GetIntel

Manage GetIntel AI visibility (GEO) from your own AI agent — visibility scores, competitor share-of-voice, content gaps, and mission approvals.

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What it can do

Get Visibility: Get the AI Visibility score (0-100) — how often AI named the brand across the last 7 days of scans (a stable trailing average, not a single day). score is NULL when nothing was measure
Get Ai Answers: See which buyer questions AI search engines were asked and, for each, the RATE the brand was named across the last 7 days of scans (over runs_counted) plus the per-engine state: 'open'
Get Receipts: Get the exact answer each AI engine gave for one buyer question over the last 7 days, and how many of the (non-errored) runs named the brand.

What data it sees

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Manage GetIntel AI visibility (GEO) from your own AI agent — visibility scores, competitor share-of-voice, content gaps, and mission approvals.

Server tool list (19)

Raw names from tools/list. Only developers need these.

get_visibility	Get the AI Visibility score (0-100) — how often AI named the brand across the last 7 days of scans (a stable trailing average, not a single day). score is NULL when nothing was measured; 0 means AI answered and named the brand nowhere. Also returns scans_in_window and prompts_observed (the confidence behind the score), the change vs the previous 7-day window, and up to 12 points of history.
get_ai_answers	See which buyer questions AI search engines were asked and, for each, the RATE the brand was named across the last 7 days of scans (over runs_counted) plus the per-engine state: 'open' (AI named no product at all — a winnable slot), 'absent' (AI named others, not this brand), 'mentioned', 'recommended', 'no_answer', or 'error' (the run failed).
get_receipts	Get the exact answer each AI engine gave for one buyer question over the last 7 days, and how many of the (non-errored) runs named the brand.
list_activity	List recent things the agent found or did — signals, approvals, drafts, outcomes — most recent first.
list_missions	List missions the agent has proposed or is running — batches of related opportunities waiting for approval.
get_mission	Read-only preview of one mission: the buyer opportunities it bundles and any drafts already written — WITHOUT running it. Use this to inspect a mission before the irreversible approve_mission.
get_competitors	Share-of-voice board: how often each AI engine names the brand vs each competitor over the last 30 days — who's winning, and on which buyer prompts.
get_prompt_matrix	The per-prompt × per-engine matrix. For each buyer question, each engine's DOMINANT state over the last 7 days (open/absent/mentioned/recommended/no_answer) + the rate behind it, the brand's position when named, plus a visibility count of how many engines named the brand. no_answer means the engine returned nothing to read (failed call, or Google rendered no AI Overview) — it is NOT an open slot.
get_sources	Which domains the AI engines cite in the brand's category, how often, and whether each is the brand's own / a competitor's / third-party — where to get published to earn citations.
get_content_gaps	Topic coverage: for each buyer question, whether the brand has a page, whether AI cites it, the recommended action (write / improve / leave), and (for gaps) a page_type hint — commerce_page vs editorial — for ecommerce/local/hybrid brands.
get_signals	Recent Reddit + X signals the agent surfaced — buyer threads AI already cites where the brand is absent, competitor complaints, and ICP discovery posts.
get_search_console	Google Search Console performance joined against the tracked prompt set, so you can find pages and queries that rank on Google but that AI never cites. Returns totals (clicks, impressions, ctr, impression-weighted avg_position), a `rows` array, and `ranks_but_never_cited` — rows in the top 10 of Google that AI cited zero times. With dimension="page", each Search Console URL is matched exactly against the URLs AI cited (tracking params and www. normalized away), giving cited_by_ai / ai_citations / cited_by_engines. With dimension="query", the keyword is matched to a tracked prompt by normalized substring containment, giving matched_prompt, ai_mention_rate, ai_engines_naming_you and ai_answer_state; rows carry matched=false when no tracked prompt matched. cited_by_ai is null (not false) whenever the join has nothing to decide on — never read null as "AI ignores this". Errors clearly if Search Console is not connected or the grant was revoked; an empty result always means Google genuinely reported no data.
get_authority	Link authority for the brand's domain: domain_rating, referring_domains, backlinks, and net new referring domains over 7/30 days. Also returns link_opportunities — the global catalog of high-DR link targets (dr_targets) and listing directories (directories), ranked by domain rating, with directories the brand has already submitted to filtered out — plus the brand's own submission counts by status. authority_score is computed live from DR (or a log curve on referring domains when DR is unknown) and is NOT a component of the Findability score; treat it as context only.
get_brand	Does AI know this brand, and would it recommend it when asked — the trust/reputation signal (distinct from get_visibility's raw citation rate, which has no sentiment). Reads the last stored weekly run, not a live probe. Per engine (openai/perplexity/gemini_direct/google_aio — Claude excluded from this pillar): web (findability verdict — does it accurately describe the brand when asked directly), blind_state/blind_state_label (does the brand come up UNPROMPTED to a blind category question like 'what's the best tool for X', brand name never given), and recommendation (verdict + followup_reasoning — the model's own one-line explanation for whether it would recommend the brand BY NAME, always included, not just when negative). Deliberately lightweight — verdicts/labels/scores only, NOT the full AI answer text; call get_brand_transcript for that. verdict.good/verdict.bad are a synthesized, evidence-grounded summary across all engines. next_run_at is when this data next refreshes (weekly, independent of the other pillars).
get_crawlability	Can AI reach and read the site at all — the technical prerequisite layer underneath both get_visibility (does AI NAME the brand) and get_brand (does AI KNOW/RECOMMEND the brand): a site failing these gates can't be cited regardless of content quality or reputation. 12 pass/warn/fail checks (SSL, robots.txt allowing AI crawlers, firewall not blocking them, server response time, llms.txt, sitemap.xml, JS-only rendering, noindex, nosnippet/max-snippet blocking, entity schema, FAQ/HowTo content schema, page title/meta) run against the homepage plus a second page picked from the sitemap — the worse of the two wins per check. Reads the last stored run; refreshes at signup and weekly (piggybacks on the same AiVisibilityJob cadence as get_visibility, not an independent job).
get_usage	This month's MCP budget: reads and drafts used / limit / remaining, and when it resets. Check this before planning a large run so you don't hit the cap mid-task.
get_prompt_history	Per-prompt movement: which buyer questions you WON, LOST, or held between the current 7-day window and the window a full 7 days earlier, with the mention rate in each, joined by probe_id. Answers 'which prompts did we lose?'.
list_drafts	List drafts the agent has written — outreach emails, blog pitches, llms.txt / schema drafts, Reddit replies. Summary rows; call get_draft for the full text.
get_draft	Get the FULL content of one draft — the actual article / llms.txt / schema / reply text the agent generated, so you can ship it. This is what closes the loop after approving a mission or finding.