Compatible with every major AI agent and IDE
Get account on Junip
Use to verify account identity and access levels. Retrieves details about your Junip account
Get product on Junip
Essential for providing a summary of a product's performance within the store. Retrieves details for a specific product
Get question on Junip
Use this before crafting an official response. Retrieves details for a specific question
Get review on Junip
Returns metadata, custom question responses, and photo/video links (if applicable). Use this when analyzing a specific customer testimonial. Retrieves details for a specific review
List answers on Junip
Use this to audit response quality and ensure all customer queries are being addressed correctly. Lists all answers to questions
List campaigns on Junip
Use this to analyze active efforts to collect new customer reviews and feedback. Lists active review request campaigns
List products on Junip
Includes product names, IDs, and aggregate review metrics. Use this to identify which items have reviews. Lists all products in your store
List questions on Junip
Returns question text, status, and associated products. Use this to find customer inquiries that require a merchant response. Lists all customer questions
List reviews on Junip
Returns ratings, review content, and reviewer names. Use this to monitor brand sentiment and identify high-quality social proof. Lists all product reviews
List themes on Junip
Useful for auditing the visual presentation of reviews on the storefront. Lists all review display themes
How Vinkius protects your data
How do I get Junip API credentials?
Log in to your Junip admin dashboard, navigate to Settings > API, and generate a new Access Token for a Private App.
Can I audit what my AI agents are doing with this integration?
Yes, Vinkius provides an immutable, HMAC-chained audit log. Every tool execution, payload, and response is tracked in real-time on your dashboard, giving you complete visibility into your agent's actions.
What happens if the underlying API rate limits my agent?
Our edge infrastructure automatically handles backoffs, queueing, and throttling. If an AI agent sends too many erratic requests, Vinkius manages the rate limits gracefully, ensuring your backend doesn't crash.
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.
What can AI Agents do with Junip?
Enable conversational interfaces like ChatGPT and Claude to execute programmatic commands against the Junip infrastructure.
Automating product reviews with AI
Use Junip to manage product reviews via conversational interfaces. The integration centralizes access control for ecommerce operations performed by ChatGPT.
ChatGPT customer feedback Automation
Integrate customer feedback features into your LLM framework using Junip. The MCP server ensures precise command execution across your ecommerce stack.
Junip. 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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