
DeepRecall Product Safety Intelligence
Check whether products you sell or source appear on global recall lists before launch and during ongoing catalog reviews.
Overview
io.github.adrida/deeprecall-mcp is a MCP server for the Ship phase that lets agents search 120,000+ recalled products from 8 global agencies using AI similarity.
What is this MCP server?
- Search 120,000+ recalled products indexed from 8 global safety agencies
- AI similarity matching beyond exact SKU lookup
- Remote streamable HTTP at mcp.deeprecall.io with X-API-Key (dr_live_ keys)
- Product safety intelligence for ecommerce and hardware solo sellers
- 120,000+ recalled products in index
- 8 global safety agencies as data sources
- MCP server version 1.0.0
What problem does it solve?
Indie sellers cannot manually scan eight agency recall feeds every time they add or ship a product.
Who is it for?
Ecommerce founders, Amazon or Shopify operators, and hardware indie builders who need fast recall due diligence.
Skip if: Pure software SaaS with no physical product risk, or teams unwilling to use a paid DeepRecall API key.
What do I get? / Deliverables
Agents return recall hits and similarity matches so you can block risky SKUs before customers receive them.
- Recall search results with agency-sourced matches
- Agent-ready safety intelligence for catalog decisions
Recommended MCP Servers
Journey fit
How it compares
Recall-compliance MCP, not a general web scraper or penetration-testing exploit framework.
Common Questions / FAQ
Who is io.github.adrida/deeprecall-mcp for?
Solo builders and small teams selling or sourcing physical products who want agent-driven recall checks against global agency data.
When should I use io.github.adrida/deeprecall-mcp?
Use it before launch, when onboarding suppliers, or whenever you refresh catalog SKUs and need similarity-aware recall search.
How do I add io.github.adrida/deeprecall-mcp to my agent?
Register https://mcp.deeprecall.io/mcp as streamable-http MCP and set header X-API-Key to your dr_live_ DeepRecall API key.