Account data tools

These tools cover the account-scoped surface of the MCP server — your own private data. Every one is read-only and gated by your membership: the server checks that your signed-in account can access the property before returning anything.

Almost everything here starts from a propertyId, so the first call in any account session is list_properties.

Many of these tools return numeric series over time. Nothing is charted server-side — the assistant builds any visualization from the returned data. Just ask for "a chart of share of voice over the last 90 days" and it will.

Discover your properties

list_properties

Lists the properties (brands / sites) on your account, each with its organization and your role. Use a returned id as the propertyId for every other tool on this page.

Projects

Projects are bundled, time-bound tracking efforts (an SEO push, a PR campaign). See the Projects dashboard for the concept.

list_projects

Lists a property's projects with each one's type, status, date range, goals, and counts.

get_project_insights

A project's deep insights, matching its exported report: metric deltas from start to now (consistency, share of voice, mentions, owned citations, owned citation rate, and cumulative goal citations), a weekly trend series (including weekly goal hits), goals with their first-hit details plus hit counts and influence rates (the share of the project's citations each tracked publisher/article/author/coverage group accounts for), the annotation timeline, key insights, and next steps.

Historical trends

get_metrics_history

A property's AI visibility metrics over time — one point per report / nightly run: share of voice, mentions, citations, citation rate, and per-platform breakdowns. Pass a projectId to also get the grounding-search ranking trend scoped to that project's tracked queries.

Pass a tag to get a theme-scoped series instead: one point per UTC day, each with per-stage (awareness / consideration / decision) mentions, opportunities and share of voice for that tag, plus the day's consideration + decision headline. Pass a locationPropertyId to scope the series to one tracked market. The two combine.

list_prompt_tags

The filter vocabulary for a property: the free-form tags on its tracked prompts, plus their categories and use-cases. Call this before slicing anything by theme — a tag that does not appear here will return an empty series.

get_answer_drilldown

The L3 drill-down behind the visibility dashboard. For one UTC day it lists the tracked prompts that ran, and for each one every platform execution: which model answered, whether the answer mentioned the brand, the brand's rank inside the answer, and its citation counts. Totals reconcile exactly with the same day's point from get_metrics_history for the same scope — this is how you answer "why did share of voice move on this date?".

It returns no answer text — use get_answer_summaries for wording. If the day has no completed run (or falls outside the tracked range) the call reports that rather than returning zeros; pick a date that appears in get_metrics_history.

get_consistency_history

A property's brand-consistency score over time (overall and per platform) — how consistently AI platforms describe the brand vs. its source-of-truth identity.

Locations and competitors

list_locations

Per-market AI share of voice for a brand's tracked locations (its LOCATION child properties). Each entry carries the market's city / region / country and its latest measurement — share of voice, mentions, citations, citation rate, and the measurement date — alongside a rollup.

averageSov is equal-weighted across the markets that have data: a "typical market" number that treats a small market and a large one alike. It deliberately will not match the brand-wide share of voice from get_metrics_history, which pools every answer. For one market's history over time, feed its id back into get_metrics_history as locationPropertyId. A brand with no tracked locations returns an empty list, not an error.

get_competitor_share_of_voice

The ranked competitor share of voice from a property's latest measurement (nightly run or report, whichever is fresher). Each competitor carries shareOfVoice, totalMentions, totalCitations, queriesAppeared, and gapQueriesCount — the prompts where the competitor appeared and the brand did not, which is the acquisition gap worth acting on.

Two bases come back, and they must not be mixed inside one ranking:

• The top-level brandShareOfVoice and per-competitor values are the stored numbers from that single measurement, spanning all funnel stages.
• headline pools the last 7 days over the consideration and decision stages only — the same definition the brand dashboard's share-of-voice hero uses, and therefore the one to quote when it is present.

headline is null for properties whose data predates stage scoping; fall back to the all-stage fields in one piece when that happens.

Brand & comparison prompts

Prompts typed brand_identity ("What is [brand]?") or brand_comparison ("[brand] vs [competitor]") always mention the brand, so they are excluded from share of voice and measured by these two tools instead.

get_brand_prompt_health

Per-prompt health metrics for brand/comparison prompts, one row per prompt per day: expected-message coverage (% of the prompt's "should appear" messages found in answers), unwanted-message incidence (% of answers containing a "should not appear" message — lower is better), and theme drift.

Drift is 0–1 against the prompt's trailing 28-day theme pool: 0 means today's answers cover the same themes as the recent past; 1 means an entirely new story. Each row includes the day's themes, the novelThemes driving the drift (themes with no close match in the pool), and a messageBreakdown showing each expected message's per-day match count and a sample matched sentence — so you can say which messages appeared and what shifted, not just the aggregate numbers.

get_comparison_verdicts

Aggregated head-to-head outcomes from brand_comparison prompts: per compared brand and day, how often answers favor it, what they favor it for (topFavoredFor — "agencies", "multi-language teams"), the verdict shapes (clear_winner, segmented_winners, no_verdict, list_only), a sample framing summary, and frequency-ranked strengths/weaknesses the answers attribute to it. isOurBrand marks the property's own brand.

Each row also carries a derived favoredRate (0–100, one decimal) — favoredCount / totalComparisons for that row.

Read both counts carefully. Favored counts are not zero-sum: a segmented answer ("X for agencies, Y for in-house teams") favors several brands at once, so per-brand favored counts can each exceed half the total and the rates across brands can sum past 100. And totalComparisons is the day's count of comparison answers, shared by every brand row for that day — it is not that brand's own sample size.

brand is alias-aware: pass a tracked competitor's name and rows recorded under any of its aliases are included too, because stored rows key on whatever name the answer used. A name that matches no tracked competitor is still accepted as a raw compared-brand name.

Message tracking and drift

These two pair together: one shows how often your key messages get pulled through, the other shows how the wording changes.

get_message_tracking

How often each tracked key message is pulled through into AI answers over time — a mention rate per message, plus first/latest values and the change. Good for a per-message trend chart.

Filter by tags and/or sentiment. Tags plus sentiment: NEGATIVE is the crisis-monitoring cut: the messages you never want AI to repeat, and whether it is repeating them — a rising rate there is bad news, the inverse of every other metric on this page.

get_answer_summaries

The full answer text AI platforms gave for one tracked query, bucketed by week (one representative answer per week per platform). Compare weeks to narrate how the AI's description of the brand shifts. Omit query to first list the property's tracked queries, then call again with the one you want.

See the Key Messages dashboard for the concept behind both.

Citation intelligence

get_citation_intelligence

A property's citation intelligence: the mix of sources AI cites, broken down by media type, authority type, content format, and page type; per-platform stats; a historical trend (citation mix over time); and the top citation sources by owner (brand / competitor / third-party). Use the historicalData series to chart how the mix shifts.

The summary also includes the cited-vs-evaluated split (citationTypeBreakdown — sources referenced in the answer text vs merely fetched while composing it) and earned-media rollups (earnedMedia — third-party sources whose fetched page content mentions the brand, including hidden earned media that never surfaces in answer-text attribution). Each top source carries contentMentions: brands found in its pages' content, distinct from answer-text brandMentions.

For "what would this filter give me?" questions, facetCounts holds per-dimension value counts computed with that dimension's own filter lifted (so media type, authority type, content format and platform compose instead of zeroing each other out), and facetTotals holds the same tallies with all four lifted.

See the Citation Intelligence dashboard for how these breakdowns are defined.

get_coverage_citations

For a coverage group (a list of earned-media placement URLs), the AI citations its URLs earned from the property's tracked prompts and reports. Answers "which prompt and platform cited my placement, and in what context?"

Returns a funnel (coverage URLs → cited by AI → cited inline), a cited-vs-uncited comparison (average AIPQS, word count, content age, byline share, top authors), per-URL rollups, and the individual citation hits — each with the prompt text, platform, model, date, citation type (cited_inline = referenced in the answer text, a true citation; evaluated_source = fetched but not referenced), and, for inline citations, the answer-text context around the reference.

Call without groupId to first list the property's coverage groups, then call again with the one you want.

Counts here are scoped to your property's own tracked prompts and reports — the same numbers as the coverage group's citations page in the dashboard.

get_project_goal_citations

For a project goal, the citations behind its hit count — with each citation classified by brand relevance. Publisher (and author / page-group) goals match on the source, so their counts include citations unrelated to the brand; this tool separates them:

• attributed — the answer credited the brand for this source by name, or (on Google AI Overviews) the overview mentions the brand while this source is in its list. AIO doesn't credit sources individually, so those hits carry attributedViaAio: true — treat them as strong-but-circumstantial
• content_mention — the cited page's fetched content mentions the brand, but the answer never credited it (hidden earned media; includes the mention context from the page)
• answer_mention — the answer mentions the brand somewhere, just not attached to this citation
• unrelated — the source matched on its own authority, and the answer never mentions the brand

Hits are scoped to the project window, so totals match the project page's goal counts exactly. Returns a breakdown (total / attributed / content mentions / hidden earned media / answer mentions / cited inline / unrelated) plus per-citation prompt, platform, model, date, citation type, and answer context. Call without goalId to list the project's goals with their citation counts, then call again with the one you want.

A typical flow

Or run the Analyze a project, Track message drift, or Citation mix over time prompts.

Related

• Projects dashboard · Key Messages dashboard · Citation Intelligence dashboard
• Scoring tools — evaluate publishers and placements for a property