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Fourni-j

App Store Connect MCP Server

by Fourni-j

get_customer_reviews

Retrieve customer reviews and ratings for any app. Filter by star rating, territory, and date range to analyze user feedback and monitor App Store performance.

Instructions

Get customer reviews and ratings for an app. Returns individual written reviews with aggregated rating statistics (average rating, star distribution). Also fetches the official App Store rating (average + count) from the iTunes Lookup API — set storeCountry (2-letter ISO code, default 'US') to get ratings for a specific country. Written reviews can be filtered by star rating, territory (3-letter code like 'USA', 'FRA'), and date range. Sorted by newest first by default. Requires appId from list_apps.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sortNoSort order (default: -createdDate, newest first)-createdDate
appIdYesApp Store Connect app ID (from list_apps)
limitNoMax reviews to fetch (default 500, max 1000)
ratingNoFilter by star rating (1-5)
endDateNoFilter reviews on or before this date (YYYY-MM-DD)
startDateNoFilter reviews on or after this date (YYYY-MM-DD)
territoryNoFilter by territory code (e.g. 'USA')
storeCountryNoISO 2-letter country code for App Store rating lookup (default 'US'). Ratings vary by country.US
Behavior4/5

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

Discloses behavior: returns written reviews, aggregated stats, fetches iTunes rating, supports filtering by rating/territory/date, default sorting, and limit. No annotations provided, so description carries burden effectively.

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?

Multiple sentences, each adding value. Structure is front-loaded with main purpose. Could be slightly more concise but not wasteful.

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?

Fairly complete given 8-param tool with no output schema. Covers sources, filtering, sorting, prerequisite. Lacks pagination details but limit implies single request. Adequate.

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%, but description adds context: explains storeCountry's purpose (iTunes Lookup API), territory as 3-letter code, and default sorting. Enhances understanding beyond 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?

Description clearly states it retrieves customer reviews and ratings, including aggregated statistics and iTunes API ratings. Differentiates well from sibling tools like list_apps and analytics tools.

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?

States prerequisite appId from list_apps and describes various filtering options. Does not explicitly compare to siblings, but purpose is distinct. Could mention when not to use.

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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