# Return or Repair Path Logic Engine. AI Agent Connect > Return or Repair Path Logic Engine analyzes purchase data and warranty terms to determine if a consumer can successfully claim a refund, repair, or replacement. It checks legal windows, verifies evidence strength, and confirms deadline compliance to build a step-by-step guide for resolving product issues. ## Overview - **Category:** decision-support - **Price:** Free - **Endpoint:** https://edge.vinkius.com/vk_preview_0s6eN43VpK1RS2khNIrzc0kL6JxTivvhLIs8Fn7G/ai-agent-connect - **Tags:** warranty, returns, consumer-protection, logic, claims-management ## Description You can use this MCP to automate the heavy lifting involved in consumer protection and warranty claims. Instead of manually cross-referencing purchase dates against complex warranty fine print, you give your AI client the raw data and let it run the logic. It evaluates whether a user is still within their rights to seek a remedy and if their evidence is strong enough to hold up against a manufacturer's scrutiny. Once the analysis is done, your agent produces a specific, actionable plan. This removes the guesswork from deciding whether to pursue a refund, a repair, or a total replacement. It's a decision-support tool designed to turn raw purchase history and defect reports into a tactical path forward. ## Tools ### analyze_eligibility This tool checks if a consumer is still within the legal or contractual windows required to seek a remedy. ### check_deadline_compliance It verifies that no critical intermediate deadlines have been missed during the claim process. ### evaluate_defect_validity This tool assesses if the provided evidence is sufficient to trigger a valid remedy. ### generate_resolution_path It synthesizes all previous analysis into a clear, step-by-step instructional roadmap. ## Prompt Examples **Prompt:** ``` I bought a laptop 10 days ago, the return window is 30 days, the warranty is 365 days, it is currently 2024-01-15, I have a photo of a broken screen (strength 90/100), the threshold is 70, and I discovered the defect today. I want a refund. ``` **Response:** ``` 1. Return to Vendor. 2. Present photographic evidence of the broken screen. 3. Complete the refund process at the point of purchase. ``` **Prompt:** ``` My phone warranty is valid for 730 days. I bought it 400 days ago. The warranty is still active. I have a technical report (strength 85/100) and the threshold is 80. I discovered the issue 2 days ago and am reporting it today. The deadline is 5 days. I want a repair. ``` **Response:** ``` 1. Manufacturer Service Request. 2. Submit the technical report to the service center. 3. Await repair confirmation. ``` **Prompt:** ``` I bought a camera 400 days ago. The return window was 30 days and the warranty was 365 days. I want a refund. ``` **Response:** ``` Claim Denied. The product is outside both the return window and the warranty period. ``` ## Capabilities ### Eligibility Verification Your agent uses this to confirm if a claim falls within valid contractual windows. ### Evidence Assessment The AI evaluates the strength of provided proof against required thresholds. ### Deadline Tracking It checks for missed reporting timelines or intermediate deadlines. ### Roadmap Generation Your client produces a specific sequence of steps to achieve a refund or repair. ## Use Cases ### Warranty Claim Validation Verify if a customer's device is still covered before initiating a service request. ### Return Policy Auditing Check if a product return request meets the specific terms set by a vendor. ### Evidence Review Determine if a photo or technical report meets the necessary threshold for a remedy. ### Dispute Resolution Create a step-by-step guide for users to follow when seeking a refund for a defective item. ## Benefits - Reduces manual calculation of warranty and return windows. - Standardizes the evaluation of evidence strength. - Provides a consistent logic for claim approval or denial. - Generates actionable instructions instead of just raw data. ## How It Works Connecting this MCP to your AI client gives you immediate access to a specialized logic engine. 1. Connect your MCP-compatible client to Vinkius. 2. Provide your agent with purchase dates, warranty terms, and evidence details. 3. The MCP runs the logic through eligibility, compliance, and validity checks. 4. Your agent receives a structured resolution roadmap. ## Frequently Asked Questions **What can this MCP do with my consumer data?** It analyzes purchase dates, warranty windows, and evidence strength to determine if a claim is valid and how to proceed. **Which AI clients can use this MCP?** You can use this with any MCP-compatible client, including Claude, Cursor, Windsurf, and VS Code. **Does it provide a way to get a refund?** It doesn't process the refund itself, but it generates the specific roadmap of steps you need to take to achieve a refund. **Can it handle technical reports as evidence?** Yes, it can evaluate the strength of technical reports against a set threshold to see if they trigger a remedy. **How does it handle denied claims?** If the data shows the product is outside the return or warranty window, the tool will output a denial based on that logic. **How does the engine determine if I can return my product?** The engine uses the `analyze_eligibility` tool to compare your purchase date against the allowed return window days to see if you are still eligible for a refund. **What happens if my evidence is not strong enough?** If `evaluate_defect_validity` determines the evidence strength is below the required threshold, the generated resolution path will include steps for providing additional proof. **Can this tool help with warranty claims?** Yes. By using `analyze_eligibility` and `generate_resolution_path`, the engine can identify if a product is within its warranty period and provide a path for manufacturer service requests.