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Developer ToolsAuto-generatedScore: 46

App Store Connect API MCP Server

The App Store Connect API, provided by Apple, serves as the definitive programmatic interface for managing the complete lifecycle of iOS, macOS, watchOS, and tvOS applications on the App Store.

Quick Start Summary

The App Store Connect API MCP server is a Model Context Protocol bridge that connects AI assistants — including Claude Desktop, Cursor, Windsurf, and VS Code Copilot — to the App Store Connect API API through natural language. It exposes 10 API endpoints as callable tools, such as ageRatingDeclarations-update_instance, appCategories-get_collection, appCategories-get_instance, and more. No authentication is required — setup takes approximately 30 seconds. The server uses STDIO transport and can be installed by running npx -y @mcp/apple-com-app-store-connect. This integration is sourced from the auto App Store Connect API OpenAPI specification (v1.4.1) and has a quality score of 46/99 (fair documentation coverage).

10Endpointstools mapped
NoneAuthopen access
46/99Qualityfair
~30 secSetupno auth
View Hosted Config URLClaude Desktop Setup Guide

Server Details

Category
Developer Tools
Authentication
None
Endpoints
10 operations
Transport
STDIO
Spec Version
v1.4.1
Install Command
npx -y @mcp/apple-com-app-store-connect

Environment Variables

APP_STORE_CONNECT_API_API_KEY

Example: your_app_store_connect_api_api_key

Top Endpoints

PATCH
/v1/ageRatingDeclarations/{id}

ageRatingDeclarations-update_instance

GET
/v1/appCategories

appCategories-get_collection

GET
/v1/appCategories/{id}

appCategories-get_instance

GET
/v1/appCategories/{id}/parent

appCategories-parent-get_to_one_related

GET
/v1/appCategories/{id}/subcategories

appCategories-subcategories-get_to_many_related

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📖 Detailed MCP Integration Guide

A technical breakdown of capabilities, agent workflows, and security/configuration best practices.

⚡Capabilities & Use Cases
The App Store Connect API, provided by Apple, serves as the definitive programmatic interface for managing the complete lifecycle of iOS, macOS, watchOS, and tvOS applications on the App Store. It replaces and expands upon the manual workflows traditionally performed through the App Store Connect web portal, enabling developers and enterprises to automate and integrate critical tasks into their CI/CD pipelines and internal tooling. Its core capabilities encompass the management of application metadata (such as descriptions, keywords, and screenshots), the handling of test builds and beta testing via TestFlight, the configuration of pricing and availability, and the monitoring of sales and financial reports. The specific endpoints in this API subset facilitate operations like updating age rating declarations to comply with global content standards, programmatically retrieving the hierarchical taxonomy of App Store categories, submitting and managing encryption declarations required for app distribution, and dynamically creating localized versions of app information. Typical use cases range from a solo developer scripting the upload and metadata update process for a new release to large enterprises synchronizing localized marketing assets across dozens of regional storefronts from a central content management system.
🤖AI Agent Value
When these App Store Connect API endpoints are exposed as tools through a Model Context Protocol (MCP) server, they transform a general-purpose AI coding assistant into a powerful, context-aware partner for mobile DevOps and release management. The AI, operating within an environment like Claude Desktop or Cursor, gains the ability to directly interact with the developer's App Store Connect account in a secure, scoped manner. This integration provides unique value by embedding deep domain knowledge of Apple's ecosystem directly into the development workflow. Instead of a developer having to look up API documentation, craft specific queries, and handle JSON responses, they can interact with the API using natural language instructions. The AI can serve as an intelligent intermediary, understanding the intent behind a command like "Check what categories are available for a new productivity app" or "Prepare the encryption documentation for the latest build," thereby reducing context-switching, minimizing manual errors, and accelerating the iteration loop between code commits and store readiness.
💬Example Workflows
This MCP server unlocks dynamic, automated workflows that can be orchestrated via simple instructions to the AI agent. A developer could instruct the agent to query all current App Store categories to analyze a competitor's positioning or to fetch subcategories to refine their own app's metadata for better discoverability. The AI could be tasked with dynamically updating the age rating declaration for a specific app version in response to new content flagged in the codebase, ensuring compliance before a build is even submitted. For international releases, a developer could command the AI to generate and post new appInfoLocalizations for a list of specified languages, pulling template strings from a local file. Furthermore, the AI agent could perform critical pre-flight checks by retrieving an encryption declaration and verifying its associated app and builds, ensuring all regulatory paperwork is in order before initiating a store submission. These examples demonstrate how the AI transitions from a code completion tool to an active participant in the operational logistics of app deployment.
🛡️Security & Auth
Secure integration is paramount when configuring the MCP server for the App Store Connect API. Although the listed authentication method is noted as "None" for the tool exposure layer, the underlying API calls to Apple's servers require robust authentication. Developers must generate and securely manage API keys or, more commonly, use JSON Web Tokens (JWT) with their App Store Connect API credentials. The principle of least privilege is critical; the API key or JWT should be created with the absolute minimum scopes required for the intended tasks—for instance, a key scoped only to read app metadata should not be granted permissions to manage builds or financial reports. Credentials must never be hardcoded or exposed in version control; they should be injected into the MCP server environment via secure secrets management tools like environment variables or a dedicated vault. The MCP server itself should be configured to run in a trusted environment, with strict access controls limiting which local machines or users can initiate commands to the AI, ensuring the automation does not become a potential vulnerability.

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