webdata-tools-mcp

Get App Store and Google Play reviews

get_app_reviews

Read-onlyIdempotent

Fetch app reviews from Apple App Store and Google Play in one dataset, filtered by country and star rating, for feedback and sentiment analysis.

Instructions

Reviews from the Apple App Store and Google Play in one dataset: rating, text, author, date, app version, developer reply, sentiment. Mix both stores and several countries. Runs the Apify Actor tacps126/app-reviews on your Apify account (about $0.0002 per review; spend per call is capped at $0.5).

Input Schema

TableJSON Schema

Name	Required	Description
`apps`	Yes	App Store / Google Play links, App Store ids ("id324684580") or Android package names ("com.spotify.music").
`countries`	No	Two-letter store countries, e.g. ["us","gb"].
`max_items`	No	Maximum results to return (default 100, max 2000). Cost scales with this.
`extra_input`	No	Advanced: extra Actor input fields, merged over the defaults.
`star_ratings`	No	Only these ratings, e.g. ["1","2"].

Output Schema

TableJSON Schema

Name	Required	Description
`tool`	Yes	Name of the tool that produced the result.
`count`	Yes	Number of records the Actor returned.
`items`	Yes	The records. Long text fields are shortened to 600 characters.
`shown`	Yes	Number of records included in `items` (can be lower than count when the result is long).
`truncated`	Yes	True when records were left out to keep the result short; ask for fewer items.

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedv0.1.1Oct 17, 2026

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "$schema": "http://json-schema.org/draft-07/schema#",
+  "additionalProperties": false,
+  "properties": {
+    "count": {
+      "description": "Number of records the Actor returned.",
+      "maximum": 9007199254740991,
+      "minimum": -9007199254740991,
+      "type": "integer"
+    },
+    "items": {
+      "description": "The records. Long text fields are shortened to 600 characters.",
+      "items": {
+        "additionalProperties": {},
+        "propertyNames": {
+          "type": "string"
+        },
+        "type": "object"
+      },
+      "type": "array"
+    },
+    "shown": {
+      "description": "Number of records included in `items` (can be lower than count when the result is long).",
+      "maximum": 9007199254740991,
+      "minimum": -9007199254740991,
+      "type": "integer"
+    },
+    "tool": {
+      "description": "Name of the tool that produced the result.",
+      "type": "string"
+    },
+    "truncated": {
+      "description": "True when records were left out to keep the result short; ask for fewer items.",
+      "type": "boolean"
+    }
+  },
+  "required": [
+    "tool",
+    "count",
+    "shown",
+    "truncated",
+    "items"
+  ],
+  "type": "object"
+}

First observedv0.1.0Oct 17, 2026

TDQS

A3.9/5.0

Behavior4/5

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

Annotations already cover safety (readOnly, idempotent, non-destructive, openWorld), so the description is free to add operational context, which it does: it runs the Apify Actor tacps126/app-reviews on the caller's account, costs ~$0.0002 per review, and caps spend at $0.5 per call. That cost/execution detail is genuinely additive beyond the annotations, though latency and pagination behavior remain unstated.

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?

Two tight sentences that front-load what the dataset contains and then the execution/cost note. The 'Mix both stores and several countries' clause is slightly redundant with the opening clause but overall there is no wasted prose.

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 an output schema present, the description need not explain return values, and annotations carry the safety profile; the added cost and Actor-execution context rounds it out well. Minor gap: it doesn't reconcile the max_items ceiling with the $0.5 spend cap or mention result limits in practice.

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%, so all five parameters are already documented in the schema; baseline is 3. The description's mention of mixing stores and countries loosely maps to the countries parameter but adds no syntax or format detail beyond the schema.

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 ('Reviews from the Apple App Store and Google Play'), names the two data sources, and enumerates the returned fields. This is immediately distinguishable from the sibling get_trustpilot_reviews because the store sources are explicit.

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

Usage Guidelines3/5

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

The description implies usage ('Mix both stores and several countries') but never states when to prefer this tool over the similar sibling get_trustpilot_reviews or any exclusion criteria. Usage is inferable from the resource rather than stated.

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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