ReturnCheck
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@ReturnCheckCan I return this product in the US? https://store.example/p/shoe"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
ReturnCheck — Verified return-policy API for AI shopping agents
Can this specific product actually be returned? ReturnCheck answers that one question for AI shopping agents, with a verified verdict — not a guess.
Give it a product_url and a buyer_country and it returns a verdict
(YES / YES_WITH_CONDITIONS / NO / UNKNOWN) with the exact policy clause
quoted from the page, the source URL, the return window, and a confidence
score. If it cannot verify a clause on the page, it returns UNKNOWN — it
never invents.
Built for agent-to-agent commerce: an MCP tool plus x402-friendly micro-pricing at $0.02 per verified answer (UNKNOWN is free; a keyless free trial is available).
Why it exists
AI agents are starting to buy things. Before they buy, they need to know if a purchase is reversible — and today no one answers "is this returnable?" in a way a machine can trust and act on. ReturnCheck is the neutral verification primitive for that: it sells to every shopping agent and competes with none of them.
Related MCP server: Periskop MCP Server
Quick start
MCP (Streamable HTTP) — tool: check_return
https://returncheck.m-angelmartinez-fer.workers.dev/mcpHTTP
curl -X POST https://returncheck.m-angelmartinez-fer.workers.dev/v1/check \
-H "content-type: application/json" \
-d '{"product_url":"https://store.example/p/shoe","buyer_country":"US","item_condition":"unopened"}'If you already have the product/policy page rendered, pass it as page_html or
page_text — ReturnCheck verifies against it and skips fetching (best coverage,
bypasses sites that block server-side reads). It still never invents.
What you get back
{
"verdict": "YES_WITH_CONDITIONS",
"returnable": true,
"confidence": 0.9,
"policy": { "merchant_return_days": 30, "return_category": "FiniteReturnWindow" },
"evidence": {
"source_url": "https://store.example/policies/refund-policy",
"exact_clause": "Items may be returned within 30 days of delivery for a full refund.",
"verified_on": "2026-08-23"
}
}Pricing
Verified answer (YES / NO / conditions) | $0.02 |
UNKNOWN | Free |
Keyless free trial | a few calls/day, no signup |
Discovery for agents
OpenAPI:
/openapi.jsonPlugin manifest:
/.well-known/ai-plugin.jsonAgents manifest:
/agents.jsonLLM manifest:
/llms.txtMCP tool list:
/mcp
Design principles
Never invent. Every determinate verdict carries a clause verified literally against the page. If it can't be verified, the answer is
UNKNOWN.Frozen contract (v1.0). Fields are only ever added, never broken.
US data first, global architecture. Runs 100% serverless on the edge (Cloudflare Workers + D1 + Workers AI).
Keywords
return policy API · returns verification · AI shopping agents · agentic commerce · MCP server · check_return · x402 · agent-to-agent payments · e-commerce returns · is this returnable · refund policy checker
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AlicenseNot gradedqualityCmaintenanceEnables AI agents to perform product discovery from natural language shopping intents, returning ranked products with merchant links without completing checkout.MIT- FlicenseNot gradedqualityCmaintenanceEnables AI agents to independently investigate and resolve e-commerce order issues, particularly refund processing, with tools for order search, refund eligibility checks, and safe refund execution.
- FlicenseAqualityCmaintenanceEnables AI shopping agents to verify a storefront's legitimacy before committing payment by checking domain registration, SSL certificate history, HTTPS validity, and known-scam blocklists, returning a trust score with explainable reasons and a clear recommendation.1
Related MCP Connectors
Fail-closed refund, cancellation, return, and trial checks for 100 US subscription vendors.
Merchant verification for AI shopping agents.
Policy review and purchase discovery for AI-agent commerce actions.
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