Compatible with every major AI agent and IDE
Get app info on AppGallery Connect
The appId can be found via list_apps. Get detailed information for a specific application
Get app language info on AppGallery Connect
g. "en-US", "zh-CN", "pt-BR"). Get localized app information for a specific language
Get comments on AppGallery Connect
Get user comments and reviews for an application
Get download stats on AppGallery Connect
Dates must be in YYYYMMDD format. Get download statistics for an application
Get install stats on AppGallery Connect
Dates must be in YYYYMMDD format. Get installation statistics for an application
Get rating info on AppGallery Connect
Get rating and review summary for an application
Get submission status on AppGallery Connect
Check the review status of a submitted application
Get upload url on AppGallery Connect
Specify the file suffix (e.g. "apk", "png"). Get a pre-signed upload URL for app binaries or assets
List apps on AppGallery Connect
List all applications in the AppGallery Connect account
Reply to comment on AppGallery Connect
Use get_comments to find comment IDs. Reply to a user comment on the AppGallery
Submit for review on AppGallery Connect
The app must have all required metadata and at least one valid binary uploaded. Submit an application for review and publication
How Vinkius protects your data
Is there a risk of the AI "going crazy" and deleting important company data?
No. With Vinkius, the AI operates on "rails". It can only make the exact moves you authorized in the tool's settings. It cannot invent routes, access other networks in your company, or decide to delete random files. If the action isn't in the approved catalog, the attempt is blocked instantly.
Can I submit an app build for review?
Yes! Use get_upload_url to get a pre-signed upload URL, then submit_for_review to push the build through the moderation pipeline. You can track progress with get_submission_status.
What if the AI ends up reading customer data or confidential information?
We have a built-in digital "bodyguard" called DLP (Data Loss Prevention). If a tool fetches data and the response contains social security numbers, credit cards, or personal customer info, Vinkius magically blocks and erases that information before it is delivered to the AI. The AI works only with what is strictly necessary, and your sensitive data never leaks.
Does the AI train on my tools or API data?
No. Vinkius enforces a strict Zero-Retention policy. Your data simply passes through our secure servers to complete the requested action and is instantly forgotten. Nothing you do here is ever stored, logged, or used to train any artificial intelligence.
Supported Use Cases for AppGallery Connect
The AppGallery Connect integration provides comprehensive execution endpoints, allowing AI models to orchestrate tasks reliably.
Prompting app store Workflows
The AppGallery Connect MCP integration translates natural language prompts into structured app store queries. This allows agents to fetch and update developer tools records securely.
Streamlining mobile apps
The AppGallery Connect toolkit provides AI native integration for mobile apps. It structures data so Claude Code can accurately process developer tools requirements.
AppGallery Connect. Runs on everything.
From IDE to framework. Every connection governed by Vinkius.
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
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