Apptiller

com.apptiller/apptillerVersion 0.1.3

Grow App Store apps: ranks, listing, ads, revenue and AI answers. Sign in to read your own apps.

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Responds535 msNov 14, 2026, 13:48 UTCAnswered our handshake without sign-in.

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Last checked: Nov 14, 2026, 13:48 UTC
Latency: 535 ms
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Connect

Streamable HTTP

https://mcp.apptiller.com/mcpResponds535 msNov 14, 2026, 13:48 UTC

No sign-in

Claude Code

claude mcp add --transport http apptiller https://mcp.apptiller.com/mcp

Claude Desktop and claude.ai

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Settings > Connectors > Add custom connector
Name: apptiller
Remote MCP server URL: https://mcp.apptiller.com/mcp

Cursor

{
  "mcpServers": {
    "apptiller": {
      "url": "https://mcp.apptiller.com/mcp"
    }
  }
}

VS Code

code --add-mcp '{"name":"apptiller","type":"http","url":"https://mcp.apptiller.com/mcp"}'

Streamable HTTP

https://mcp.apptiller.com/publicResponds546 msNov 14, 2026, 13:47 UTC

No sign-in

Claude Code

claude mcp add --transport http apptiller https://mcp.apptiller.com/public

Claude Desktop and claude.ai

1
2
3

Settings > Connectors > Add custom connector
Name: apptiller
Remote MCP server URL: https://mcp.apptiller.com/public

Cursor

{
  "mcpServers": {
    "apptiller": {
      "url": "https://mcp.apptiller.com/public"
    }
  }
}

VS Code

code --add-mcp '{"name":"apptiller","type":"http","url":"https://mcp.apptiller.com/public"}'

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Tools

57 tools

Tools of Apptiller
	Description		Read-only	Idempotent	Open world
`ai_referrals`Use this when the user asks how many visitors AI assistants sent to their website. Whether the app's website script is installed (status), and what it counted from AI assistants over the last days (UTC): visits per assistant, clicks to the App Store or Google Play after one, purchases the site reported, by day, and the pages people landed on. Google AI Mode and AI Overviews refer from google.com and aren't counted here.	Use this when the user asks how many visitors AI assistants sent to their website. Whether the app's website script is installed (status), and what it counted from AI assistants over the last days (UTC): visits per assistant, clicks to the App Store or Google Play after one, purchases the site reported, by day, and the pages people landed on. Google AI Mode and AI Overviews refer from google.com and aren't counted here.	No	Yes	Not declared	No
`ai_referrals_setup`Use this when the user wants to count visitors that AI assistants send to their website. Turns on counting of the people ChatGPT, Perplexity, Gemini, Copilot, Claude and other assistants send to an app's own website, and their clicks to the App Store or Google Play (tagged with an App Store campaign token per assistant) or a purchase the site reports. Returns the script tag to add to the site; calling it again keeps the same key. Domains default to the ones AI-answer tracking knows, else the project's website. Counts only, no cookies.	Use this when the user wants to count visitors that AI assistants send to their website. Turns on counting of the people ChatGPT, Perplexity, Gemini, Copilot, Claude and other assistants send to an app's own website, and their clicks to the App Store or Google Play (tagged with an App Store campaign token per assistant) or a purchase the site reports. Returns the script tag to add to the site; calling it again keeps the same key. Domains default to the ones AI-answer tracking knows, else the project's website. Counts only, no cookies.	Yes	No	Yes	No
`ai_visibility_collect`Use this after asking the questions again, to fetch the answers that are ready. Fetches every queued answer that is ready and scores it. Runs by itself every hour; running it fetches fresh answers sooner.	Use this after asking the questions again, to fetch the answers that are ready. Fetches every queued answer that is ready and scores it. Runs by itself every hour; running it fetches fresh answers sooner.	No	No	Yes	Yes
`ai_visibility_plan`Use this when the user asks how many apps, questions or runs their AI-answer tracking covers. The organization's AI-visibility allowance: how many products and questions it covers and how many runs a day, what is used, and how the answers run: daily or once a week on a few questions, depending on the account.	Use this when the user asks how many apps, questions or runs their AI-answer tracking covers. The organization's AI-visibility allowance: how many products and questions it covers and how many runs a day, what is used, and how the answers run: daily or once a week on a few questions, depending on the account.	No	Yes	Not declared	No
`ai_visibility_report`Use this when the user asks whether ChatGPT or Google's AI answers recommend their app, and who they name instead. How often ChatGPT, Google AI Mode and AI Overviews named the app for its questions, with a 95% range, its average position when named, which apps they named instead, and which sites they cited (including whether the app's own site or store listing was cited).	Use this when the user asks whether ChatGPT or Google's AI answers recommend their app, and who they name instead. How often ChatGPT, Google AI Mode and AI Overviews named the app for its questions, with a 95% range, its average position when named, which apps they named instead, and which sites they cited (including whether the app's own site or store listing was cited).	No	Yes	Not declared	No
`ai_visibility_run_now`Use this when the user asks for fresh AI answers now instead of waiting for the daily run. Queues one extra round of a project's questions on its engines now, instead of waiting for the daily run (up to 150 questions × engines). Answers arrive within about an hour.	Use this when the user asks for fresh AI answers now instead of waiting for the daily run. Queues one extra round of a project's questions on its engines now, instead of waiting for the daily run (up to 150 questions × engines). Answers arrive within about an hour.	No	No	Not declared	Yes
`ai_visibility_set_questions`Use this when the user wants to add or change the questions AI answers are checked for. Adds the questions people would ask an assistant when looking for an app like this one, e.g. "best app to track PCOS symptoms". They work best in a buyer's own words, mostly without the app's name. With replace, questions not in the list stop being asked (their history is kept).	Use this when the user wants to add or change the questions AI answers are checked for. Adds the questions people would ask an assistant when looking for an app like this one, e.g. "best app to track PCOS symptoms". They work best in a buyer's own words, mostly without the app's name. With replace, questions not in the list stop being asked (their history is kept).	Yes	No	Yes	No
`ai_visibility_track`Use this when the user wants to start tracking whether AI assistants recommend their app. Starts (or updates) tracking whether ChatGPT, Google AI Mode and Google AI Overviews recommend an app. Creates the project if it does not exist. Give every name the app goes by, its own domains, its App Store id or Play package, and the competitors to compare against.	Use this when the user wants to start tracking whether AI assistants recommend their app. Starts (or updates) tracking whether ChatGPT, Google AI Mode and Google AI Overviews recommend an app. Creates the project if it does not exist. Give every name the app goes by, its own domains, its App Store id or Play package, and the competitors to compare against.	Yes	No	Yes	No
`ai_visibility_tracked`Use this when the user asks which apps and questions are tracked in AI answers. Lists the apps tracked in AI answers, what Apptiller looks for in each, and their active questions.	Use this when the user asks which apps and questions are tracked in AI answers. Lists the apps tracked in AI answers, what Apptiller looks for in each, and their active questions.	No	Yes	Not declared	No
`app_brief`Use this when the user asks what goal, markets, constraints or limits Apptiller works from for an app. What Apptiller's agent works from for one app: the brief the user set (the goal, such as a target cost per paying subscriber or a ROAS, core countries, competitors, constraints such as "don't touch brand campaigns", and short facts), the limits it works inside (mode: watch only reports, ask proposes and waits for approval; the biggest step one change may take; the most a day's budget may grow; which levers it may use; campaigns it must never touch), its open plan items with their check dates, its last 14 journal entries and what past changes taught it on this app. Read-only.	Use this when the user asks what goal, markets, constraints or limits Apptiller works from for an app. What Apptiller's agent works from for one app: the brief the user set (the goal, such as a target cost per paying subscriber or a ROAS, core countries, competitors, constraints such as "don't touch brand campaigns", and short facts), the limits it works inside (mode: watch only reports, ask proposes and waits for approval; the biggest step one change may take; the most a day's budget may grow; which levers it may use; campaigns it must never touch), its open plan items with their check dates, its last 14 journal entries and what past changes taught it on this app. Read-only.	No	Yes	Not declared	No
`app_map_sources`Use this when the user wants to add an app to Apptiller or link an ad account, attribution app or RevenueCat project to it. Creates an app (with create) and maps connected accounts to it: Meta and Apple Ads ad accounts (spend), AdServices, AppsFlyer and Adjust apps (attribution), RevenueCat projects (revenue). Name an account by source_id or provider:external_id as this account lists them (e.g. meta:act_123, revenuecat:proj1a2b, adservices:com.example.app). For an ad account shared by several apps, set campaign_name_prefix so only that app's campaigns count. remove unmaps; history stays. Also looks the app up on the App Store (name, icon, developer) from its App Store id, bundle id, or a mapped AdServices or AppsFlyer app.	Use this when the user wants to add an app to Apptiller or link an ad account, attribution app or RevenueCat project to it. Creates an app (with create) and maps connected accounts to it: Meta and Apple Ads ad accounts (spend), AdServices, AppsFlyer and Adjust apps (attribution), RevenueCat projects (revenue). Name an account by source_id or provider:external_id as this account lists them (e.g. meta:act_123, revenuecat:proj1a2b, adservices:com.example.app). For an ad account shared by several apps, set campaign_name_prefix so only that app's campaigns count. remove unmaps; history stays. Also looks the app up on the App Store (name, icon, developer) from its App Store id, bundle id, or a mapped AdServices or AppsFlyer app.	Yes	No	Yes	Yes
`app_ownership`Use this when the user asks whether Apptiller sees an app as theirs, or how to prove it. Whether the app is proven to be this organization's, and by what: a connected App Store Connect key that sees the app, or a verified domain that the app's App Store listing (developer website) points to. When it isn't, says what would prove it.	Use this when the user asks whether Apptiller sees an app as theirs, or how to prove it. Whether the app is proven to be this organization's, and by what: a connected App Store Connect key that sees the app, or a verified domain that the app's App Store listing (developer website) points to. When it isn't, says what would prove it.	No	Yes	Not declared	No
`app_performance`Use this when the user asks about one app's ad spend, installs, revenue, ROAS or cost per install across ad networks. One app's spend, installs, trials, revenue, ROAS and cost per install, per day and per network (with an 'all' total per day) or per campaign, joined from Apptiller's synced history. Every number names its source: spend from the ad platforms; installs from the attribution layer (Apptiller's AdServices lookup for Apple Ads, the MMP for other networks), falling back to what the network claims, then to the revenue tool's tags; revenue, and so ROAS, from the MMP from the first day it has revenue for the app (revenue from the installs it attributed, USD, by install day; zeros mean the network earned nothing), else from the revenue tool's acquisition tags, whose split then sits in revenue_elsewhere; new customers and trials from the revenue tool, whose customers with no acquisition tag form an 'untagged' row (unknown source, not organic). Apple's own counts from App Store Connect sit beside each day's total in the network breakdown: first-time downloads in installs_elsewhere and proceeds (after Apple's commission, net of refunds) in revenue_elsewhere, standing in only on days no other layer counts; appleads rows carry app_store_search, Apple's count of all App Store search downloads, organic and Apple Ads together. Meta web campaigns (aimed at leads, sales or traffic, not app installs) carry web_results: the sign-ups, purchases and purchase value Meta's pixel counted on the website, Meta's own claim; they have no installs, the MMP doesn't judge them, and Meta's purchase value is their revenue only where the revenue tool has none tagged to them. ROAS only where spend and revenue share a currency. Set per_day false for one row per network or campaign over the whole range.	Use this when the user asks about one app's ad spend, installs, revenue, ROAS or cost per install across ad networks. One app's spend, installs, trials, revenue, ROAS and cost per install, per day and per network (with an 'all' total per day) or per campaign, joined from Apptiller's synced history. Every number names its source: spend from the ad platforms; installs from the attribution layer (Apptiller's AdServices lookup for Apple Ads, the MMP for other networks), falling back to what the network claims, then to the revenue tool's tags; revenue, and so ROAS, from the MMP from the first day it has revenue for the app (revenue from the installs it attributed, USD, by install day; zeros mean the network earned nothing), else from the revenue tool's acquisition tags, whose split then sits in revenue_elsewhere; new customers and trials from the revenue tool, whose customers with no acquisition tag form an 'untagged' row (unknown source, not organic). Apple's own counts from App Store Connect sit beside each day's total in the network breakdown: first-time downloads in installs_elsewhere and proceeds (after Apple's commission, net of refunds) in revenue_elsewhere, standing in only on days no other layer counts; appleads rows carry app_store_search, Apple's count of all App Store search downloads, organic and Apple Ads together. Meta web campaigns (aimed at leads, sales or traffic, not app installs) carry web_results: the sign-ups, purchases and purchase value Meta's pixel counted on the website, Meta's own claim; they have no installs, the MMP doesn't judge them, and Meta's purchase value is their revenue only where the revenue tool has none tagged to them. ROAS only where spend and revenue share a currency. Set per_day false for one row per network or campaign over the whole range.	No	Yes	Not declared	No
`app_store_charts`Use this when the user asks where an app sits in the App Store top charts, or why it moved. App Store category chart positions for one app, per storefront: for each chart Apptiller reads (top free or top paid, and top grossing, in the app's category) the place on the latest day read (null: not in the list), that day, the best place of the last 30 days, the place a week before, and the rivals from its search terms that are in the same list. moves lists the app's moves of 5 places or more over the 30 days (into or out of the list too), newest first, each with what Apptiller saw happen that day or the day before (a listing edit, a release, an App Store draft created, a reply posted, a page published, a listing gained). Charts are read daily on a plan. Read-only: it reads no chart itself.	Use this when the user asks where an app sits in the App Store top charts, or why it moved. App Store category chart positions for one app, per storefront: for each chart Apptiller reads (top free or top paid, and top grossing, in the app's category) the place on the latest day read (null: not in the list), that day, the best place of the last 30 days, the place a week before, and the rivals from its search terms that are in the same list. moves lists the app's moves of 5 places or more over the 30 days (into or out of the list too), newest first, each with what Apptiller saw happen that day or the day before (a listing edit, a release, an App Store draft created, a reply posted, a page published, a listing gained). Charts are read daily on a plan. Read-only: it reads no chart itself.	No	Yes	Not declared	No
`app_store_drafts`Use this when the user asks about proposed App Store listing edits, featuring nominations, in-app events or custom product pages. App Store listing and featuring drafts for one app, as Apptiller proposed them. listing_edits: open proposals for the promotional text, subtitle, keyword field or description, and those applied or undone in the last 90 days, each with its field, locale, the text live now (as the daily App Store Connect read last saw it), the text it was drafted from, the proposed text, why, its status (proposed, failed, applied, undone), any error, the version it rides on, and whether it was pasted by hand. store_drafts: featuring nominations, in-app events and custom product pages with their drafted text and dates, status (proposed, created in App Store Connect, submitted to Apple, failed) and any error; with the signs of being featured (jumps in App Store browse impressions) and readiness numbers. Read-only: it drafts, applies, creates, submits or rejects nothing.	Use this when the user asks about proposed App Store listing edits, featuring nominations, in-app events or custom product pages. App Store listing and featuring drafts for one app, as Apptiller proposed them. listing_edits: open proposals for the promotional text, subtitle, keyword field or description, and those applied or undone in the last 90 days, each with its field, locale, the text live now (as the daily App Store Connect read last saw it), the text it was drafted from, the proposed text, why, its status (proposed, failed, applied, undone), any error, the version it rides on, and whether it was pasted by hand. store_drafts: featuring nominations, in-app events and custom product pages with their drafted text and dates, status (proposed, created in App Store Connect, submitted to Apple, failed) and any error; with the signs of being featured (jumps in App Store browse impressions) and readiness numbers. Read-only: it drafts, applies, creates, submits or rejects nothing.	No	Yes	Not declared	No
`app_store_funnel`Use this when the user asks where an app's downloads came from (search, browse, websites, other apps) or about impressions, page views and conversion. Apple's App Analytics for each app, from App Store Connect's analytics reports, organic and paid alike: App Store impressions and page views, first-time downloads and redownloads, the conversion rate, purchases with proceeds in USD, subscription events (trial and paid offer starts, conversions to paid, paid starts, renewals, voluntary and involuntary churn, refunds) and active subscriptions (trials, paid offers, paid plans, billing issues), per app by day, by where people found the app (App Store search, which includes Apple Ads, App Store browse, App referrer, Web referrer) or by country. Days are UTC; the last two or three are incomplete. Apple makes these reports only after an Admin asks once, which Apptiller asks nobody to do, so only apps whose reports someone started (for another tool) have them. Says nothing about which campaign brought a download.	Use this when the user asks where an app's downloads came from (search, browse, websites, other apps) or about impressions, page views and conversion. Apple's App Analytics for each app, from App Store Connect's analytics reports, organic and paid alike: App Store impressions and page views, first-time downloads and redownloads, the conversion rate, purchases with proceeds in USD, subscription events (trial and paid offer starts, conversions to paid, paid starts, renewals, voluntary and involuntary churn, refunds) and active subscriptions (trials, paid offers, paid plans, billing issues), per app by day, by where people found the app (App Store search, which includes Apple Ads, App Store browse, App referrer, Web referrer) or by country. Days are UTC; the last two or three are incomplete. Apple makes these reports only after an Admin asks once, which Apptiller asks nobody to do, so only apps whose reports someone started (for another tool) have them. Says nothing about which campaign brought a download.	No	Yes	Not declared	No
`app_store_keywords`Use this when the user asks which App Store searches an app ranks for, or how its keyword ranks moved. App Store keyword ranks for one app, per storefront: the search terms Apptiller tracks and the candidate terms it found, each with its rank on the latest check (null: not in the first 100), the day of that check, the median rank of the last 7 days and of the 7 before and the change, up to 21 days of rank history, difficulty (from the ratings the top 10 hold, and the store's own 0-100 score when read), the app holding #1, relevance to the app and why (as judged by a model over several runs), the sources that suggested the term, Apple Ads numbers for the same search, and App Store autocomplete suggestions. rank_error says why the last rank check failed, and rank_held why the last run left a tracked term out for the plan. Per storefront, search_pulse sets App Store search impressions over the last complete week against the week before, with the tracked terms that moved the same way. Ranks are read once a day on a plan and once a week without one. Read-only: it finds, tracks or drops no terms, and runs no rank check.	Use this when the user asks which App Store searches an app ranks for, or how its keyword ranks moved. App Store keyword ranks for one app, per storefront: the search terms Apptiller tracks and the candidate terms it found, each with its rank on the latest check (null: not in the first 100), the day of that check, the median rank of the last 7 days and of the 7 before and the change, up to 21 days of rank history, difficulty (from the ratings the top 10 hold, and the store's own 0-100 score when read), the app holding #1, relevance to the app and why (as judged by a model over several runs), the sources that suggested the term, Apple Ads numbers for the same search, and App Store autocomplete suggestions. rank_error says why the last rank check failed, and rank_held why the last run left a tracked term out for the plan. Per storefront, search_pulse sets App Store search impressions over the last complete week against the week before, with the tracked terms that moved the same way. Ranks are read once a day on a plan and once a week without one. Read-only: it finds, tracks or drops no terms, and runs no rank check.	No	Yes	Not declared	No
`app_store_listing`Use this when the user asks what an app's App Store listing says or what changed in it. An app's App Store listing (name, icon, developer, version, genre, price, rating) and every change Apptiller has seen to it: name, icon, description, screenshots, version and release notes, price. Checked daily; set refresh to look it up now. Uses Apple's public lookup, so it needs only the App Store id or bundle id, no App Store Connect access.	Use this when the user asks what an app's App Store listing says or what changed in it. An app's App Store listing (name, icon, developer, version, genre, price, rating) and every change Apptiller has seen to it: name, icon, description, screenshots, version and release notes, price. Checked daily; set refresh to look it up now. Uses Apple's public lookup, so it needs only the App Store id or bundle id, no App Store Connect access.	No	No	Not declared	Yes
`app_store_reviews`Use this when the user asks what reviewers say about an app, which reviews need an answer, or how its ratings are trending. App Store reviews for one app from App Store Connect: the last 60 days' reviews (up to 25, unanswered first, lowest rating first), each with its rating, title, text, storefront, date, theme and the theme's kind (bug, request, price, praise, other), whether it has an answer and its text, and any reply Apptiller drafted. unanswered counts every review of the 60 days without an answer, beyond the 25 listed. themes counts the last 90 days' reviews per theme with their average rating. ratings: the summary rating and count, new ratings in the last 28 days against the 28 before, downloads and new ratings per 1,000 downloads in each, per version, and advice when the pace fell. key says whether an App Store Connect key reads them. Reviews are read daily on a plan and once a week without one. Read-only: it drafts, sends or withdraws no reply.	Use this when the user asks what reviewers say about an app, which reviews need an answer, or how its ratings are trending. App Store reviews for one app from App Store Connect: the last 60 days' reviews (up to 25, unanswered first, lowest rating first), each with its rating, title, text, storefront, date, theme and the theme's kind (bug, request, price, praise, other), whether it has an answer and its text, and any reply Apptiller drafted. unanswered counts every review of the 60 days without an answer, beyond the 25 listed. themes counts the last 90 days' reviews per theme with their average rating. ratings: the summary rating and count, new ratings in the last 28 days against the 28 before, downloads and new ratings per 1,000 downloads in each, per version, and advice when the pace fell. key says whether an App Store Connect key reads them. Reviews are read daily on a plan and once a week without one. Read-only: it drafts, sends or withdraws no reply.	No	Yes	Not declared	No
`app_store_sales`Use this when the user asks about an app's downloads, sales, proceeds or refunds. Not for which ad brought a download. Apple's own daily App Store numbers from App Store Connect (Sales and Trends), organic and paid alike: first-time downloads, re-downloads, updates, in-app purchases, new and renewed subscriptions, refunds and the developer's proceeds (after Apple's commission and taxes, net of refunds, in the currency Apple pays for each storefront), per app by day, storefront country or product. Days are Pacific Time, Apple's report day; each day comes out the next morning and is synced within six hours. Says nothing about which ad brought a download.	Use this when the user asks about an app's downloads, sales, proceeds or refunds. Not for which ad brought a download. Apple's own daily App Store numbers from App Store Connect (Sales and Trends), organic and paid alike: first-time downloads, re-downloads, updates, in-app purchases, new and renewed subscriptions, refunds and the developer's proceeds (after Apple's commission and taxes, net of refunds, in the currency Apple pays for each storefront), per app by day, storefront country or product. Days are Pacific Time, Apple's report day; each day comes out the next morning and is synced within six hours. Says nothing about which ad brought a download.	No	Yes	Not declared	No
`apple_ads_accounts`Use this when the user asks which Apple Ads accounts Apptiller can read. Lists the Apple Ads ad accounts Apptiller can read, with the connected user's roles in each, straight from Apple. Accounts marked basic are Apple Ads Basic: Apple offers no reporting API for them, so there is no spend data and their results come through attribution.	Use this when the user asks which Apple Ads accounts Apptiller can read. Lists the Apple Ads ad accounts Apptiller can read, with the connected user's roles in each, straight from Apple. Accounts marked basic are Apple Ads Basic: Apple offers no reporting API for them, so there is no spend data and their results come through attribution.	No	Yes	Not declared	No
`apple_ads_performance`Use this when the user asks how their Apple Ads campaigns, ad groups or keywords are doing, as Apple reports them. Daily Apple Ads (App Store search ads) numbers from Apptiller's synced history: spend, impressions, taps, installs and every other metric Apple reports, by campaign, ad group, ad or keyword, between two dates. Synced four times a day; set raw to get Apple's full rows.	Use this when the user asks how their Apple Ads campaigns, ad groups or keywords are doing, as Apple reports them. Daily Apple Ads (App Store search ads) numbers from Apptiller's synced history: spend, impressions, taps, installs and every other metric Apple reports, by campaign, ad group, ad or keyword, between two dates. Synced four times a day; set raw to get Apple's full rows.	No	Yes	Not declared	No
`apple_ads_search_terms`Use this when the user asks what people searched when their Apple Ads showed, which searches Search Match matched, or which searches to add as keywords or negatives. Apple's search terms report for one app's Apple Ads campaigns over the last 90 days (Apple's limit), read with each full sync: each search people typed, the campaign and ad group, whether Search Match found it (source AUTO) or one of the keywords did (source TARGETED, with the keyword and its match type), impressions, taps, installs and spend. to_add lists Search Match searches that brought installs and aren't a keyword yet (judged against every keyword the campaigns have, read from Apple, so one just added counts); no_installs lists searches with 5 taps or more and no install; waiting lists active keywords added in the last 14 days that have had no impression yet, with the day each was added; never_shown lists active keywords added longer ago with no impression in the history kept. Keywords are read once a day. Apple leaves out searches with fewer than 10 impressions. Read-only: it adds or blocks no keyword.	Use this when the user asks what people searched when their Apple Ads showed, which searches Search Match matched, or which searches to add as keywords or negatives. Apple's search terms report for one app's Apple Ads campaigns over the last 90 days (Apple's limit), read with each full sync: each search people typed, the campaign and ad group, whether Search Match found it (source AUTO) or one of the keywords did (source TARGETED, with the keyword and its match type), impressions, taps, installs and spend. to_add lists Search Match searches that brought installs and aren't a keyword yet (judged against every keyword the campaigns have, read from Apple, so one just added counts); no_installs lists searches with 5 taps or more and no install; waiting lists active keywords added in the last 14 days that have had no impression yet, with the day each was added; never_shown lists active keywords added longer ago with no impression in the history kept. Keywords are read once a day. Apple leaves out searches with fewer than 10 impressions. Read-only: it adds or blocks no keyword.	No	Yes	Not declared	No
`apply_proposal`Use this only after the user has seen a specific proposal and said to apply it. Not for changes the user describes without a proposal. Makes the change a proposal the user has seen and approved describes, in the live ad account: pauses the campaign, ad group or keyword, or moves its bid or daily budget by the proposed step (at most 20%). Apple Ads, Meta and Google Ads (Meta and Google Ads move budgets and pause; they have no bids to move). Apptiller first reads the entity live from the platform and writes only if it still has the value the proposal started from; the value it replaces is kept, so the change can be undone. A proposal waits while an earlier change to the same entity, one above it or one inside it is still being measured (7 days), so what each change did can be told apart. This spends or saves real money.	Use this only after the user has seen a specific proposal and said to apply it. Not for changes the user describes without a proposal. Makes the change a proposal the user has seen and approved describes, in the live ad account: pauses the campaign, ad group or keyword, or moves its bid or daily budget by the proposed step (at most 20%). Apple Ads, Meta and Google Ads (Meta and Google Ads move budgets and pause; they have no bids to move). Apptiller first reads the entity live from the platform and writes only if it still has the value the proposal started from; the value it replaces is kept, so the change can be undone. A proposal waits while an earlier change to the same entity, one above it or one inside it is still being measured (7 days), so what each change did can be told apart. This spends or saves real money.	Yes	No	No	No
`apps`Use this when the user asks which apps are in their Apptiller account, or which accounts feed each app. Lists the apps in this Apptiller account with the ad accounts, attribution sources and revenue projects mapped to each (and which layer each one feeds), plus the connected accounts no app uses yet. Per-app performance covers mapped accounts only.	Use this when the user asks which apps are in their Apptiller account, or which accounts feed each app. Lists the apps in this Apptiller account with the ad accounts, attribution sources and revenue projects mapped to each (and which layer each one feeds), plus the connected accounts no app uses yet. Per-app performance covers mapped accounts only.	No	Yes	Not declared	No
`attribution_performance`Use this when the user asks which network, campaign or keyword brought installs, as the attribution tool counted them. Daily installs by attribution source from Apptiller's attribution layer (Apptiller's own Apple AdServices lookup, AppsFlyer and Adjust when connected: their rows carry every metric the MMP reports in metrics, including sessions, revenue, cost and in-app events; Adjust also has ad group rows), by network, campaign, ad group, keyword or ad, between two dates, with claim type, conversion type and country counts. These are installs as the attribution source saw them, not what the ad network claims or what the revenue tool tagged.	Use this when the user asks which network, campaign or keyword brought installs, as the attribution tool counted them. Daily installs by attribution source from Apptiller's attribution layer (Apptiller's own Apple AdServices lookup, AppsFlyer and Adjust when connected: their rows carry every metric the MMP reports in metrics, including sessions, revenue, cost and in-app events; Adjust also has ad group rows), by network, campaign, ad group, keyword or ad, between two dates, with claim type, conversion type and country counts. These are installs as the attribution source saw them, not what the ad network claims or what the revenue tool tagged.	No	Yes	Not declared	No
`attribution_setup`Use this only when the user asks to set up Apple Ads attribution for an app that has no attribution or revenue SDK. An optional fallback for an app with no MMP (AppsFlyer, Adjust…) and no revenue SDK that collects Apple Ads attribution; Apptiller otherwise reads attribution from the tools already connected. Creates this organization's Apptiller ingest key and returns a Swift function to add to the iOS app. The app then sends each install's Apple AdServices token to Apptiller, which resolves it with Apple: which Apple Ads campaign, ad group, keyword and ad brought the install, for Advanced and Basic accounts alike, with no third-party SDK and no tracking prompt. Calling it again replaces the key; apps with the old key stop counting until updated.	Use this only when the user asks to set up Apple Ads attribution for an app that has no attribution or revenue SDK. An optional fallback for an app with no MMP (AppsFlyer, Adjust…) and no revenue SDK that collects Apple Ads attribution; Apptiller otherwise reads attribution from the tools already connected. Creates this organization's Apptiller ingest key and returns a Swift function to add to the iOS app. The app then sends each install's Apple AdServices token to Apptiller, which resolves it with Apple: which Apple Ads campaign, ad group, keyword and ad brought the install, for Advanced and Basic accounts alike, with no third-party SDK and no tracking prompt. Calling it again replaces the key; apps with the old key stop counting until updated.	Yes	No	No	No
`briefing`Use this when the user asks what's wrong with their ads, what to change, or what an earlier ad change did. What Apptiller's analyst found in each app's last 14 days of synced data: Meta campaigns and ad sets, and Apple Ads campaigns, ad groups and keywords, that spent with no results, cost far more per result than the rest of their channel, or far less. Each finding has its evidence (spend, results and their source, cost per result with a 90% range, the baseline it was compared with), how sure it is, and one proposed change (pause, bid or budget). Like is compared with like: one channel, level, objective and currency, measured in the deepest result the group has enough of (purchases, trials, sign-ups, attributed installs, then installs the network claims), from one source. Also, per group, what it was judged by or why it couldn't be, and the changes Apptiller made in the app's ad accounts over the last 30 days (with change ids), each with its effect: the 7 days before it against the 7 after, in the result and source its finding was judged by, net of how the rest of its group moved over the same days, with how sure that is and a verdict (better, worse or unclear: cheaper results after a cut, more of them after a raise). An Apple Ads change also gets `search` once the app's App Store Connect analytics are connected (search results campaigns only): all of App Store search's first-time downloads a day before and after (Apple's App Analytics, organic included), the part Apple Ads credits its search results campaigns with, and the share of Apple Ads' move that was new to search, with a 90% range set by how much organic search moved week to week before (verdict incremental, organic or unclear, once Apple's numbers for all 7 days after are in); the analyst doesn't raise again what a raise mostly took from organic search. While a change is being measured, the analyst leaves alone the entity, those above it and those inside it; their proposals wait (status 'waiting', and `wai	Use this when the user asks what's wrong with their ads, what to change, or what an earlier ad change did. What Apptiller's analyst found in each app's last 14 days of synced data: Meta campaigns and ad sets, and Apple Ads campaigns, ad groups and keywords, that spent with no results, cost far more per result than the rest of their channel, or far less. Each finding has its evidence (spend, results and their source, cost per result with a 90% range, the baseline it was compared with), how sure it is, and one proposed change (pause, bid or budget). Like is compared with like: one channel, level, objective and currency, measured in the deepest result the group has enough of (purchases, trials, sign-ups, attributed installs, then installs the network claims), from one source. Also, per group, what it was judged by or why it couldn't be, and the changes Apptiller made in the app's ad accounts over the last 30 days (with change ids), each with its effect: the 7 days before it against the 7 after, in the result and source its finding was judged by, net of how the rest of its group moved over the same days, with how sure that is and a verdict (better, worse or unclear: cheaper results after a cut, more of them after a raise). An Apple Ads change also gets `search` once the app's App Store Connect analytics are connected (search results campaigns only): all of App Store search's first-time downloads a day before and after (Apple's App Analytics, organic included), the part Apple Ads credits its search results campaigns with, and the share of Apple Ads' move that was new to search, with a 90% range set by how much organic search moved week to week before (verdict incremental, organic or unclear, once Apple's numbers for all 7 days after are in); the analyst doesn't raise again what a raise mostly took from organic search. While a change is being measured, the analyst leaves alone the entity, those above it and those inside it; their proposals wait (status 'waiting', and `wai	No	No	Not declared	No
`check_launch`Use this after the user connects or proves something that could change a launch's tier. Works out a launch's tier again from what is connected now (after connecting RevenueCat, mapping its project to the app, or proving ownership).	Use this after the user connects or proves something that could change a launch's tier. Works out a launch's tier again from what is connected now (after connecting RevenueCat, mapping its project to the app, or proving ownership).	No	No	Yes	Yes
`close_site_guide`Use this when the user says a guide went live, or wants to drop it. Marks one guide as published, with the full https address where it went live, so Apptiller counts its Google clicks from then on; or dismissed.	Use this when the user says a guide went live, or wants to drop it. Marks one guide as published, with the full https address where it went live, so Apptiller counts its Google clicks from then on; or dismissed.	Yes	No	No	No
`connect_account`Use this when the user wants to connect a service to Apptiller: App Store Connect, an ad account, an attribution tool, RevenueCat, Stripe or Google Search Console. Returns a one-time link (valid 15 minutes) that the user opens in a browser to connect a service to Apptiller. The user enters any keys or passwords on that page, not in the chat.	Use this when the user wants to connect a service to Apptiller: App Store Connect, an ad account, an attribution tool, RevenueCat, Stripe or Google Search Console. Returns a one-time link (valid 15 minutes) that the user opens in a browser to connect a service to Apptiller. The user enters any keys or passwords on that page, not in the chat.	No	No	Not declared	No
`data_coverage`Use this before judging ad campaigns by revenue or paying users, or when the user asks what their data can show. Per app and ad channel (Apple Ads, Meta, …), over the last 30 days of synced data: what Apptiller can judge the channel's campaigns by (paying subscribers, the MMP's purchase or trial event counts, Meta's own conversion counts, installs, or only the network's own claims), the source that rests on, and what is missing, with how to fix it in tools the user already has. Also each connected account's facts in its layer (installs, MMP revenue and purchase events, customers and tags, spend). Reads synced data only; asks nothing of the app.	Use this before judging ad campaigns by revenue or paying users, or when the user asks what their data can show. Per app and ad channel (Apple Ads, Meta, …), over the last 30 days of synced data: what Apptiller can judge the channel's campaigns by (paying subscribers, the MMP's purchase or trial event counts, Meta's own conversion counts, installs, or only the network's own claims), the source that rests on, and what is missing, with how to fix it in tools the user already has. Also each connected account's facts in its layer (installs, MMP revenue and purchase events, customers and tags, spend). Reads synced data only; asks nothing of the app.	No	Yes	Not declared	No
`dismiss_finding`Use this when the user wants a finding to stop coming up. Dismisses one of the analyst's findings: it leaves the briefing, its pending proposal is rejected, and the analyst stays quiet about the same thing for 30 days. Nothing changes in the ad account, and changes already made stay.	Use this when the user wants a finding to stop coming up. Dismisses one of the analyst's findings: it leaves the briefing, its pending proposal is rejected, and the analyst stays quiet about the same thing for 30 days. Nothing changes in the ad account, and changes already made stay.	Yes	No	Yes	No
`edit_launch`Use this when the user asks to change how a launch shows on the board. Changes what the board shows of a launch: its name, tagline, category, and whether dollar amounts are hidden (rank and growth still show). Fields left out stay as they are. The address (slug) never changes.	Use this when the user asks to change how a launch shows on the board. Changes what the board shows of a launch: its name, tagline, category, and whether dollar amounts are hidden (rank and growth still show). Fields left out stay as they are. The address (slug) never changes.	Yes	No	Yes	Yes
`launch_ai_answers`Use this when the user asks whether AI answers name their launched product. A claimed launch's free AI answers (tier owner or verified; an unclaimed launch can save questions but not run them): up to 5 questions someone who needs the product would ask (never naming it), asked on ChatGPT, Google AI Mode and AI Overviews. Pass questions to replace them; run: true starts the first check, once per launch (each question 3 times on every engine), asked as from country (US unless given). Claimed founding launches are then asked again every day until their period ends. Returns the questions and the results so far: how often the product is named and who is named instead, per question. With raw: true it also returns the latest day's answers themselves: each engine's text (up to 1500 characters), whether and where it named the product, who else it named, and the pages it cited. Answers arrive within a few hours.	Use this when the user asks whether AI answers name their launched product. A claimed launch's free AI answers (tier owner or verified; an unclaimed launch can save questions but not run them): up to 5 questions someone who needs the product would ask (never naming it), asked on ChatGPT, Google AI Mode and AI Overviews. Pass questions to replace them; run: true starts the first check, once per launch (each question 3 times on every engine), asked as from country (US unless given). Claimed founding launches are then asked again every day until their period ends. Returns the questions and the results so far: how often the product is named and who is named instead, per question. With raw: true it also returns the latest day's answers themselves: each engine's text (up to 1500 characters), whether and where it named the product, who else it named, and the pages it cited. Answers arrive within a few hours.	Yes	No	No	Yes
`launch_product`Use this when the user asks to launch their app or website on Apptiller Launches. Launches an app (from its App Store link or id) or a website (its domain, plus a name) on Apptiller Launches, the public board ranked by the revenue a launch adds in its period, verified through the product's own RevenueCat app or its Stripe account and a TXT-verified domain (websites). It goes into the first open period with a spot (the founding month first). Returns the launch with its tier: verified (ranked), owner (ownership proven: listed, not ranked) or unverified, and what would raise it. One launch per product across Apptiller. Launching is free; it makes the product's name, tagline and launch-period numbers public.	Use this when the user asks to launch their app or website on Apptiller Launches. Launches an app (from its App Store link or id) or a website (its domain, plus a name) on Apptiller Launches, the public board ranked by the revenue a launch adds in its period, verified through the product's own RevenueCat app or its Stripe account and a TXT-verified domain (websites). It goes into the first open period with a spot (the founding month first). Returns the launch with its tier: verified (ranked), owner (ownership proven: listed, not ranked) or unverified, and what would raise it. One launch per product across Apptiller. Launching is free; it makes the product's name, tagline and launch-period numbers public.	Yes	No	No	Yes
`list_connections`Use this when the user asks which services are connected to Apptiller. Shows which services (Meta Ads, App Store Connect, Apple Ads, Google Ads, RevenueCat, AppsFlyer, Adjust) are connected to this Apptiller account.	Use this when the user asks which services are connected to Apptiller. Shows which services (Meta Ads, App Store Connect, Apple Ads, Google Ads, RevenueCat, AppsFlyer, Adjust) are connected to this Apptiller account.	No	Yes	Not declared	No
`list_domains`Use this when the user asks which domains are verified. The organization's domains with their state (pending, verified, lapsed, failed) and the TXT record each one needs. Removing a domain is done in the web app.	Use this when the user asks which domains are verified. The organization's domains with their state (pending, verified, lapsed, failed) and the TXT record each one needs. Removing a domain is done in the web app.	No	Yes	Not declared	No
`list_launches`Use this when the user asks how their launches on Apptiller Launches are doing. This organization's launches on Apptiller Launches: period, tier, proof, what would raise the tier, the latest numbers (revenue added in the period so far, growth, new customers, trials), and the public page's traffic over the last 7 days (views by where they came from, clicks out to the product, badge loads on other sites). For an app, app_store_from_launches: the App Store page views and first-time downloads Apple's App Analytics credits to apptiller.com (Web referrer) since the launch was made (since, a UTC day as App Analytics counts them), through latest, the last day Apple's reports reached. latest null: Apple's Detailed reports haven't both come in (started false: App Analytics not started; started true: still coming in). latest before since: Apple hasn't reported the launch's days yet, so the zeros aren't counts. stopped: every App Store Connect key that reads the app is revoked or broken, so latest won't move until it's replaced. Apple leaves small counts out. Each has its page in the web app. Withdrawing is done in the web app.	Use this when the user asks how their launches on Apptiller Launches are doing. This organization's launches on Apptiller Launches: period, tier, proof, what would raise the tier, the latest numbers (revenue added in the period so far, growth, new customers, trials), and the public page's traffic over the last 7 days (views by where they came from, clicks out to the product, badge loads on other sites). For an app, app_store_from_launches: the App Store page views and first-time downloads Apple's App Analytics credits to apptiller.com (Web referrer) since the launch was made (since, a UTC day as App Analytics counts them), through latest, the last day Apple's reports reached. latest null: Apple's Detailed reports haven't both come in (started false: App Analytics not started; started true: still coming in). latest before since: Apple hasn't reported the launch's days yet, so the zeros aren't counts. stopped: every App Store Connect key that reads the app is revoked or broken, so latest won't move until it's replaced. Apple leaves small counts out. Each has its page in the web app. Withdrawing is done in the web app.	No	Yes	Not declared	No
`meta_ad_accounts`Use this when the user asks which Meta ad accounts Apptiller can read. Lists the Meta ad accounts Apptiller can read, with currency and status.	Use this when the user asks which Meta ad accounts Apptiller can read. Lists the Meta ad accounts Apptiller can read, with currency and status.	No	Yes	Not declared	No
`meta_diagnose`Use this when Meta data is missing or a Meta account can't be read. Shows what the connected Meta token is (system user or person), its permissions and granted account ids, and what each ad-account lookup returns. Never shows the token.	Use this when Meta data is missing or a Meta account can't be read. Shows what the connected Meta token is (system user or person), its permissions and granted account ids, and what each ad-account lookup returns. Never shows the token.	No	Yes	Not declared	No
`meta_performance`Use this when the user asks how their Meta (Facebook, Instagram) ads are doing. Spend, impressions, reach, clicks, CPM, CTR and key results (purchases, trials, registrations, leads, installs, checkouts…) with cost per result and ROAS, for a Meta ad account by account, campaign, ad set or ad. Use a date preset such as last_7d, or since/until dates. Set raw to get Meta's full action list.	Use this when the user asks how their Meta (Facebook, Instagram) ads are doing. Spend, impressions, reach, clicks, CPM, CTR and key results (purchases, trials, registrations, leads, installs, checkouts…) with cost per result and ROAS, for a Meta ad account by account, campaign, ad set or ad. Use a date preset such as last_7d, or since/until dates. Set raw to get Meta's full action list.	No	Yes	Not declared	No
`organic_todo`Use this when the user asks what to do to show up more in Google search or AI answers. One app's organic To do, as Search & AI › To do shows it: one ranked list of the work Google's searches and the AI answers point at, best first, each item in a group (New page: a need no page on the site answers, from Google searches, an AI question, or both; Improve a page: a page Google shows but few click, or just off the top results; Fix what AI says: a wrong claim, or rivals' App Store listings cited instead; Get listed or compared: a rival named instead, or a page the answers cite). Each item has its evidence lines from every source (Google impressions, clicks and position; the AI answers that leave the app out, by engine; the page that ranks now; its visits), its score and why it is first (Google clicks missed at a position a page can reach, plus AI answers weighted by engine, plus a draft waiting), its state (new, planned, drafted, or its guide ready, held, published or dismissed), its finding ids and its actions as the web app offers them. today says how the last morning run went: what it drafted, or why nothing, or the error. unavailable names any part that couldn't be read just now. done lists items marked done with what each brought: Google clicks on its page in the 28 days after against the 28 days before, and AI answers naming the app for its questions, saying where the 28 days aren't in yet.	Use this when the user asks what to do to show up more in Google search or AI answers. One app's organic To do, as Search & AI › To do shows it: one ranked list of the work Google's searches and the AI answers point at, best first, each item in a group (New page: a need no page on the site answers, from Google searches, an AI question, or both; Improve a page: a page Google shows but few click, or just off the top results; Fix what AI says: a wrong claim, or rivals' App Store listings cited instead; Get listed or compared: a rival named instead, or a page the answers cite). Each item has its evidence lines from every source (Google impressions, clicks and position; the AI answers that leave the app out, by engine; the page that ranks now; its visits), its score and why it is first (Google clicks missed at a position a page can reach, plus AI answers weighted by engine, plus a draft waiting), its state (new, planned, drafted, or its guide ready, held, published or dismissed), its finding ids and its actions as the web app offers them. today says how the last morning run went: what it drafted, or why nothing, or the error. unavailable names any part that couldn't be read just now. done lists items marked done with what each brought: Google clicks on its page in the 28 days after against the 28 days before, and AI answers naming the app for its questions, saying where the 28 days aren't in yet.	No	Yes	Not declared	No
`reject_proposal`Use this when the user declines one of the analyst's proposals. Marks one of the analyst's proposals as rejected. Nothing changes in the ad account; the finding stays in the briefing, and the analyst doesn't propose that change again while the finding stays open.	Use this when the user declines one of the analyst's proposals. Marks one of the analyst's proposals as rejected. Nothing changes in the ad account; the finding stays in the briefing, and the analyst doesn't propose that change again while the finding stays open.	Yes	No	Yes	No
`revenuecat_chart`Use this when the user asks how a subscription metric (trials, conversion, MRR, churn, retention) moved over time. A RevenueCat chart over time: trials, trial conversion, MRR, revenue, churn, actives, retention, refunds, paywall conversion and more, optionally segmented (e.g. by country or product) and filtered.	Use this when the user asks how a subscription metric (trials, conversion, MRR, churn, retention) moved over time. A RevenueCat chart over time: trials, trial conversion, MRR, revenue, churn, actives, retention, refunds, paywall conversion and more, optionally segmented (e.g. by country or product) and filtered.	No	Yes	Not declared	No
`revenuecat_chart_options`Use this before building a RevenueCat chart, to see what it accepts. The resolutions, segments (country, product, store…), filters and selectors a RevenueCat chart accepts.	Use this before building a RevenueCat chart, to see what it accepts. The resolutions, segments (country, product, store…), filters and selectors a RevenueCat chart accepts.	No	Yes	Not declared	No
`revenuecat_overview`Use this when the user asks for an app's current subscription numbers, such as MRR, active subscriptions or trials. Current subscription metrics for a RevenueCat project: active trials, active subscriptions, MRR, revenue and new customers over the last 28 days, and active users.	Use this when the user asks for an app's current subscription numbers, such as MRR, active subscriptions or trials. Current subscription metrics for a RevenueCat project: active trials, active subscriptions, MRR, revenue and new customers over the last 28 days, and active users.	No	Yes	Not declared	No
`revenuecat_projects`Use this when the user asks which RevenueCat projects Apptiller can read. Lists the RevenueCat projects Apptiller can read, with their ids.	Use this when the user asks which RevenueCat projects Apptiller can read. Lists the RevenueCat projects Apptiller can read, with their ids.	No	Yes	Not declared	No
`revenuecat_revenue`Use this when the user asks how much revenue an app made between two dates, from RevenueCat. Total revenue for a RevenueCat project between two dates (inclusive): gross, net of taxes, or proceeds after store fees.	Use this when the user asks how much revenue an app made between two dates, from RevenueCat. Total revenue for a RevenueCat project between two dates (inclusive): gross, net of taxes, or proceeds after store fees.	No	Yes	Not declared	No
`set_app_brief`Use this when the user states an app's goal, markets, competitors or constraints for Apptiller to work from. Writes the brief Apptiller's agent works from for one app. Fields left out stay as they are. goal: what a good result is, as a cost per paying subscriber, per trial or per install (with its currency) or a ROAS (revenue over spend, e.g. 1.2), or null to clear it. countries: the markets that matter most, as two-letter codes. competitors: apps the user names as competitors (names or App Store ids). constraints: plain words the agent must respect, such as a launch date or campaigns not to touch. facts: short facts by key (prices, seasonality, anything the agent should know); a null value removes one. The agent never overwrites what the user set here. These come from the user.	Use this when the user states an app's goal, markets, competitors or constraints for Apptiller to work from. Writes the brief Apptiller's agent works from for one app. Fields left out stay as they are. goal: what a good result is, as a cost per paying subscriber, per trial or per install (with its currency) or a ROAS (revenue over spend, e.g. 1.2), or null to clear it. countries: the markets that matter most, as two-letter codes. competitors: apps the user names as competitors (names or App Store ids). constraints: plain words the agent must respect, such as a launch date or campaigns not to touch. facts: short facts by key (prices, seasonality, anything the agent should know); a null value removes one. The agent never overwrites what the user set here. These come from the user.	Yes	No	Yes	No
`set_app_limits`Use this only when the user asks to change how far Apptiller may go with an app's ad changes. Sets, for one app, how far Apptiller's agent may go. Owners and admins only. Fields left out stay as they are. mode: watch (the agent only reports), ask (it proposes changes and a member approves each one; the default) or autopilot. autopilot: it applies its own proposals inside these limits by itself, two changes a day at most (where the account's plan includes it; needs a linked ad account that is being read, an attribution source, and max_daily_increase unless the budget lever is off). max_step_pct: the biggest step one change may take, 1 to 50 percent of the current bid or budget (default 20). max_daily_increase: the most one change may add to a day's budget, in the ad account's currency (null: only the percentage applies). levers: which kinds of change the agent may propose (pause, budget, bid). protected_entities: campaign, ad set or keyword ids it must never propose to change. These limits also hold when a member applies a change, from here or the dashboard: one outside them is refused.	Use this only when the user asks to change how far Apptiller may go with an app's ad changes. Sets, for one app, how far Apptiller's agent may go. Owners and admins only. Fields left out stay as they are. mode: watch (the agent only reports), ask (it proposes changes and a member approves each one; the default) or autopilot. autopilot: it applies its own proposals inside these limits by itself, two changes a day at most (where the account's plan includes it; needs a linked ad account that is being read, an attribution source, and max_daily_increase unless the budget lever is off). max_step_pct: the biggest step one change may take, 1 to 50 percent of the current bid or budget (default 20). max_daily_increase: the most one change may add to a day's budget, in the ad account's currency (null: only the percentage applies). levers: which kinds of change the agent may propose (pause, budget, bid). protected_entities: campaign, ad set or keyword ids it must never propose to change. These limits also hold when a member applies a change, from here or the dashboard: one outside them is refused.	Yes	No	Yes	No
`set_site_guides`Use this only when the user asks to turn website guides on or off. Turns daily guides on or off for one app's website. On needs the website verified, in a connected Google Search Console, and a plan that includes them; the error says which is missing. Each morning after that, Apptiller writes at most one guide, only when a search or question is worth one (otherwise it drafts the fix for a page Google shows but few click, in To do), and pauses while 3 wait unpublished.	Use this only when the user asks to turn website guides on or off. Turns daily guides on or off for one app's website. On needs the website verified, in a connected Google Search Console, and a plan that includes them; the error says which is missing. Each morning after that, Apptiller writes at most one guide, only when a search or question is worth one (otherwise it drafts the fix for a page Google shows but few click, in To do), and pauses while 3 wait unpublished.	Yes	No	Yes	No
`setup_suggestions`Use this when the user asks what to set up next in Apptiller, or why some numbers are missing. What this Apptiller account is still missing (connections to add or repair, settings in tools already used), each with why it helps and how to do it. Steps marked optional need a change in the user's app.	Use this when the user asks what to set up next in Apptiller, or why some numbers are missing. What this Apptiller account is still missing (connections to add or repair, settings in tools already used), each with why it helps and how to do it. Steps marked optional need a change in the user's app.	No	Yes	Not declared	No
`site_guides`Use this when the user asks about the guides Apptiller writes for their app's website. Daily guides for one app's website: whether they're on and what's missing to turn them on (a verified website in a connected Search Console, and a plan that includes them), and its guides, newest first. Each guide answers one need no page on the site answers: Google searches that show the site but are rarely clicked (the search and its numbers), a question Google's AI answers leave the app out of (its answers), or both. finding_id is the To do item's finding it was written for and finding_ids all of that item's findings (empty for guides written before items had findings): the need behind it, the title, address slug, meta description, the guide in Markdown with its two calls to action, the sentences to add on the site's own pages to link to it, and every claim the check read with what backs it (status held: something couldn't be backed; fix it before publishing). agent_spec is the whole job for a coding agent: where the page goes, its head tags and structured data, the links to add, the checks. Published guides carry their Google clicks and impressions since. Guides written from research also carry research (what they were written from, each part with its source and date or why it is missing: the site's Search Console searches on the topic, its App Store search terms, labelled as App Store demand and not Google volume, the tracked AI questions, the product's facts, the site's pages, Google's results and the top pages read, and Google search volume and difficulty), plan (the target searches by research id, the sections and the searches each serves, internal links from the site's pages, the FAQ), watch (the Google searches it targets) and, once published, watched (each of those searches' clicks, impressions and position on its address since). readiness.last_run says how the last morning run ended: a guide, the fix for a page's search finding drafted instead (its finding id), nothing	Use this when the user asks about the guides Apptiller writes for their app's website. Daily guides for one app's website: whether they're on and what's missing to turn them on (a verified website in a connected Search Console, and a plan that includes them), and its guides, newest first. Each guide answers one need no page on the site answers: Google searches that show the site but are rarely clicked (the search and its numbers), a question Google's AI answers leave the app out of (its answers), or both. finding_id is the To do item's finding it was written for and finding_ids all of that item's findings (empty for guides written before items had findings): the need behind it, the title, address slug, meta description, the guide in Markdown with its two calls to action, the sentences to add on the site's own pages to link to it, and every claim the check read with what backs it (status held: something couldn't be backed; fix it before publishing). agent_spec is the whole job for a coding agent: where the page goes, its head tags and structured data, the links to add, the checks. Published guides carry their Google clicks and impressions since. Guides written from research also carry research (what they were written from, each part with its source and date or why it is missing: the site's Search Console searches on the topic, its App Store search terms, labelled as App Store demand and not Google volume, the tracked AI questions, the product's facts, the site's pages, Google's results and the top pages read, and Google search volume and difficulty), plan (the target searches by research id, the sections and the searches each serves, internal links from the site's pages, the FAQ), watch (the Google searches it targets) and, once published, watched (each of those searches' clicks, impressions and position on its address since). readiness.last_run says how the last morning run ended: a guide, the fix for a page's search finding drafted instead (its finding id), nothing	No	Yes	Not declared	No
`to_do`Use this when the user asks what to do next for an app, or what is waiting for their approval. What to do next for an app, or for every app: the open items of Apptiller's To do list, best first, as the web app shows them. Splits: To approve (listing edits, App Store drafts, findings with a page or pitch to write, ad proposals), Review replies (reviews without an answer, with any drafted reply), Reach out (threads to join, lists to get onto) and New today (alerts). Each item has its app, kind, title, detail, why it is here, evidence, before and after text, what its action does (where it is written, whether it is public, whether it can be undone), due date, score, and locked: the plan feature its action needs when the account's plan lacks it. Snoozed and done items are left out. unavailable names any part that couldn't be read just now. Read-only: it approves, sends, rejects or marks nothing; each item carries the web app page where that is done.	Use this when the user asks what to do next for an app, or what is waiting for their approval. What to do next for an app, or for every app: the open items of Apptiller's To do list, best first, as the web app shows them. Splits: To approve (listing edits, App Store drafts, findings with a page or pitch to write, ad proposals), Review replies (reviews without an answer, with any drafted reply), Reach out (threads to join, lists to get onto) and New today (alerts). Each item has its app, kind, title, detail, why it is here, evidence, before and after text, what its action does (where it is written, whether it is public, whether it can be undone), due date, score, and locked: the plan feature its action needs when the account's plan lacks it. Snoozed and done items are left out. unavailable names any part that couldn't be read just now. Read-only: it approves, sends, rejects or marks nothing; each item carries the web app page where that is done.	No	Yes	Not declared	No
`undo_change`Use this only when the user asks to undo a change Apptiller made. Puts back, at the user's request, the value an ad account had before Apptiller changed it. Only while the campaign, ad group or keyword still has the value Apptiller wrote: if it was changed since, nothing is written. It changes the live ad account.	Use this only when the user asks to undo a change Apptiller made. Puts back, at the user's request, the value an ad account had before Apptiller changed it. Only while the campaign, ad group or keyword still has the value Apptiller wrote: if it was changed since, nothing is written. It changes the live ad account.	Yes	No	No	No
`verify_domain`Use this when the user wants to prove they own a domain. Starts proving the organization owns a domain, or checks it again: returns the TXT record to add at the domain's DNS provider (host and value), and whether Apptiller finds it now. Apptiller also looks for it every hour for 72 hours. Calling it again for the same domain keeps the same record. A verified domain proves an app is the organization's when the app's App Store listing points to it.	Use this when the user wants to prove they own a domain. Starts proving the organization owns a domain, or checks it again: returns the TXT record to add at the domain's DNS provider (host and value), and whether Apptiller finds it now. Apptiller also looks for it every hour for 72 hours. Calling it again for the same domain keeps the same record. A verified domain proves an app is the organization's when the app's App Store listing points to it.	No	No	Yes	Yes

Details

Registry status: Active
Published: Nov 9, 2026
Updated: Nov 9, 2026
Website: https://apptiller.com/features/claude-chatgpt-connector⁠ (opens in a new tab)
Repository: https://github.com/GPT-Genius-Lab/apptiller-mcp⁠ (opens in a new tab)
Categories (suggested): Marketing and SEOSuggested categories are assigned automatically from the registry text and may be wrong. Verified operators can correct them.
GDPR: Not declared

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