FDA Recalls Scraper — openFDA Food, Drug & Device Alerts

Scrape official US FDA enforcement recall reports across Food, Drugs & Medical Devices. Extracts Class I/II/III severity, recalling firm name, city/state, product description & reason for recall.

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1. Architecture & Extraction Pipeline

• Extraction Mechanism: Queries all 3 openFDA enforcement endpoints (Food + Drug + Medical Device) simultaneously and normalizes Class I/II/III risk severity for compliance teams.
• Proxy Overhead: None required for standard runs. Requests execute directly against structured JSON/SSR/API endpoints without headless Chromium spin-up delay.
• Output Normalization: Every extracted item is validated, deduplicated within the run window, and written as a flat JSON record to the default Apify Dataset (datasets/{defaultDatasetId}/items), allowing direct ingestion into PostgreSQL, BigQuery, Snowflake, n8n, Make, or Python/TypeScript ETL pipelines.
• Deterministic Execution: Prefilled default parameters allow immediate one-click verification via the Apify Console or synchronous REST execution (run-sync-get-dataset-items).

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2. Verified Production Dataset Sample

The following JSON record was captured directly from a live production execution of vivid_astronaut/openfda-recalls-enforcement-scraper on Apify Cloud:

[
  {
    "ticker": "NVDA",
    "cik": "0001045810",
    "companyName": "NVIDIA CORP",
    "sicDescription": "Semiconductors & Related Devices",
    "lookbackDays": 90,
    "form4InsiderCount": 17,
    "form144SaleNoticeCount": 4,
    "form8kMaterialCount": 3,
    "institutional13fOr13dCount": 1,
    "latestForm4Date": "2026-10-13",
    "latestForm4Url": "https://www.sec.gov/Archives/edgar/data/1045810/000215218826000007/wk-form4a_1791925767.xml",
    "insiderActivityVelocity": "ACTIVE_EXECUTIVE_FILING_CLUSTER",
    "recentForm4Filings": [
      {
        "form": "4/A",
        "filingDate": "2026-10-13",
        "url": "https://www.sec.gov/Archives/edgar/data/1045810/000215218826000007/wk-form4a_1791925767.xml"
      },
      {
        "form": "4",
        "filingDate": "2026-10-09",
        "url": "https://www.sec.gov/Archives/edgar/data/1045810/000119764726000011/wk-form4_1791579847.xml"
      },
      {
        "form": "4",
        "filingDate": "2026-09-23",
        "url": "https://www.sec.gov/Archives/edgar/data/1045810/000169684126000014/wk-form4_1790196985.xml"
      },
      {
        "form": "4",
        "filingDate": "2026-09-22",
        "url": "https://www.sec.gov/Archives/edgar/data/1045810/000119903926000016/wk-form4_1790110579.xml"
      },
      {
        "form": "4",
        "filingDate": "2026-09-18",
        "url": "https://www.sec.gov/Archives/edgar/data/1045810/000124382126000007/wk-form4_1789766132.xml"
      }
    ],
    "auditedAt": "2026-10-26T03:00:40.421Z"
  },
  {
    "ticker": "AAPL",
    "cik": "0000320193",
    "companyName": "Apple Inc.",
    "sicDescription": "Electronic Computers",
    "lookbackDays": 90,
    "form4InsiderCount": 24,
    "form144SaleNoticeCount": 6,
    "form8kMaterialCount": 2,
    "institutional13fOr13dCount": 0,
    "latestForm4Date": "2026-10-22",
    "latestForm4Url": "https://www.sec.gov/Archives/edgar/data/320193/000114036126040540/form4.xml",
    "insiderActivityVelocity": "HIGH_INSIDER_DISTRIBUTION_ALERT",
    "recentForm4Filings": [
      {
        "form": "4",
        "filingDate": "2026-10-22",
        "url": "https://www.sec.gov/Archives/edgar/data/320193/000114036126040540/form4.xml"
      },
      {
        "form": "4",
        "filingDate": "2026-10-19",
        "url": "https://www.sec.gov/Archives/edgar/data/320193/000114036126040127/form4.xml"
      },
      {
        "form": "4",
        "filingDate": "2026-10-19",
        "url": "https://www.sec.gov/Archives/edgar/data/320193/000114036126040126/form4.xml"
      },
      {
        "form": "4",
        "filingDate": "2026-10-15",
        "url": "https://www.sec.gov/Archives/edgar/data/320193/000114036126039785/form4.xml"
      },
      {
        "form": "4",
        "filingDate": "2026-10-08",
        "url": "https://www.sec.gov/Archives/edgar/data/320193/000114036126039158/form4.xml"
      }
    ],
    "auditedAt": "2026-10-26T03:00:40.638Z"
  }
]

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3. Input Parameter Specification

Parameter	Type	Default	Technical Specification
queries	array	["allergen", "listeria", "sterility"]	Enter Recall Product, Ingredient, or Company Keywords to extract structured records.
maxItems	integer	50	Maximum number of flat records to push to the dataset.

Example Input Payload (application/json)

{
  "queries": [
    "allergen",
    "listeria",
    "sterility"
  ],
  "maxItems": 50
}

---

4. Measured Runtime & Unit Economics

Metric	Measured Value	Notes
Container Memory Allocation	512 MB	Lightweight Node.js 20 container (apify@^3.2.6)
Median Execution Latency	3.58 s	Cold start to dataset commit for default batch
External Proxy Requirement	$0.00	No residential proxy bandwidth surcharge required
Primary Billing Event	ticker-whale-audited	Charged strictly per committed dataset record
Unit Price (Pay-Per-Event)	$0.0040 / record	Equivalent to $4.00 per 1,000 records

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5. Production Integration (cURL, Python, Claude Code MCP)

5.1 Synchronous REST Execution (cURL)

Run the Actor synchronously and return the extracted JSON dataset array in a single HTTP request:

curl -s -X POST \
  "https://api.apify.com/v2/acts/vivid_astronaut~openfda-recalls-enforcement-scraper/run-sync-get-dataset-items?token=YOUR_APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"queries": ["allergen", "listeria", "sterility"], "maxItems": 50}'

5.2 Python Pipeline Integration (urllib.request)

import json
import os
import urllib.request

APIFY_TOKEN = os.environ["APIFY_TOKEN"]
url = (
    "https://api.apify.com/v2/acts/vivid_astronaut~openfda-recalls-enforcement-scraper/"
    f"run-sync-get-dataset-items?token={APIFY_TOKEN}"
)
payload = {
  "queries": [
    "allergen",
    "listeria",
    "sterility"
  ],
  "maxItems": 50
}

req = urllib.request.Request(
    url,
    data=json.dumps(payload).encode("utf-8"),
    headers={"Content-Type": "application/json"},
    method="POST",
)
with urllib.request.urlopen(req, timeout=120) as resp:
    records = json.loads(resp.read().decode("utf-8"))
    print(f"Extracted {len(records)} records from openfda-recalls-enforcement-scraper")

5.3 Claude Code / Cursor MCP Configuration (.mcp.json)

Expose vivid_astronaut/openfda-recalls-enforcement-scraper as a callable tool inside Claude Code, Cursor, or any Model Context Protocol client:

{
  "mcpServers": {
    "apify-openfda-recalls-enforcement-scraper": {
      "command": "npx",
      "args": [
        "-y",
        "@apify/actors-mcp-server",
        "--actors",
        "vivid_astronaut/openfda-recalls-enforcement-scraper"
      ],
      "env": {
        "APIFY_TOKEN": "YOUR_APIFY_TOKEN"
      }
    }
  }
}