What is the AppGoat remote MCP server?
The AppGoat remote MCP server is a hosted Model Context Protocol endpoint at https://api.appgoat.ai/mcp, so AI assistants can connect to it without installing or running anything locally.
AppGoat MCP ServerVerifiedFeatured
Basic information
About AppGoat MCP Server
App Store and Google Play data for agents: apps, reviews, keyword research, top charts, competitors and ASO audits.
Connection details
https://api.appgoat.ai/mcpSetup
claude mcp add appgoat --transport http https://api.appgoat.ai/mcpAppGoat MCP Server tools
29Look up one App Store or Google Play app: title, subtitle, developer, category, price, rating and histogram, installs (Play), version and dates, description, languages, and the same app in the other store. Accepts any id, bundle id, package, store URL or a name. Reads stored data (refreshed from the store only when older than max_age, default 7 days) for one country (default us); add include sections for markets, versions, IAP, privacy, estimates and chart positions. Cost: 1 + 1 per country refreshed from the store (max 10) credits.
Read an app's user reviews, newest first, up to 100 per page: rating, title, text, version, date, developer reply and AI tags (sentiment, intent, severity, topic) where tagged. Filter by stars (rating='1-2' for complaints), version, date range, text (q) or AI tags (intent='bug,crash'; tag filters skip untagged reviews). Page with cursor. Cost: 1 per page + 1 if the US reviews are refreshed credits.
An app's daily metric history per country: rating, ratings count, reviews count, installs (Play), star histogram and price, one row per day a value changed (default the last 90 days), with the change over the period. Use it to chart growth or spot rating drops after a release. Cost: 1 + 1 per country refreshed (max 10) credits.
What changed in an app's store listing, newest first, with old and new values: version, release notes, title, subtitle, description, screenshots, icon, price, IAP, privacy, in-app events, badges, featuring, installs, content rating. Use it to monitor competitors ("what did X change this month?"). Cost: 1 + 1 if the US listing is refreshed credits.
The search terms an app ranks for in a country, best rank first, with popularity (5–100) and difficulty (0–100): from the weekly keyword universe plus your tracked keywords. Call it for the app and a competitor to find keyword gaps. Cost: 1 credits.
An app's competitors, best first, scored from search terms both apps rank for (shared keywords) plus the store's similar-apps list. Feed the app ids into get_app or get_app_changes for a competitor digest. Cost: 1 credits.
Find apps by name or id in AppGoat's catalog of both stores (~5M apps): exact title matches first, then prefix, then substring, most-rated first. Returns store, app_id, title, developer, category, rating, ratings and price; pass the app_id to the other tools. Cost: 1 credits.
A top free, paid or grossing chart for a store, country and category, today or on a past date: rank, app, developer, rating and the move since the previous capture (new entries marked), plus apps that dropped out. Charts are captured daily for every country and category. Cost: 1 credits.
Keyword metrics and research for App Store / Google Play search terms: popularity (5–100), difficulty (0–100), result count and the #1 result's estimated daily downloads. include adds related terms with metrics, the store's autocomplete and the current top 10 apps; app adds that app's rank and metadata relevance per term (the core of an ASO keyword audit). Unmeasured terms are measured live (a few per call) or come back pending. Cost: 1 per keyword; 5 per seed with include=related or suggestions credits.
Deprecated: use watch with kind keyword (also reports rank moves as events). Starts tracking the search ranking of terms in one or both stores and the given countries: ranked apps are captured daily from now on (idempotent; already tracked terms are reported as such). Each term × store × country uses one keyword slot of the plan; a request over the limit tracks nothing (plan_limit). Read history with get_keyword_ranks. Cost: 0 credits.
Deprecated: use unwatch for keyword watches. Stops tracking keywords by id (from list_tracked_keywords or track_keywords): no new rankings are recorded and their plan slots are freed. Cost: 0 credits.
Deprecated: use list_watches (keyword watches list their slots). Your tracked keywords with id, store, country, popularity, depth, cadence, last ranking and current top 3. Filter by store, country or a term substring. Cost: 0 credits.
Ranking history of a watched keyword: per capture the top 10 app ids, or with app, that app's rank over time (best, worst, latest). Default the last 90 days. The id is a keyword slot of a keyword watch (list_watches and watch show the slot ids) or a list_tracked_keywords id. Cost: 1 credits.
Watch an app, a set of competitors or a set of keywords; significant changes become events (get_events, webhooks, daily email). kind app {app}: new versions, metadata and price changes, featuring, rating drops, review and ratings spikes, chart entries. kind competitor_set {competitors, app?}: the same for every competitor. kind keyword {terms, store or app}: the app's rank moves per term and new apps in the top N. Watched apps count against the plan's watch limit, keyword watches use one keyword slot per term × store × country; over a limit nothing changes (plan_limit). With id, changes that watch instead (send only what changes; settings are merged; active=false pauses it). Cost: 0 credits.
Stop watches by id (from list_watches or watch): no new events, and their watched apps and keyword slots are freed. Past events are kept. To pause instead, call watch with id and active=false. Cost: 0 credits.
Your watches (apps, competitor sets, keyword sets), newest first, with id, apps, terms, countries, event types and whether they are paused, plus watched apps and keyword slots used vs the plan's limits. Filter by kind or by an app they include. Cost: 0 credits.
Significant changes on your watched apps and keywords, newest first: type, one-line title, AI summary, significance (0–1), app, country and the key payload fields (version, changes old → new, rating drop, rank move, chart rank…). Filter by type, app, watch, since and min_significance. To check for news, pass since = the created_at of the newest event already handled. Cost: 0 credits.
A developer's profile: name, website, country, app count, total ratings and installs, all their apps (most-rated first) and the same company in the other store. get_app shows the developer id as dev <store>:<id>. Cost: 1 credits.
Poll a background store fetch that another call started (its output said refreshing or still being fetched, with a job id): status, per-country progress. When it is done, repeat the original call. Cost: 0 credits.
The user's connected App Store Connect, Play Console and Apple Ads accounts: connection id, provider, mode (actions or read_only), status and the linked apps. Start here before read_connection or propose_action; secrets are never returned. No connections yet: the user adds them at https://dash.appgoat.ai/connections. Cost: 0 credits.
Read live data from one of the user's connected accounts. what='reviews' (asc, play_console): the app's own reviews with reply status, unanswered=true for those without a developer reply; their review_id feeds propose_action review.reply (Play only returns reviews from the last 7 days). what='listing' (asc, play_console): the current listing text for one locale with lengths and which fields are editable right now (App Store name, subtitle, description, keywords and what's new need a version in Prepare for Submission). what='ads' (apple_ads): view=campaigns → ad_groups (campaign_id) → keywords (campaign_id, ad_group_id) gives the ids the ads.* actions take, view=negatives lists negative keywords, view=report with level=campaigns|adgroups|keywords|searchterms returns impressions, taps, installs, spend, CPT and CPA for start..end (default the last 7 days). Cost: 1 credits.
Prepare a change to the user's connected account as a DRY RUN: nothing is written. AppGoat reads the live account and returns the before → after diff, guardrail results (AI probabilities for store policy, tone and risky claims, plus checks such as character limits and bid jumps) and an action id. ALWAYS show the diff and any guardrail flags to the user and get their go-ahead before calling apply_action. Types and params (app = a linked App Store id or package name, locale like en-US): review.reply {app, review_id, text} (review ids from read_connection what=reviews; Play replies ≤ 350 chars); listing.update {app, locale, fields: {name|title, subtitle, description, promotional_text, whats_new, marketing_url, support_url, privacy_policy_url}} (Play: title, short_description, full_description, video); keywords.set {app, locale, keywords: [..] or 'a,b,c', mode?: replace|add|remove} (App Store, 100 bytes comma-joined); screenshots.upload {app, locale, display_type: APP_IPHONE_67… (asc) or image_type: phoneScreenshots… (play), images: [{url}], replace?}; ads.keyword.bid {campaign_id, ad_group_id, keywords: [{id, bid?, status?: ENABLED|PAUSED}], max_increase?}; ads.keyword.add {campaign_id, ad_group_id, keywords: [{text, match_type?: EXACT|BROAD, bid?}]}; ads.negative.add {campaign_id, ad_group_id?, keywords: [{text, match_type?}]} (Apple Ads ids from read_connection what=ads). Cost: 0 credits.
Go ahead with an action from propose_action, after the user has seen its diff and agreed. Outcomes: applied (written to the store / Apple Ads account, 1 credit; when the org has an auto-apply rule the guardrail score clears, or allows agents to approve); pending_approval (a person must approve it in the AppGoat dashboard: give the user the approve link, nothing is written until then); needs a person (it was already pending and agents may not approve: hand over the link, do not retry); changed (the account changed since the dry run: the new diff is shown; show it to the user and call again with force=true only if they accept it, or propose_action again). Cost: 1 credit when applied, else 0 credits.
One action from propose_action: its status (draft, pending_approval, approved, applied, failed, rejected), diff, guardrail scores, the provider result or error, the approve link and the audit trail. Use it to check whether a pending action was approved and applied. Cost: 0 credits.
Discard a draft or pending action the user does not want; nothing is written to the account. Cost: 0 credits.
Run an App Audit of one app in one country: a 0–100 score, prioritised ASO actions with evidence, title / subtitle / keyword rewrites within the store character limits, and findings from listing, ratings, reviews, keywords and competitors, plus a shareable report page. Takes 1–3 minutes: waits about 25 s, then returns the audit id to pass to get_audit. An audit of the same app, country and mode from the last 24 h is returned again for free unless fresh=true; failed audits are not charged. The first audit of an organization is free (free_only=true runs only that one). Cost: 100 credits.
Check on an App Audit that audit_app started (by its id, e.g. aud_3fK9aQ2mXc81LpRt): waits up to about 25 s for it to finish, then returns the report (score, actions, metadata rewrites, findings, report page) or its status. Cost: 0 credits.
What an app's users praise and complain about, from the AI tags on its reviews: top issues (topics behind negative, bug, crash, UX and pricing reviews) with last-30-days vs previous-30-days counts and sample reviews, topics, what each recent version changed in rating, sentiment and topics, and weekly sentiment. Use it for "what do users complain about since v2.3?" before reading individual reviews with get_reviews. Cost: 25 credits.
AppGoat playbooks: step-by-step recipes (which tools to call, credit budget, decision rules, output format) for app audits, app idea research, ASO metadata rewrites, weekly competitor digests, turning reviews into GitHub issues, and, on connected accounts, replying to every review, optimizing Apple Ads and pushing localized listings. Without name, lists them; with name, returns the full playbook to follow. Also offered as MCP prompts. Free.
Overview
AppGoat gives AI assistants live App Store and Google Play data. Look up any app from a name, id, bundle id or store URL. You get metadata, ratings and histogram, versions, and the same app in the other store. Read reviews with AI tags (bugs, crashes, feature requests), daily rating and install history, listing changes with old and new values, and top free, paid and grossing charts on any date. Find competitors from shared keywords.
For ASO, AppGoat researches keywords: popularity, difficulty, related terms and autocomplete. It reports the keywords an app ranks for and runs a full App Audit. The audit returns a score, prioritised actions and metadata rewrites within the store's character limits. Watch apps, competitor sets and keywords, and significant changes become events your agent can act on.
On your own connected App Store Connect, Play Console and Apple Ads accounts, AppGoat reads reviews, listings and ads data. It proposes review replies, listing updates and bid changes as dry runs, with a before-and-after diff that a person approves before anything is written.
Built-in playbooks run as prompts: app audit, find app ideas, ASO keyword rewrite, competitor digest, and reviews to GitHub issues.
Sign in with your AppGoat account (OAuth). The free plan includes monthly credits.
Frequently asked questions
How do I connect to the AppGoat MCP server?
Add the endpoint https://api.appgoat.ai/mcp to any MCP-compatible client such as Claude Code, Cursor, or VS Code. The setup snippets on this page configure each client in one step.
Does the AppGoat MCP server require authentication?
Yes. AppGoat uses OAuth: the first time you connect, your MCP client opens a browser window to sign in and authorize access, then reuses the credentials for future sessions.
Which transport does the AppGoat MCP server use?
AppGoat exposes a Streamable HTTP endpoint, the transport used by remote MCP servers and supported by all major MCP clients.
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