mcpbeat

DeepRecall - Product Safety Intelligence MCP Server

io.github.adrida/deeprecall-mcp
answering

DeepRecall - Product Safety Intelligence is answering right now. Last checked 8 min ago. It exposes 2 tools.

Search 120,000+ recalled products from 8 global safety agencies using AI similarity.

The linked repository no longer exists on GitHub — it was deleted or made private.

Uptime history 41 hours of history
41 hours agonow
100.0%
Uptime 24h
91 of 91 checks
2
Tools
read from the server
372 ms
Response time
average over 24h
open, no key
Access
streamable-http

Connect this server

Endpoint below is the one we actually reach during checks — not the one copied from a README. Last verified 8 min ago.

run in your terminal
claude mcp add deeprecall-mcp --transport http https://mcp.deeprecall.io/mcp
~/Library/Application Support/Claude/claude_desktop_config.json
{
  "mcpServers": {
    "deeprecall-mcp": {
      "url": "https://mcp.deeprecall.io/mcp"
    }
  }
}
~/.codex/config.toml
[mcp_servers.deeprecall-mcp]
url = "https://mcp.deeprecall.io/mcp"
.cursor/mcp.json
{
  "mcpServers": {
    "deeprecall-mcp": {
      "url": "https://mcp.deeprecall.io/mcp"
    }
  }
}
.vscode/mcp.json
{
  "mcpServers": {
    "deeprecall-mcp": {
      "url": "https://mcp.deeprecall.io/mcp"
    }
  }
}

Available tools 2

Read directly from the server with tools/list, grouped by what they act on. If a tool disappears, we record the date.

data
get_data_sources
Get information about available recall data sources. Returns a list of all supported regulatory agencies and their coverage. This is a free call that does not consume API credits. Returns: Dictionary with data sources and their descriptions
recalls
search_recalls
Search for recalled products similar to your query. This tool searches DeepRecall's global product safety database using AI-powered multimodal matching. Provide a text description and/or product images to find similar recalled products. Use Cases: - Pre-purchase safety checks: Before buying, verify if similar products were recalled - Supplier vetting: Check if a supplier's products have safety issues - Marketplace compliance: Verify products against recall databases - Consumer protection: Identify potentially hazardous products Data Sources: - us_cpsc: US Consumer Product Safety Commission - us_fda: US Food and Drug Administration - safety_gate: EU Safety Gate (Europe) - uk_opss: UK Office for Product Safety & Standards - canada_recalls: Health Canada Recalls - oecd: OECD GlobalRecalls portal - rappel_conso: French Consumer Recalls - accc_recalls: Australian Competition and Consumer Commission Cost: 1 API credit per search Args: content_description: Text description of the product (e.g., "children's toy with small parts") image_urls: List of product image URLs for visual matching (1-10 images) filter_by_data_sources: Limit search to specific agencies (optional) top_k: Number of results (1-100, default: 10) model_name: Fusion model - fuse_max (recommended), fuse_flex, or fuse input_weights: Weights for [text, images], must sum to 1.0 api_key: Your DeepRecall API key (optional if provided via X-API-Key header) Returns: Search results with matched recalls, scores, and product details Example: search_recalls( content_description="baby crib with drop-side rails", top_k=5 )

Endpoints

URLTransportStateLatencyChecked
https://mcp.deeprecall.io/mcp streamable-http answering 308 ms 8 min ago

DeepRecall - Product Safety Intelligence — questions

Answers built from our own checks of this server.

What can DeepRecall - Product Safety Intelligence do?
It exposes 2 tools, read directly from the server on our last check. Among them: get_data_sources, search_recalls. The full list with descriptions is on this page — we take it from the server itself via tools/list, not from a README. How MCP servers expose tools in the first place →
Is DeepRecall - Product Safety Intelligence working right now?
We send a real MCP handshake every 15 minutes. Over the last 24 hours 91 of 91 checks got a reply (100.0%), average response time 372 ms. The bar chart above shows every period we have measured.
Is DeepRecall - Product Safety Intelligence still maintained?
The linked repository no longer exists on GitHub — it was deleted or made private. We show this because it changes what you can expect: an unmaintained server may keep answering for months and then stop without warning.
How do I connect DeepRecall - Product Safety Intelligence?
Copy the ready config from this page — we generate it for Claude Code, Claude Desktop, Codex, Cursor and VS Code, each with the file path that client actually reads. It is a remote server, so there is nothing to install — the client connects to the address.
Does DeepRecall - Product Safety Intelligence need an API key?
No. DeepRecall - Product Safety Intelligence completed a full MCP handshake with us as an anonymous client and listed its tools without asking for anything. All 2 of them are readable on this page. This is what we observed, not what the docs claim.
How fast is DeepRecall - Product Safety Intelligence?
It answers our handshake in 372 ms on average, which is faster than 37% of all working MCP servers we measure. The comparison comes from our own checks across the whole registry, every 15 minutes.