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adhistory-mcp

adhistory-mcp

by OBrandon
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

App Store & Google Play reviews

app_reviews
Read-onlyIdempotent

Retrieve and filter iOS App Store and Google Play reviews by star rating to analyze user feedback, identify complaints, and compare apps across countries.

Instructions

Get user reviews for iOS App Store and Google Play apps. Each item: store, app id and name, country, rating (1-5), title, review text, date, app version, helpful votes, developer reply and link. Filter by star rating (e.g. min 1 / max 2 for complaints only). Apps can be App Store URLs or IDs (324684580), Google Play URLs or package names (com.spotify.music), or an app name (App Store search). Cost: $0.10 per 1,000 reviews on the user's Apify account; the default 20 reviews per app cost a fraction of a cent. Latency: usually 10-40 s.

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": {
      "apps": "<apps>"
    },
    "name": "app_reviews"
  }
}

Input Schema

NameRequiredDescriptionDefault
appsYesApp Store / Google Play URLs, IDs, package names or app names.
sortNoWhich reviews come first.newest
languageNoGoogle Play review language, e.g. en, es, de.en
countriesNoTwo-letter country codes, e.g. ['us', 'gb'].
max_ratingNoKeep reviews with at most this many stars.
min_ratingNoKeep reviews with at least this many stars.
max_reviews_per_appNoPer app and country. The App Store returns at most 500.

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.4.0

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true and destructiveHint=false, so safety is covered. The description goes beyond them with cost ($0.10 per 1,000 reviews, default 20 is a fraction of a cent) and latency (10-40 s), which materially affect whether an agent should call it and how long to wait. The enumerated return fields are partly redundant with the output schema.

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?

Three sentences, front-loaded with purpose, then data shape, then filtering and cost/latency. Efficient overall, but the long 'Each item: store, app id and name, country...' enumeration is largely wasted text because an output schema exists.

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?

For a read-only multi-source scraper with a full output schema, the description covers the essentials an agent needs: what is returned, how to specify apps, how to filter, cost, and expected latency. Minor gaps remain around rate limits or partial-failure behavior across multiple apps, but nothing critical is missing.

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

Parameters3/5

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

Schema description coverage is 100%, and the description mostly restates what the schema already says (identifier formats, star filtering). The 'for complaints only' framing of min/max rating adds a small amount of interpretive value, but there is no added detail on sort, language, or country interaction beyond what the schema provides. Baseline 3 is appropriate.

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?

States a specific verb and resource ('Get user reviews for iOS App Store and Google Play apps') and immediately scopes the source to the two stores. That is clearly distinct from every sibling tool, which cover entirely different data domains (ads, jobs, invoices, PDFs).

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

Usage Guidelines4/5

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

Gives concrete usage context: the star-rating filter example ('min 1 / max 2 for complaints only') signals the complaint-mining use case, and the accepted app identifier forms tell the caller exactly what to pass. It stops short of explicit when-not-to-use guidance or naming an alternative, so it falls short of a 5.

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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