App Store Operator
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| ASO_DEBUG_RATINGS | No | Set to 1 to dump the SensorTower Ratings and Reviews panel text to stderr when rating score or count come back N/A. Leave unset to disable. | |
| ASO_CACHE_TTL_HOURS | No | How long research_rivals results stay cached before re-scraping. Defaults to 24 when unset. | 24 |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {} |
| prompts | {} |
| resources | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| research_rivalsA | Search the App Store for a keyword and fetch SensorTower analytics for the top results — all in one call. Results are cached for 24 hours so repeat queries are instant. Use this for a quick competitive overview when you want everything in one step.
Use Requires a SensorTower account. On a cache miss the server opens a real Chromium window on the user's machine; the first run needs the user to log in there, and the session is reused from then on. If there is no session the call returns an error result carrying Trigger phrases: "rival research", "research rivals", "competitor analysis", "find competing apps", "check competitors", "what apps compete with", "App Store competitors", "rivals for keyword". Returns JSON: Fields missing or gated behind a paywall will be Present results as a clean report for each app: #1 — {name}
|
| search_app_storeA | Search the App Store for a keyword and return ranked results as a detailed table — instantly, no browser required. Use this when you want to discover which apps rank for a keyword before deciding which ones to analyse in depth.
Unlike Returns markdown (not JSON): one table per result, ranked, with every App Store field available including the numeric app ID that |
| get_app_detailsA | Fetch SensorTower analytics for one or more App Store app IDs. Returns downloads, revenue, ratings, publisher info, markets, and more for each app. Use this when you already have app IDs (e.g. from Requires a SensorTower account. The server opens a real Chromium window on the user's machine; the first run needs the user to log in there, and the session is reused from then on. If there is no session the call returns an error result carrying Returns JSON: Fields missing or gated behind a paywall will be |
| prepare_iaeA | Prepare an iOS App Store In-App Event (IAE) — generate copy variations and a final report. Use this when the user wants to create or draft an in-app event, prepare IAE metadata, or generate App Store event copy. Accepts user-supplied keywords and event parameters, then returns a structured brief. Do not use it for ordinary App Store listing metadata (title, subtitle, description) — it covers In-App Event fields only. Runs entirely locally: no network calls, no App Store or SensorTower lookup, and no keyword research of its own — the caller supplies the keywords (reach for After receiving the tool output, you MUST:
Output table: Final summary report: Flag any checklist item that is not yet satisfied. Returns JSON with the structured brief for generating copy. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
| competitor_snapshot | Full competitive read on one App Store keyword: pulls rival downloads, revenue, and ratings, then summarises who owns the keyword and how contested it is. |
| keyword_shortlist | Expands one seed keyword into a ranked shortlist of App Store search terms worth targeting, each checked against live search results. |
| app_teardown | Deep teardown of one or more known App Store apps: analytics, monetisation, market spread, and what their numbers imply about strategy. |
| positioning_gap | Compares your app against the rivals ranking for a keyword and identifies where you are behind, level, or able to attack. |
| metadata_rewrite | Rewrites App Store name, subtitle, and keyword field against live rival listings, with hard character counts on every field. |
| in_app_event | Runs the full In-App Event workflow: builds the brief, generates three copy variations inside Apple's character limits, and produces the final report. |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
| tool_selection_guide | Which tool to reach for, what each one costs, how the SensorTower login works, and how to treat missing data. |
| country_codes | Two-letter storefront codes accepted by every tool's `country` argument, grouped by region. |
| aso_fields | Character limits and indexing behaviour for app name, subtitle, keyword field, promotional text, and description. |
| iae_fields | Character limits, artwork sizes, copy rules, and keyword tiers for iOS In-App Events. |
| iae_locales | Every locale `prepare_iae` accepts, with its Apple locale code, language, country, and keyword storefront. |
| research_cache_index | Keyword/country pairs already researched on this machine, with their age and whether they are still fresh. |
TDQS
Scored across 4 tools
The four tools have clearly distinct purposes: search_app_store for discovery, get_app_details for analytics on specific IDs, research_rivals as a combined convenience wrapper, and prepare_iae for in-app event copy generation. Each description explicitly tells when to use it versus the alternatives, eliminating ambiguity.
All tool names follow a consistent verb_noun pattern with snake_case: research_rivals, search_app_store, get_app_details, prepare_iae. Verbs (research, search, get, prepare) clearly indicate actions, and nouns (rivals, app_store, app_details, iae) identify the target. No mixing of casing or verb styles.
Four tools is well-scoped for an iOS App Store operations server. The primary workflows are covered: discovering apps (search_app_store), retrieving analytics (get_app_details), a combined research shortcut (research_rivals), and creating in-app events (prepare_iae). No bloat or redundancy; each tool earns its place.
The tool surface covers the main research and IAE copy generation workflows thoroughly. Minor gaps exist: no tool for managing App Store listing metadata (title, description), and no explicit handling of Google Play, but the tool descriptions clearly scope the server to iOS App Store research and IAE. The explicit boundary is acceptable, though a listing-management tool would round out the 'Operator' name.