Report which engines are configured and reachable.

Always safe to call. Returns a dict keyed by engine name with configured: bool and a short message. Use this as the first call in a session to know what's available.

List all Search Console properties the authenticated user can access.

Returns a list of site entries with siteUrl and permissionLevel. Use siteUrl from this list as input to other gsc_* tools.

Query GSC search analytics.

Get index status for a specific URL via the URL Inspection API.

Returns coverage state, last crawl time, mobile usability, indexed verdict, and indexing rich-result data. Slow (~1s/call); rate-limited by Google.

Submit (or resubmit) a sitemap URL to GSC.

feedpath is the absolute URL of the sitemap, e.g. https://example.com/sitemap.xml.

List all Bing-verified sites for the API key owner.

Last-6-months query stats from Bing Webmaster (clicks, impressions, position).

site_url must match what Bing has verified, e.g. https://example.com/.

Per-page stats from Bing Webmaster.

Index status + crawl info for a single URL on Bing.

Submit a URL for fast crawling. Daily quota applies (default ~10/day).

Crawl errors / blocked URLs / DNS issues reported by Bingbot.

Notify Bing, Yandex, Naver, Seznam, and Yep that a single URL was published or updated.

Requires GEOSEO_INDEXNOW_KEY env var (a 32-char hex string you also host at https://yourdomain.com/<key>.txt).

Batch-notify search engines about up to 10,000 URLs (must share one host).

Best for sitemap-wide rebuilds or large content updates.

Ask Perplexity a question; return answer + cited URLs/domains.

Citation share for target_domain across a Perplexity question batch.

Ask ChatGPT (with web search) a question; return answer + cited URLs.

Uses the OpenAI Responses API with the web_search_preview tool. Default model: GEOSEO_OPENAI_MODEL (gpt-4o-mini).

Ask Claude (with server-side web search) a question; return answer + cited URLs.

Ask Gemini (with Google Search grounding) a question; return answer + cited URLs.

Grounding sources here are the same signal Google uses for AI Overviews, so this is the closest open-API proxy for "what AIO might cite for this query".

Ask the same question to all (or selected) configured LLM engines in parallel.

engines: optional subset of ["perplexity","openai","anthropic","gemini"]. Default: every engine with credentials configured (see geoseo_status). Engines that error are reported per-engine and don't block the others.

Citation-share metrics for target_domain across every configured LLM.

This is the headline GEO/AEO tool: feed it your top 20-50 user questions, get a per-engine breakdown of how often ChatGPT/Claude/Gemini/Perplexity cite your domain, plus the top competing domains per engine. Run weekly and diff to track AI-search visibility over time.

Return the LLM engines currently configured (have an API key).

Run a Google search via SerpAPI and parse the AI Overview block.

Returns aio_present, the AIO answer text, the URLs/domains AIO cites, and the top-10 organic results for context. Use this to track which pages Google's generative answers actually source.

For a batch of queries, report AIO fire-rate and citation share for target_domain.

This is the GEO companion to multi_llm_citation_check — same idea, but specifically for Google's on-SERP AI Overviews. Run weekly and snapshot to snapshot_serp_aio to track AIO visibility over time.

Audit a single page (local file path or http(s) URL).

Returns a structured report with: title/meta/headings, word count, link counts, image alt coverage, JSON-LD schema types, Open Graph, Twitter Card, freshness signals, GEO-quotability score, and a list of human-readable findings. Plus a 0-100 overall score.

Examples: audit_page("seo/aa-meetings-what-to-expect.html") audit_page("https://soberpath.com/blog/quit-drinking")

Recursively audit every HTML file under a folder.

Returns per-file scores, an aggregate summary (mean score, worst pages, most common findings), and the top opportunities for improvement.

Useful as the first call against a content directory to spot the worst offenders quickly.

Generate a draft llms.txt from a folder of HTML pages.

llms.txt (https://llmstxt.org) is the emerging standard for telling LLM crawlers where your canonical content lives. This tool reads each page's <title> and meta description, groups by URL prefix, and produces spec-compliant Markdown ready to drop at /llms.txt.

section_strategy controls grouping: - first_path_segment (default): groups by first URL path segment, e.g. all /blog/... pages under "Blog". - flat: a single "Pages" section.

Validate an llms.txt file (local path or URL) against the spec.

Returns parsed structure plus an issues list with line numbers for any violations (missing H1, broken link syntax, non-http(s) URLs, etc).

Audit a folder of HTML pages as a directed internal-link graph.

Returns counts of files/edges, the orphans (no inbound links), dead-ends (no outbound links), top hub pages, and a list of dangling internal hrefs that don't resolve to any file.

Pass site_host (e.g. "example.com") if pages link to themselves with absolute URLs — those will then count as internal edges. Files are also matched by URL slug, so /blog/foo resolves to foo.html even when paths don't match exactly.

Suggest top-K internal links to add to each page in a folder.

Uses TF-IDF cosine similarity over <title>, headings, and meta description. Excludes links the source already has, plus the page itself. Returns suggestions for page only if provided, otherwise for every page.

Each suggestion includes a cheap anchor_hint derived from terms shared between source headings and target title.

Create the local SQLite snapshot DB if it doesn't exist; return its path.

Inventory of what's stored: row counts, sites/domains, oldest/newest snapshots.

Run a GSC performance query and persist the rows as a snapshot.

Run this on a schedule (cron, n8n, launchd — anything that can invoke an MCP tool) to build a local time-series of search performance. Default dimensions: ["query"].

Run multi-LLM citation check and persist the per-question results.

Builds the dataset behind trend_llm_citations. engines defaults to every configured LLM (see geoseo_status).

Run AIO citation check via SerpAPI and persist as serpapi_aio engine rows.

Time-series of clicks/impressions/position from stored GSC snapshots.

Aggregates by captured_at. Filter by query and/or page to drill in. Returns up to limit most recent snapshots in chronological order.

Per-snapshot citation share for target_domain over time.

engine filters to one of perplexity|openai|anthropic|gemini|serpapi_aio. Returns rows of {captured_at, engine, questions, cited, citation_share}.