tool

What it answers

image_keyword_overview

Top image-search queries on the site, sorted by impressions, clicks, or position

image_search_quick_wins

Image queries at positions 4-15 with high impressions, scored by image-CTR opportunity. The CTR baseline is calibrated for image search, which runs roughly 5-6x lower than web at equivalent positions

compare_web_vs_image

Same query, side-by-side performance across web and image surfaces, with an impressions ratio that surfaces where image search carries disproportionate volume

image_pages_overview

Pages on the site ranked by image-search performance. Pairs with image_keyword_overview to map queries back to the pages carrying them

image_keyword_trends

Period-over-period deltas for image-search queries. Impressions delta and position delta (negative position delta means the query improved its average rank)

image_impressions_no_clicks

Query and page pairs earning meaningful image impressions but near-zero clicks. The textbook thumbnail-not-converting pattern

image_content_decay

Image-search version of content_decay. Pages losing image-search traffic across 3 consecutive 30-day periods, sorted by total click loss

image_page_audit

Fetches pages from your own site and audits every image on them: alt text, filenames, width/height attributes, lazy loading on the LCP candidate, srcset, format and weight, intrinsic dimensions vs the ~250x200 indexing minimum, ImageObject and licensable schema, max-image-preview, and in-file metadata (camera EXIF, IPTC editorial fields, XMP DigitalSourceType). The bridge from "which pages fail" to "why they fail" (v2.5)

Indexing

Tool

What it does

submit_url

Submit a URL to Google's Indexing API for crawling

submit_batch

Batch submit up to 200 URLs (daily quota)

submit_sitemap

Notify Google of a new or updated sitemap

list_sitemaps

All submitted sitemaps with status, errors, and indexed counts

Safety

Tool

What it does

verify_claim

Self-check: re-queries GSC data to verify a numeric claim before presenting it

What makes this different from other Google Search Console MCP servers

Analysis, not just API access. Most Google Search Console MCP servers wrap the raw API. This one ships with pre-built analysis: opportunity scoring, cannibalisation detection, decay tracking, CTR benchmarking, traffic drop diagnosis. You ask a question, it runs the analysis and tells you what to do.

Local and private. No hosted middleman, no account, no plan. The server runs on your machine, tokens are cached on your machine, and your Search Console data travels directly between your machine and Google. The developer operates no servers and receives nothing. Read only scope by default.

Hallucination guardrails. Every tool instructs Claude to base analysis only on returned data. Provenance metadata in every response. The verify_claim tool lets Claude fact-check its own numbers. Credit to Krinal Mehta for pushing this.

Visual dashboards. Results render as rich, interactive visualisations in Claude Desktop. Summary cards, colour coded indicators, bar charts, and tabbed sections. Not plain text dumps.

Fresh data. Uses dataState: 'all' so data matches the GSC dashboard, not 2-3 days stale.

Proactive, not reactive. Alerting, content recommendations, and scheduled reports catch problems before you think to look.

Environment variables

Variable

Required

Description

GSC_AUTH_MODE

No

oauth or service_account (default: service_account)

GSC_KEY_FILE

Service account mode

Path to service account JSON key

GSC_OAUTH_SECRETS_FILE

OAuth mode

Path to OAuth client secrets JSON

GSC_OAUTH_CLIENT_ID

OAuth mode (alt)

OAuth client ID

GSC_OAUTH_CLIENT_SECRET

OAuth mode (alt)

OAuth client secret

GSC_SITE_URL

Yes

Primary GSC property URL

GSC_SITE_URLS

No

Comma-separated list for multi-site

GSC_SCOPES

No

readonly or full (default: full). Read only keeps the Google consent to a single view permission; submission tools then explain how to upgrade

Full guide

Step-by-step setup with screenshots, use cases, and examples:

suganthan.com/blog/google-search-console-mcp-server/

Changelog

v2.5.1 Three fixes from the issue queue. The sitemaps tools now call sc-domain: properties as-is, which the Sitemaps API supports and always has; the old URL-prefix rewrite manufactured a 403, blamed the API for it, and on some accounts silently returned a stale URL-prefix property's sitemap list instead of the domain property's. The rewrite survives only as a fallback for accounts whose permission genuinely lives on a URL-prefix property. Credit to pauljlange for proving the premise wrong with raw API calls. Service-account mode now requests the same scope set as the OAuth flow, so submit_url and submit_batch work with service accounts and the GSC_SCOPES=readonly tier applies there too; the OAuth half of this shipped earlier via tomschmidty12-sys's PR, after stuli1989 reported it and sent the first fix for both modes in #3. And the Google client libraries are bumped (googleapis 144 to 176, google-auth-library 10, gaxios 7) so token fetches use Node's native fetch; the old node-fetch path failed to decompress Google's gzip token responses on Node 22 and newer, which broke service accounts, most visibly on Windows. Credit to wilotas for the full diagnosis and the verified fix. Also fixed: the one-click desktop bundle. Every previous .mcpb shipped without the googleapis package internals (the packer silently pruned them), so the extension could never start, and "Unable to connect to extension server" was this bug, not your config. The v2.5.1 bundle carries the complete production dependency tree and was runtime-tested against the live API before upload, which is why it is bigger. Credit to VeloWulf for the report.

v2.5.0 Image page audit. image_page_audit fetches up to 5 pages from your own site and audits every image on them against the on-page factors that decide image-search performance: missing, empty, generic, filename-as-alt or duplicate alt text, camera-default and stock-agency-default filenames (shutterstock_524347192.jpg tells Google nothing), missing width/height attributes, lazy loading on the LCP candidate, srcset coverage, file format and weight (flags photos shipped as PNG and anything over 500KB), intrinsic dimensions against Google's ~250x200 indexing minimum, ImageObject and licensable-field schema, primaryImageOfPage, max-image-preview, inline background images, and the metadata inside the image files via exifr: camera EXIF and GPS that should be stripped, IPTC Creator/Copyright/Caption that should survive your CMS, and XMP DigitalSourceType on AI-generated images. Returns per-image findings, page-level checks, and an ordered top_fixes list. Pairs with image_impressions_no_clicks and image_search_quick_wins: those name the pages, this names the reasons. Fetches only the URLs it is given, so the privacy model is unchanged: your data goes to Google and your own site and nowhere else. New dependencies: node-html-parser, image-size, exifr (all pure JS, no native builds). The 7 image-search analysis tools also gain the optional site_url override that advanced_search_analytics already had, so any of them can be pointed at any property your credentials can see without editing the config. Launch post with the full workflow on real client data: "One Page Earned 102,657 Image Impressions and 2 Clicks".

Per-image findings from image_page_audit

v2.4.0 Generative AI conversation queries. genai_conversation_queries finds the AI conversation fragments hiding in your regular query data and sorts them into seven kinds: reply artefacts ("yes", "go on"), pivot follow-ups ("what about resend?"), conversational questions, tracker probes, agent harnesses, pasted strings, and a review pile. Google counts every AI Mode follow-up as a brand new query, so these rows carry real impressions, positions and clicks, and the dedicated Generative AI report has no query view, which makes this the only query-level AI evidence available anywhere. One call classifies sixteen months of your queries, attaches landing pages via query and page grouping, and returns a monthly reply-artefact timeline. Plain Search Analytics API, no BigQuery, no new permissions. Full method and findings: the launch post. Sparked by Anastasia Kourou surfacing the queries with John Mueller confirming the mechanism, and by Ross Tavendale asking how to reverse engineer it.

Reply artefact queries classified by the new tool

v2.3.0 Image SEO suite and one command setup. 7 new tools that pass type=image to the GSC Search Analytics API, plus a type parameter on advanced_search_analytics covering all 6 GSC search surfaces (web, image, video, news, discover, googleNews). The image-search surface was invisible to most third-party SEO tools because they default to type=web and never expose the others; v2.3 makes it queryable end-to-end. Also new: npx suganthan-gsc-mcp setup, a wizard that signs you in, verifies the connection with a live call, and writes your Claude Desktop and Claude Code configs; a read only scope tier (GSC_SCOPES=readonly, now the setup default) so the standard consent asks for one view permission; and a one click Claude Desktop bundle (.mcpb) on the releases page.

v2.2.2 Published to npm as suganthan-gsc-mcp. Config can now use npx instead of a local checkout path.

v2.2.1 Fixed OAuth EADDRINUSE crash when multiple tool calls triggered concurrent authentication flows. The server now reuses the active auth session instead of spawning duplicate listeners. Thanks to Rushabh Rathod for finding and reporting this.

v2.2.0 Visual dashboard rendering. All analysis tools now produce rich, interactive visualisations in Claude Desktop with summary cards, colour coded indicators, bar charts, and tabbed sections instead of plain text output. No reinstall needed, just restart Claude Desktop.

Visual dashboard rendering in Claude Desktop

v2.1.0 Added Indexing API tools: submit_url, submit_batch, submit_sitemap, list_sitemaps. Request Google to crawl and index pages directly from Claude.

v2.0.0 Added OAuth authentication, advanced search analytics, check_alerts, content_recommendations, generate_report, multi_site_dashboard, verify_claim. Server grew from 10 to 16 tools.

v1.1.0 Added hallucination guardrails: explicit prompts in tool descriptions, data provenance metadata in responses, and verify_claim self-checking tool. Thanks to Krinal Mehta for the feedback.

v1.0.0 Initial release with 10 analysis tools and service account authentication.

Licence

Apache 2.0. See LICENSE and NOTICE for details. Use it, fork it, build on it. Just keep the attribution.


Built by Suganthan Mohanadasan

I write about organic search, AI, and the tools I build on suganthan.com.

Posts about this server

Post

What it covers

Google Search Console MCP setup guide

Step by step setup with screenshots, for OAuth and service accounts

"Yes, Go On": The AI Conversations Leaking Into Your Search Console

The research behind genai_conversation_queries (v2.4)

One Page Earned 102,657 Image Impressions and 2 Clicks

The image SEO tools on real client data (v2.3 and v2.5)

How my MCP calculates average position

The maths behind every position figure, and how to make Claude prove a number

Outgrowing the Search Console API?

The BigQuery MCP Server reads your Search Console bulk export instead of the API, so large sites keep the rows the API cuts and you can see how much of your traffic sits behind anonymised queries. It has 33 tools, including ML forecasting, anomaly detection, and GA4 revenue per keyword. Setup guide.

Follow along

suganthan.com Newsletter Suganthan Mohanadasan on LinkedIn Follow @suganthan on X Suganthan Mohanadasan on GitHub Follow Suganthan on Google

If you find it useful, star it.

Available Tools

29 tools
advanced_search_analyticsA

Run a custom search analytics query with flexible dimensions and filters. Supports country, device, query, and page filtering, plus search type (web/image/video/news/discover/googleNews). For power users who need specific data cuts. IMPORTANT: Base your analysis ONLY on the data returned. Report exact numbers from the results. Do not speculate about causes (e.g. algorithm updates, competitor actions) unless the data explicitly supports it. If the data does not contain enough information to answer a question, say so clearly rather than guessing. PRESENTATION: Always present these results as a rich, interactive visualization using artifacts. Use summary cards for key metrics, colour-coded indicators for severity or change direction (green for positive, red for negative), bar charts or sparklines for comparisons, and tabbed sections to organise different categories of results. Make the output visually scannable and dashboard-like rather than plain text or raw tables. POSITION: position is an impression-weighted average over real impressions, blended across queries, devices and countries. It is not a rank-tracker rank. Deep positions are only recorded when a user actually reaches that part of the results, so values beyond page one rest on sparse data. Treat absolute positions as directional and prefer position deltas between periods when judging change.

Inputs: days, filters, order_by, site_url, +4 more.

cannibalization_checkA

Find keywords where multiple pages from your site compete against each other. Shows which page ranks higher, the position gap, and combined impressions being split. IMPORTANT: Base your analysis ONLY on the data returned. Report exact numbers from the results. Do not speculate about causes (e.g. algorithm updates, competitor actions) unless the data explicitly supports it. If the data does not contain enough information to answer a question, say so clearly rather than guessing. PRESENTATION: Always present these results as a rich, interactive visualization using artifacts. Use summary cards for key metrics, colour-coded indicators for severity or change direction (green for positive, red for negative), bar charts or sparklines for comparisons, and tabbed sections to organise different categories of results. Make the output visually scannable and dashboard-like rather than plain text or raw tables. POSITION: position is an impression-weighted average over real impressions, blended across queries, devices and countries. It is not a rank-tracker rank. Deep positions are only recorded when a user actually reaches that part of the results, so values beyond page one rest on sparse data. Treat absolute positions as directional and prefer position deltas between periods when judging change.

Inputs: days, min_impressions.

check_alertsA

Check for SEO alerts: position drops, CTR collapses, click losses, and pages that disappeared from search results. Returns severity-rated alerts so you know what needs attention first. IMPORTANT: Base your analysis ONLY on the data returned. Report exact numbers from the results. Do not speculate about causes (e.g. algorithm updates, competitor actions) unless the data explicitly supports it. If the data does not contain enough information to answer a question, say so clearly rather than guessing. PRESENTATION: Always present these results as a rich, interactive visualization using artifacts. Use summary cards for key metrics, colour-coded indicators for severity or change direction (green for positive, red for negative), bar charts or sparklines for comparisons, and tabbed sections to organise different categories of results. Make the output visually scannable and dashboard-like rather than plain text or raw tables. POSITION: position is an impression-weighted average over real impressions, blended across queries, devices and countries. It is not a rank-tracker rank. Deep positions are only recorded when a user actually reaches that part of the results, so values beyond page one rest on sparse data. Treat absolute positions as directional and prefer position deltas between periods when judging change.

Inputs: days, ctr_drop_threshold, click_drop_threshold, position_drop_threshold.

compare_web_vs_imageA

For each query, returns side-by-side performance across web and image search. Two GSC API calls joined on query, with an impressions ratio that surfaces where image search carries disproportionate volume relative to web. IMPORTANT: Base your analysis ONLY on the data returned. Report exact numbers from the results. Do not speculate about causes (e.g. algorithm updates, competitor actions) unless the data explicitly supports it. If the data does not contain enough information to answer a question, say so clearly rather than guessing. PRESENTATION: Always present these results as a rich, interactive visualization using artifacts. Use summary cards for key metrics, colour-coded indicators for severity or change direction (green for positive, red for negative), bar charts or sparklines for comparisons, and tabbed sections to organise different categories of results. Make the output visually scannable and dashboard-like rather than plain text or raw tables. POSITION: position is an impression-weighted average over real impressions, blended across queries, devices and countries. It is not a rank-tracker rank. Deep positions are only recorded when a user actually reaches that part of the results, so values beyond page one rest on sparse data. Treat absolute positions as directional and prefer position deltas between periods when judging change.

Inputs: days, site_url, row_limit, min_combined_impressions.

content_decayA

Find pages that are slowly dying with consistent traffic decline over three consecutive 30-day periods. One bad month is noise; three consecutive bad months is a problem. IMPORTANT: Base your analysis ONLY on the data returned. Report exact numbers from the results. Do not speculate about causes (e.g. algorithm updates, competitor actions) unless the data explicitly supports it. If the data does not contain enough information to answer a question, say so clearly rather than guessing. PRESENTATION: Always present these results as a rich, interactive visualization using artifacts. Use summary cards for key metrics, colour-coded indicators for severity or change direction (green for positive, red for negative), bar charts or sparklines for comparisons, and tabbed sections to organise different categories of results. Make the output visually scannable and dashboard-like rather than plain text or raw tables. POSITION: position is an impression-weighted average over real impressions, blended across queries, devices and countries. It is not a rank-tracker rank. Deep positions are only recorded when a user actually reaches that part of the results, so values beyond page one rest on sparse data. Treat absolute positions as directional and prefer position deltas between periods when judging change.

Inputs: no named parameters.

content_gapsA

Find topics you should create content for. Returns queries where you get impressions but rank beyond position 20, meaning there is search demand but no real content targeting it. IMPORTANT: Base your analysis ONLY on the data returned. Report exact numbers from the results. Do not speculate about causes (e.g. algorithm updates, competitor actions) unless the data explicitly supports it. If the data does not contain enough information to answer a question, say so clearly rather than guessing. PRESENTATION: Always present these results as a rich, interactive visualization using artifacts. Use summary cards for key metrics, colour-coded indicators for severity or change direction (green for positive, red for negative), bar charts or sparklines for comparisons, and tabbed sections to organise different categories of results. Make the output visually scannable and dashboard-like rather than plain text or raw tables. POSITION: position is an impression-weighted average over real impressions, blended across queries, devices and countries. It is not a rank-tracker rank. Deep positions are only recorded when a user actually reaches that part of the results, so values beyond page one rest on sparse data. Treat absolute positions as directional and prefer position deltas between periods when judging change.

Inputs: days, min_position, min_impressions.

content_recommendationsA

Get actionable content recommendations by cross-referencing quick wins, content gaps, and cannibalisation data. Returns prioritised actions: pages to update, content to create, and pages to consolidate. IMPORTANT: Base your analysis ONLY on the data returned. Report exact numbers from the results. Do not speculate about causes (e.g. algorithm updates, competitor actions) unless the data explicitly supports it. If the data does not contain enough information to answer a question, say so clearly rather than guessing. PRESENTATION: Always present these results as a rich, interactive visualization using artifacts. Use summary cards for key metrics, colour-coded indicators for severity or change direction (green for positive, red for negative), bar charts or sparklines for comparisons, and tabbed sections to organise different categories of results. Make the output visually scannable and dashboard-like rather than plain text or raw tables.

Inputs: days, max_recommendations.

ctr_opportunitiesA

Find pages with high impressions but CTR significantly below expected for their position. These are title/meta description optimisation candidates. IMPORTANT: Base your analysis ONLY on the data returned. Report exact numbers from the results. Do not speculate about causes (e.g. algorithm updates, competitor actions) unless the data explicitly supports it. If the data does not contain enough information to answer a question, say so clearly rather than guessing. PRESENTATION: Always present these results as a rich, interactive visualization using artifacts. Use summary cards for key metrics, colour-coded indicators for severity or change direction (green for positive, red for negative), bar charts or sparklines for comparisons, and tabbed sections to organise different categories of results. Make the output visually scannable and dashboard-like rather than plain text or raw tables. POSITION: position is an impression-weighted average over real impressions, blended across queries, devices and countries. It is not a rank-tracker rank. Deep positions are only recorded when a user actually reaches that part of the results, so values beyond page one rest on sparse data. Treat absolute positions as directional and prefer position deltas between periods when judging change.

Inputs: days, min_impressions.

ctr_vs_benchmarkA

Compare your actual CTR per page against industry benchmarks by position. Flags pages significantly underperforming for their ranking position. IMPORTANT: Base your analysis ONLY on the data returned. Report exact numbers from the results. Do not speculate about causes (e.g. algorithm updates, competitor actions) unless the data explicitly supports it. If the data does not contain enough information to answer a question, say so clearly rather than guessing. PRESENTATION: Always present these results as a rich, interactive visualization using artifacts. Use summary cards for key metrics, colour-coded indicators for severity or change direction (green for positive, red for negative), bar charts or sparklines for comparisons, and tabbed sections to organise different categories of results. Make the output visually scannable and dashboard-like rather than plain text or raw tables. POSITION: position is an impression-weighted average over real impressions, blended across queries, devices and countries. It is not a rank-tracker rank. Deep positions are only recorded when a user actually reaches that part of the results, so values beyond page one rest on sparse data. Treat absolute positions as directional and prefer position deltas between periods when judging change.

Inputs: days, min_impressions.

genai_conversation_queriesA

Surface AI-conversation exhaust hiding in your regular query data: bare replies to Google's AI ('yes', 'go on'), 'what about X' pivot follow-ups, conversational questions, AI-visibility tracker probes, and full agent prompts logged as queries. Google counts every AI Mode follow-up as a new query and folds AI Mode/AI Overviews into the web search type, so these fragments carry real impressions, positions and clicks. The dedicated Generative AI report has no query dimension; this is the only query-level AI evidence available anywhere. Classifies every match into seven buckets with landing pages, plus a monthly timeline showing when reply-artefacts first appeared on your site. Treat probe and harness buckets as machine traffic, not demand. IMPORTANT: Base your analysis ONLY on the data returned. Report exact numbers from the results. Do not speculate about causes (e.g. algorithm updates, competitor actions) unless the data explicitly supports it. If the data does not contain enough information to answer a question, say so clearly rather than guessing. PRESENTATION: Always present these results as a rich, interactive visualization using artifacts. Use summary cards for key metrics, colour-coded indicators for severity or change direction (green for positive, red for negative), bar charts or sparklines for comparisons, and tabbed sections to organise different categories of results. Make the output visually scannable and dashboard-like rather than plain text or raw tables. POSITION: position is an impression-weighted average over real impressions, blended across queries, devices and countries. It is not a rank-tracker rank. Deep positions are only recorded when a user actually reaches that part of the results, so values beyond page one rest on sparse data. Treat absolute positions as directional and prefer position deltas between periods when judging change.

Inputs: days, site_url, min_impressions, include_timeline, +1 more.

generate_reportA

Generate a comprehensive markdown performance report. Covers site snapshot, alerts, quick wins, traffic drops, content decay, and recommendations. Saves to disk for weekly reviews or scheduled reporting. IMPORTANT: Base your analysis ONLY on the data returned. Report exact numbers from the results. Do not speculate about causes (e.g. algorithm updates, competitor actions) unless the data explicitly supports it. If the data does not contain enough information to answer a question, say so clearly rather than guessing. PRESENTATION: Always present these results as a rich, interactive visualization using artifacts. Use summary cards for key metrics, colour-coded indicators for severity or change direction (green for positive, red for negative), bar charts or sparklines for comparisons, and tabbed sections to organise different categories of results. Make the output visually scannable and dashboard-like rather than plain text or raw tables.

Inputs: days, output_path, include_sections.

image_content_decayA

Image-search version of content_decay. Three 30-day windows, flags pages with a consistent decline across all three. Defaults to a lower minimum click threshold than the web equivalent because image search produces lower click volumes overall. IMPORTANT: Base your analysis ONLY on the data returned. Report exact numbers from the results. Do not speculate about causes (e.g. algorithm updates, competitor actions) unless the data explicitly supports it. If the data does not contain enough information to answer a question, say so clearly rather than guessing. PRESENTATION: Always present these results as a rich, interactive visualization using artifacts. Use summary cards for key metrics, colour-coded indicators for severity or change direction (green for positive, red for negative), bar charts or sparklines for comparisons, and tabbed sections to organise different categories of results. Make the output visually scannable and dashboard-like rather than plain text or raw tables. POSITION: position is an impression-weighted average over real impressions, blended across queries, devices and countries. It is not a rank-tracker rank. Deep positions are only recorded when a user actually reaches that part of the results, so values beyond page one rest on sparse data. Treat absolute positions as directional and prefer position deltas between periods when judging change.

Inputs: site_url, min_period3_clicks.

image_impressions_no_clicksA

Surfaces query and page pairs that earn meaningful image-search impressions but effectively zero clicks. The textbook 'thumbnail is not converting' pattern. Defaults tuned for image search, which runs at much higher impression volumes per page than web. IMPORTANT: Base your analysis ONLY on the data returned. Report exact numbers from the results. Do not speculate about causes (e.g. algorithm updates, competitor actions) unless the data explicitly supports it. If the data does not contain enough information to answer a question, say so clearly rather than guessing. PRESENTATION: Always present these results as a rich, interactive visualization using artifacts. Use summary cards for key metrics, colour-coded indicators for severity or change direction (green for positive, red for negative), bar charts or sparklines for comparisons, and tabbed sections to organise different categories of results. Make the output visually scannable and dashboard-like rather than plain text or raw tables. POSITION: position is an impression-weighted average over real impressions, blended across queries, devices and countries. It is not a rank-tracker rank. Deep positions are only recorded when a user actually reaches that part of the results, so values beyond page one rest on sparse data. Treat absolute positions as directional and prefer position deltas between periods when judging change.

Inputs: days, site_url, row_limit, max_clicks, +1 more.

image_keyword_overviewA

Top image-search keywords for the site, sorted by impressions, clicks, or position. Filtered to type=image so it returns only what surfaces in Google Images, not web search. IMPORTANT: Base your analysis ONLY on the data returned. Report exact numbers from the results. Do not speculate about causes (e.g. algorithm updates, competitor actions) unless the data explicitly supports it. If the data does not contain enough information to answer a question, say so clearly rather than guessing. PRESENTATION: Always present these results as a rich, interactive visualization using artifacts. Use summary cards for key metrics, colour-coded indicators for severity or change direction (green for positive, red for negative), bar charts or sparklines for comparisons, and tabbed sections to organise different categories of results. Make the output visually scannable and dashboard-like rather than plain text or raw tables. POSITION: position is an impression-weighted average over real impressions, blended across queries, devices and countries. It is not a rank-tracker rank. Deep positions are only recorded when a user actually reaches that part of the results, so values beyond page one rest on sparse data. Treat absolute positions as directional and prefer position deltas between periods when judging change.

Inputs: days, order_by, site_url, row_limit, +1 more.

image_page_auditA

Fetches pages from YOUR OWN site and audits every image on them for the on-page factors that drive image-search performance: missing/empty/generic/duplicate alt text, non-descriptive filenames, missing width/height attributes, lazy loading on the LCP candidate, srcset coverage, file format and weight, intrinsic dimensions vs Google's ~250x200 indexing minimum, ImageObject and licensable schema, max-image-preview, inline background images, and the metadata inside the image files (camera EXIF and GPS that should be stripped, IPTC Creator/Copyright/Caption that should survive, XMP DigitalSourceType on AI-generated images). Feed it URLs straight from image_impressions_no_clicks or image_search_quick_wins to turn 'which pages fail' into 'why they fail'. Only fetches the URLs given; no third-party service involved. Returns a per-image findings table, page-level checks, and an ordered top_fixes list. IMPORTANT: Base your analysis ONLY on the data returned. Report exact numbers from the results. Do not speculate about causes (e.g. algorithm updates, competitor actions) unless the data explicitly supports it. If the data does not contain enough information to answer a question, say so clearly rather than guessing. PRESENTATION: Always present these results as a rich, interactive visualization using artifacts. Use summary cards for key metrics, colour-coded indicators for severity or change direction (green for positive, red for negative), bar charts or sparklines for comparisons, and tabbed sections to organise different categories of results. Make the output visually scannable and dashboard-like rather than plain text or raw tables.

Inputs: urls (required), fetch_metadata, max_images_per_page, max_images_reported.

image_pages_overviewA

Pages on the site ranked by image-search performance. Tells you which pages are actually surfacing in Google Images and which are not. Pairs with image_keyword_overview to map ranking queries back to the pages carrying them. IMPORTANT: Base your analysis ONLY on the data returned. Report exact numbers from the results. Do not speculate about causes (e.g. algorithm updates, competitor actions) unless the data explicitly supports it. If the data does not contain enough information to answer a question, say so clearly rather than guessing. PRESENTATION: Always present these results as a rich, interactive visualization using artifacts. Use summary cards for key metrics, colour-coded indicators for severity or change direction (green for positive, red for negative), bar charts or sparklines for comparisons, and tabbed sections to organise different categories of results. Make the output visually scannable and dashboard-like rather than plain text or raw tables. POSITION: position is an impression-weighted average over real impressions, blended across queries, devices and countries. It is not a rank-tracker rank. Deep positions are only recorded when a user actually reaches that part of the results, so values beyond page one rest on sparse data. Treat absolute positions as directional and prefer position deltas between periods when judging change.

Inputs: days, order_by, site_url, row_limit, +1 more.

image_search_quick_winsA

Find image-search queries ranking at positions 4-15 with high impressions, sorted by estimated traffic gain if they reach position 3. Uses an image-search CTR baseline calibrated to the lower CTRs typical of Google Images. IMPORTANT: Base your analysis ONLY on the data returned. Report exact numbers from the results. Do not speculate about causes (e.g. algorithm updates, competitor actions) unless the data explicitly supports it. If the data does not contain enough information to answer a question, say so clearly rather than guessing. PRESENTATION: Always present these results as a rich, interactive visualization using artifacts. Use summary cards for key metrics, colour-coded indicators for severity or change direction (green for positive, red for negative), bar charts or sparklines for comparisons, and tabbed sections to organise different categories of results. Make the output visually scannable and dashboard-like rather than plain text or raw tables. POSITION: position is an impression-weighted average over real impressions, blended across queries, devices and countries. It is not a rank-tracker rank. Deep positions are only recorded when a user actually reaches that part of the results, so values beyond page one rest on sparse data. Treat absolute positions as directional and prefer position deltas between periods when judging change.

Inputs: days, site_url, max_position, min_impressions.

inspect_urlA

Check if a URL is indexed and why or why not. Returns indexing status, last crawl date, canonical info, robots/noindex issues, and mobile usability in one answer. IMPORTANT: Base your analysis ONLY on the data returned. Report exact numbers from the results. Do not speculate about causes (e.g. algorithm updates, competitor actions) unless the data explicitly supports it. If the data does not contain enough information to answer a question, say so clearly rather than guessing. PRESENTATION: Always present these results as a rich, interactive visualization using artifacts. Use summary cards for key metrics, colour-coded indicators for severity or change direction (green for positive, red for negative), bar charts or sparklines for comparisons, and tabbed sections to organise different categories of results. Make the output visually scannable and dashboard-like rather than plain text or raw tables.

Inputs: url (required).

list_sitemapsA

List all sitemaps submitted for the site, with status, errors, warnings, and indexed page counts. IMPORTANT: Base your analysis ONLY on the data returned. Report exact numbers from the results. Do not speculate about causes (e.g. algorithm updates, competitor actions) unless the data explicitly supports it. If the data does not contain enough information to answer a question, say so clearly rather than guessing.

Inputs: no named parameters.

multi_site_dashboardA

Health check across multiple GSC properties in one view. Shows clicks, impressions, CTR, and position for each site with period comparison and health status. Agency essential. IMPORTANT: Base your analysis ONLY on the data returned. Report exact numbers from the results. Do not speculate about causes (e.g. algorithm updates, competitor actions) unless the data explicitly supports it. If the data does not contain enough information to answer a question, say so clearly rather than guessing. PRESENTATION: Always present these results as a rich, interactive visualization using artifacts. Use summary cards for key metrics, colour-coded indicators for severity or change direction (green for positive, red for negative), bar charts or sparklines for comparisons, and tabbed sections to organise different categories of results. Make the output visually scannable and dashboard-like rather than plain text or raw tables. POSITION: position is an impression-weighted average over real impressions, blended across queries, devices and countries. It is not a rank-tracker rank. Deep positions are only recorded when a user actually reaches that part of the results, so values beyond page one rest on sparse data. Treat absolute positions as directional and prefer position deltas between periods when judging change.

Inputs: days, site_urls.

quick_winsA

Find keywords you're almost ranking for that could be pushed to page one. Returns queries at positions 4-15 with high impressions, sorted by traffic opportunity. IMPORTANT: Base your analysis ONLY on the data returned. Report exact numbers from the results. Do not speculate about causes (e.g. algorithm updates, competitor actions) unless the data explicitly supports it. If the data does not contain enough information to answer a question, say so clearly rather than guessing. PRESENTATION: Always present these results as a rich, interactive visualization using artifacts. Use summary cards for key metrics, colour-coded indicators for severity or change direction (green for positive, red for negative), bar charts or sparklines for comparisons, and tabbed sections to organise different categories of results. Make the output visually scannable and dashboard-like rather than plain text or raw tables. POSITION: position is an impression-weighted average over real impressions, blended across queries, devices and countries. It is not a rank-tracker rank. Deep positions are only recorded when a user actually reaches that part of the results, so values beyond page one rest on sparse data. Treat absolute positions as directional and prefer position deltas between periods when judging change.

Inputs: days, max_position, min_impressions.

site_snapshotA

Get a quick overview of how the site is performing. Returns total clicks, impressions, CTR, and position with a comparison to the prior period. IMPORTANT: Base your analysis ONLY on the data returned. Report exact numbers from the results. Do not speculate about causes (e.g. algorithm updates, competitor actions) unless the data explicitly supports it. If the data does not contain enough information to answer a question, say so clearly rather than guessing. PRESENTATION: Always present these results as a rich, interactive visualization using artifacts. Use summary cards for key metrics, colour-coded indicators for severity or change direction (green for positive, red for negative), bar charts or sparklines for comparisons, and tabbed sections to organise different categories of results. Make the output visually scannable and dashboard-like rather than plain text or raw tables. POSITION: position is an impression-weighted average over real impressions, blended across queries, devices and countries. It is not a rank-tracker rank. Deep positions are only recorded when a user actually reaches that part of the results, so values beyond page one rest on sparse data. Treat absolute positions as directional and prefer position deltas between periods when judging change.

Inputs: days.

submit_batchA

Submit up to 200 URLs to Google's Indexing API in one go. Daily quota is 200 URL notifications. Use for bulk indexing requests after publishing multiple pages or a site-wide update. IMPORTANT: Base your analysis ONLY on the data returned. Report exact numbers from the results. Do not speculate about causes (e.g. algorithm updates, competitor actions) unless the data explicitly supports it. If the data does not contain enough information to answer a question, say so clearly rather than guessing.

Inputs: urls (required), action.

submit_sitemapA

Notify Google of a new or updated sitemap. Triggers Google to recrawl the sitemap and discover new pages. IMPORTANT: Base your analysis ONLY on the data returned. Report exact numbers from the results. Do not speculate about causes (e.g. algorithm updates, competitor actions) unless the data explicitly supports it. If the data does not contain enough information to answer a question, say so clearly rather than guessing.

Inputs: sitemap_url.

submit_urlA

Submit a URL to Google's Indexing API to request crawling and indexing. Works for notifying Google of new or updated content. Note: Google officially supports this for JobPosting/BroadcastEvent schema but processes all page types. IMPORTANT: Base your analysis ONLY on the data returned. Report exact numbers from the results. Do not speculate about causes (e.g. algorithm updates, competitor actions) unless the data explicitly supports it. If the data does not contain enough information to answer a question, say so clearly rather than guessing.

Inputs: url (required), action.

topic_cluster_performanceA

See how a group of pages performs as a whole. Aggregates clicks, impressions, CTR, and position for all pages matching a URL path pattern, plus top 5 pages and queries. IMPORTANT: Base your analysis ONLY on the data returned. Report exact numbers from the results. Do not speculate about causes (e.g. algorithm updates, competitor actions) unless the data explicitly supports it. If the data does not contain enough information to answer a question, say so clearly rather than guessing. PRESENTATION: Always present these results as a rich, interactive visualization using artifacts. Use summary cards for key metrics, colour-coded indicators for severity or change direction (green for positive, red for negative), bar charts or sparklines for comparisons, and tabbed sections to organise different categories of results. Make the output visually scannable and dashboard-like rather than plain text or raw tables. POSITION: position is an impression-weighted average over real impressions, blended across queries, devices and countries. It is not a rank-tracker rank. Deep positions are only recorded when a user actually reaches that part of the results, so values beyond page one rest on sparse data. Treat absolute positions as directional and prefer position deltas between periods when judging change.

Inputs: path_pattern (required), days.

traffic_dropsA

Find pages that lost the most traffic recently. Compares current period vs prior period and diagnoses whether each drop is a ranking loss, CTR collapse, or demand decline. IMPORTANT: Base your analysis ONLY on the data returned. Report exact numbers from the results. Do not speculate about causes (e.g. algorithm updates, competitor actions) unless the data explicitly supports it. If the data does not contain enough information to answer a question, say so clearly rather than guessing. PRESENTATION: Always present these results as a rich, interactive visualization using artifacts. Use summary cards for key metrics, colour-coded indicators for severity or change direction (green for positive, red for negative), bar charts or sparklines for comparisons, and tabbed sections to organise different categories of results. Make the output visually scannable and dashboard-like rather than plain text or raw tables. POSITION: position is an impression-weighted average over real impressions, blended across queries, devices and countries. It is not a rank-tracker rank. Deep positions are only recorded when a user actually reaches that part of the results, so values beyond page one rest on sparse data. Treat absolute positions as directional and prefer position deltas between periods when judging change.

Inputs: days.

verify_claimA

Verify a specific numeric claim against live GSC data. Use this to self-check your analysis before presenting findings. Pass the claim text, the metric to check, the expected value, and optionally a URL or query to filter by. Returns whether the claim is verified and any discrepancy found.

Inputs: claim (required), metric (required), expected_value (required), url, +2 more.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

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    TDQS

    A3.7/5.0

    Scored across 29 tools

    Disambiguation4/5

    Each tool has a clear analytical target: URL inspection, site snapshot, quick wins, traffic drops, content gaps, cannibalization, image-search variants, etc. The main overlap is among synthesizing tools like check_alerts, content_recommendations, and generate_report, but their descriptions clearly frame them as aggregators. Advanced_search_analytics could duplicate several specialized tools, but it is positioned as the low-level custom query option.

    Naming Consistency3/5

    Tool names are consistently snake_case and readable, and operative actions follow a clear submit_/ist_ pattern. However, most analytical tools use noun phrases like quick_wins, content_gaps, and image_content_decay rather than a uniform verb_noun convention, and compare_web_vs_image stands out as a different verb style.

    Tool Count2/5

    29 tools exceeds the 25-tool threshold, making the surface feel bloated rather than well-scoped. Many tools are near-variants of the same analytical idea (e.g. quick_ins vs image_search_quick_wins, content_decay vs image_content_decay) or are synthesizing tools that could potentially be consolidated.

    Completeness4/5

    The core GSC workflows are covered well: search analytics, URL inspection, indexing submission, sitemap management, and SEO opportunity identification. Minor gaps like sitemap deletion, property listing, and lower-level site management are absent but can be worked around in most agent workflows.

    Maintenance

    ActivitySlowing
    ResponsivenessMixed handling

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