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App Store Review Intelligence MCP Server

App Store Review Intelligence MCP Server

by gunnargray-dev
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Hybrid

Review insights & what got worse

review_insights
Read-onlyIdempotent

Analyze recent App Store and Google Play reviews to reveal rating trends, top complaints, version changes, and sample quotes, helping diagnose user dissatisfaction and update impact.

Instructions

Best first call for any question about an app's user feedback. Analyses recent reviews and returns: rating distribution, average rating per app version, top complaint phrases from 1-2★ reviews (share + example quote), versionDeltas (latest version vs earlier: rating change, negative-share change, rising complaints with quotes; falls back to last 3 days vs earlier), and sample quotes. Use for "why are users unhappy with X", "what broke in the last update", "top complaints about X", "summarize feedback". One flat price per call regardless of pages/countries. For the review text itself use get_app_reviews; to benchmark several apps at once use compare_apps. Apple and Google Play.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "app_id": "<app_id>"
    },
    "name": "review_insights"
  }
}

Input Schema

NameRequiredDescriptionDefault
langNoGoogle Play only: review/listing language, e.g. "en", "de", "pt-BR". Default "en". Ignored for Apple.en
pagesNoReview pages to fetch, ~50 newest reviews each (1-10). Default 3.
storeNo"apple" (App Store) or "google" (Google Play). Optional: inferred from app_id (numeric → apple, package name → google).
app_idYesApp to analyse. Apple: numeric id (284882215), "id284882215" or an apps.apple.com URL. Google Play: package name (com.instagram.android) or a play.google.com URL. Get ids from search_apps.
quotesNoSample quotes per sentiment (0-10). Default 3.
countriesNoStorefronts to pool, e.g. ["us","gb","ca"]. Default ["us"]. More countries = bigger sample.
keyword_limitNoComplaint phrases to return. Default 15.
since_versionNoOptional: compare reviews on this version and newer against older versions (e.g. "450.0.0"). Default: newest version in the sample vs earlier ones.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.1.0

TDQS

A4.5/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already cover read-only/idempotent/non-destructive, but the description adds real behavior beyond them: a flat per-call price independent of pages/countries, the versionDeltas fallback to "last 3 days vs earlier" when version data is thin, and the shape of each returned block. It stops short of error modes or data-freshness limits, so 4 rather than 5.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with the highest-value routing sentence ("Best first call for any question about an app's user feedback") before the return-value enumeration. The versionDeltas clause is dense and nested with parentheses, but every sentence carries usage or output information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema and 8 parameters, the description carries the return-shape burden and does so thoroughly, including fallback behavior. Gaps are minor: no statement on data freshness/recency window or failure behavior when an app has few reviews.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so baseline is 3, but the description adds decision-relevant semantics: price is flat regardless of pages/countries, so an agent need not minimize them, and the versionDeltas fallback clarifies what happens when since_version is omitted. It does not explain keyword_limit or quotes behavior beyond the schema, so not a 5.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Specific verb+resource (analyses recent reviews) plus an explicit enumeration of what is returned: rating distribution, average rating per version, complaint phrases with share and quote, versionDeltas, sample quotes. It also names the two siblings it is not (get_app_reviews, compare_apps), so an agent can route without opening schemas.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It states both a positive trigger ("Best first call for any question about an app's user feedback") with concrete exemplar queries ("why are users unhappy with X", "what broke in the last update") and negative routing to alternatives for raw review text and multi-app benchmarking. When-to-use and when-not-to-use are both explicit.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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