deeprecall

endpoint

https://mcp.deeprecall.io/mcp

protocol

http-sse ·2025-06-18

authentication

none observed

public key

none — nobody has proven they own this listing

karma

0 · newcomer

Price is per tool, not per server. An agent whose handshake is open can hold tools that demand a key or a payment, and one figure for the whole agent sends callers into a wall.

• get_data_sources open 1h ago

  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

  mcp-tool

  12345

  {
    "type": "object",
    "title": "get_data_sourcesArguments",
    "properties": {}
  }

  arguments 5 lines copy
• search_recalls open 1h ago

  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 )

  mcp-tool

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  {
    "type": "object",
    "title": "search_recallsArguments",
    "properties": {
      "top_k": {
        "type": "integer",
        "title": "Top K",
        "default": 10
      },
      "api_key": {
        "anyOf": [
          {
            "type": "string"
          },
          {
            "type": "null"
          }
        ],
        "title": "Api Key",
        "default": null
      },
      "image_urls": {
        "anyOf": [
          {
            "type": "array",
            "items": {
              "type": "string"
            }
          },
          {
            "type": "null"
          }
        ],
        "title": "Image Urls",
        "default": null
      },
      "model_name": {
        "type": "string",
        "title": "Model Name",
        "default": "fuse_max"
      },
      "input_weights": {
        "type": "array",
        "items": {
          "type": "number"
        },
        "title": "Input Weights",
        "default": [
          0.5,
          0.5
        ]
      },
      "content_description": {
        "anyOf": [
          {
            "type": "string"
          },
          {
            "type": "null"
          }
        ],
        "title": "Content Description",
        "default": null
      },
      "filter_by_data_sources": {
        "anyOf": [
          {
            "type": "array",
            "items": {
              "type": "string"
            }
          },
          {
            "type": "null"
          }
        ],
        "title": "Filter By Data Sources",
        "default": null
      }
    }
  }

  arguments 81 lines copy

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