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DeepRecall - Product Safety Intelligence

by io.github.adrida
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Server Details

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

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Status
Healthy
Uptime
100.0% over the last 24 hours
Last Tested
Transport
Streamable HTTP · MCP 2025-11-25
URL
Repository
DeepRecall-io/deeprecall-mcp
GitHub Stars
0
Server Listing
deeprecall-mcp
ChatGPT
–
Claude
–

TDQS

A4.4/5.0

Scored across 2 tools

Disambiguation5/5

get_data_sources provides metadata about available regulatory agencies, while search_recalls performs the actual product recall search. These are clearly distinct purposes with no functional overlap, making tool selection unambiguous.

Naming Consistency5/5

Both tools follow a consistent verb_noun pattern with snake_case (get_data_sources, search_recalls). The naming is predictable and matches the server's search-oriented purpose.

Tool Count3/5

With only two tools, the server feels minimal. However, for a specialized search service, a metadata tool and a search tool may be sufficient. Still, the count is on the thin side, potentially limiting discoverability of other useful capabilities.

Completeness4/5

The core workflow of discovering available data sources and searching for recalls is covered. A minor gap is the lack of a dedicated tool to retrieve detailed information for a specific recall ID, but the search results include sufficient product details, so agents can work around this.

Available Tools

2 tools
get_data_sourcesAInspect
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

Inputs: no named parameters.

search_recallsAInspect
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
    )

Inputs: top_k, api_key, image_urls, model_name, +3 more.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

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