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app-store-connect-mcp

app-store-connect-mcp

by devinwang
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TypeScript
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build_uploads_get_instance

Fetch details for a specific App Store Connect build upload by ID, with optional relationships and fields for build, asset, and upload file data.

Instructions

GET /v1/buildUploads/{id} (GET /v1/buildUploads/{id})

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": {
      "id": "<id>"
    },
    "name": "build_uploads_get_instance"
  }
}

Input Schema

NameRequiredDescriptionDefault
idYesthe id of the requested resource
includeNocomma-separated list of relationships to include
fields_buildsNothe fields to include for returned resources of type builds
fields_buildUploadsNothe fields to include for returned resources of type buildUploads
fields_buildUploadFilesNothe fields to include for returned resources of type buildUploadFiles

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.5.0

TDQS

C2.1/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden, yet it discloses nothing beyond the HTTP GET verb (which weakly implies a read). It does not mention auth requirements, error behavior, or that it returns a single resource by id.

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

Conciseness2/5

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

At two tokens it is short but not concise in a useful sense: the parenthetical simply repeats the same route verbatim, so the second half is pure waste. Nothing is front-loaded because no meaningful content exists to front-load.

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

Completeness1/5

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

For a five-parameter GET tool with no output schema, the description provides essentially zero actionable context about what is returned or how the sparse-fieldset parameters shape the response. It is inadequate for correct invocation.

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 the schema already documents all five parameters (including the include and fields_* sparse-fieldset options). The description adds nothing about parameters, which meets the baseline of 3 when the schema does the heavy lifting.

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

Purpose2/5

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

The description is just the raw HTTP route 'GET /v1/buildUploads/{id}' repeated twice, which essentially restates the tool name without explaining in human terms what a build upload resource is or why an agent would fetch one. An agent can infer it retrieves a single build upload, but gets no semantic understanding beyond the verb+path.

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

Usage Guidelines2/5

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

There is no when-to-use guidance, no mention of prerequisites, and no routing to alternatives. The description neither distinguishes this from the many sibling *_get_instance tools nor states any condition under which it should be preferred.

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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