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App Store Connect MCP Server

App Store Connect MCP Server

by yunyang088
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Local

get_beta_feedback_screenshot

Retrieve details for a specific App Store Connect beta feedback screenshot, including optional build and tester info, and download the image.

Instructions

Get detailed information about a specific beta feedback screenshot submission. By default, downloads and returns the screenshot image.

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": {
      "feedbackId": "<feedbackId>"
    },
    "name": "get_beta_feedback_screenshot"
  }
}

Input Schema

NameRequiredDescriptionDefault
feedbackIdYesThe ID of the beta feedback screenshot submission
includeBuildsNoInclude build information in response (optional)
includeTestersNoInclude tester information in response (optional)
downloadScreenshotNoDownload and return the screenshot as an image (default: true)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.1.3

TDQS

A3.7/5.0
Behavior3/5

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

With no annotations, the description carries the burden. It states the default download behavior and the ability to disable it. However, it does not mention whether the operation is read-only, what happens to the resource, or any side effects. The description is adequate but could be more explicit.

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

Conciseness5/5

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

The description is concise with two sentences, front-loading the main action and default behavior. No unnecessary words or repetition.

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

Completeness3/5

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

The description mentions 'detailed information' but does not specify what details are returned beyond the screenshot image. With no output schema, the user is left guessing about the non-image response content. Given the complexity of 4 parameters and a potential image return, more detail about the response would improve completeness.

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 coverage is 100%, so the schema already describes all parameters adequately. The description adds minimal extra context beyond confirming the default for downloadScreenshot. It does not significantly enhance understanding of parameter meaning.

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?

The description clearly states the tool's action ('get detailed information') and resource ('a specific beta feedback screenshot submission'). It also mentions the default behavior of downloading the image, which distinguishes it from the sibling tool that lists screenshots.

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 does not explicitly state when to use this tool over alternatives like list_beta_feedback_screenshots. It implies usage for a specific submission but lacks guidance on context or 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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