# FDA Food Recalls & Safety Alerts Scraper (`litezero/fda-food-recalls-scraper`) Actor

Extract official FDA food recalls, product contamination alerts, allergen mislabeling, recalling firms, distribution patterns, and enforcement classifications.

- **URL**: https://apify.com/litezero/fda-food-recalls-scraper.md
- **Developed by:** [LiteZero](https://apify.com/litezero) (community)
- **Categories:** Developer tools, AI, Automation
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $1.05 / 1,000 item scrapeds

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## 🥗 FDA Food Recalls & Safety Alerts Scraper

Extract official **FDA Food Enforcement Reports**, product safety recalls, bacterial contamination alerts (Salmonella, Listeria, E. coli), undeclared allergen notices, and recalling firm details in bulk.

Engineered for grocery chains, food brand compliance officers, supply chain risk analysts, restaurant franchises, and consumer safety watchdogs.

***

### 🥊 Why This Actor Beats the Competition

| Feature | 🥗 This Actor (`litezero`) | 🐢 FDA Enforcement Web Search | 🔒 Commercial Food Safety SaaS |
|---|---|---|---|
| **Speed** | ⚡ **< 1.0 second / query** | 🐌 Clunky slow government portal | ⏳ Heavy enterprise setup |
| **Pricing** | 💰 **$1.50 / 1,000 recalls** (Free Platform Usage) | 💸 Manual regulatory review ($$$) | 💳 $400–$1,500 / month |
| **Data Completeness** | 📦 Full reason, firm, classification, distribution | ⚠️ Truncated tables & PDF downloads | 🔒 Proprietary data format |
| **Automation** | 🤖 REST API, Python, Node.js, Webhooks | ❌ Zero API / manual search only | 🛠️ Multi-month vendor onboarding |
| **Classification** | 🏷️ Official Class I, II, III Hazard Levels | 🧩 Unstructured government text | 🔒 Paywalled behind enterprise tiers |

***

### 🛠️ Step-by-Step: How to Use

#### Method 1: Apify Web Console (No-Code)

1. Enter your search term (e.g. `salmonella`, `listeria`, `undeclared peanut`, `cheese`, `lettuce`).
2. Optional: Filter by recall status (`Ongoing`, `Completed`, `Terminated`, or `All`).
3. Click **Start** and export results to JSON, CSV, or Excel.

#### Method 2: Python SDK

```python
from apify_client import ApifyClient

client = ApifyClient("YOUR_APIFY_TOKEN")
run_input = {
    "searchQuery": "listeria",
    "status": "Ongoing",
    "maxResults": 20
}

run = client.actor("litezero/fda-food-recalls-scraper").call(run_input=run_input)
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(f"[{item['classification']}] {item['recalling_firm']}: {item['reason_for_recall'][:80]}")
```

#### Method 3: Node.js SDK

```javascript
import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: 'YOUR_APIFY_TOKEN' });
const run = await client.actor('litezero/fda-food-recalls-scraper').call({
    searchQuery: 'salmonella',
    maxResults: 15
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(`Retrieved ${items.length} food recall enforcement records.`);
```

#### Method 4: REST API / cURL

```bash
curl "https://api.apify.com/v2/acts/litezero~fda-food-recalls-scraper/runs?token=YOUR_APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"searchQuery": "undeclared allergen", "maxResults": 10}'
```

***

### 📥 Input Parameters

| Parameter | Type | Required | Default | Description |
|---|:---:|:---:|:---:|---|
| `searchQuery` | `string` | **Yes** | `"salmonella"` | Contaminant or food keyword (e.g., `listeria`, `peanut`, `dairy`). |
| `status` | `string` | No | `"all"` | Filter by status: `all`, `Ongoing`, `Completed`, `Terminated`. |
| `maxResults` | `integer`| No | `20` | Max recall records to return (1–100). |

***

### 📤 Output Data Dictionary & Sample JSON

```json
{
  "recall_number": "F-0428-2024",
  "reason_for_recall": "Potential contamination with Salmonella species.",
  "status": "Ongoing",
  "classification": "Class I",
  "recalling_firm": "Fresh Farms Packaging Co.",
  "product_description": "Organic Baby Spinach, 16 oz plastic clamshell container.",
  "product_type": "Food",
  "distribution_pattern": "Distributed in CA, OR, WA, and NV to retail grocery stores.",
  "code_info": "Lot #24810, Best by OCT 12 2026",
  "product_quantity": "4,200 cases",
  "report_date": "2026-09-24",
  "recall_initiation_date": "2026-09-18",
  "voluntary_mandated": "Voluntary: Firm Initiated",
  "city": "Salinas",
  "state": "CA",
  "country": "United States",
  "scraped_at": "2026-10-04T06:30:00.000Z"
}
```

***

### 💡 Top Commercial Use Cases

1. **Supply Chain & Grocery Risk Management:** Automatically cross-reference vendor inventory against FDA Class I recalls to pull contaminated stock before reaching consumer shelves.
2. **Restaurant Franchise Compliance:** Monitor real-time recall alerts affecting commercial produce, meat, poultry, and dairy distributors.
3. **Food Safety News & Consumer Alert Feeds:** Power consumer recall alert notification bots on Slack, SMS, or Telegram.

# Actor input Schema

## `searchQuery` (type: `string`):

Keywords or contaminant to search (e.g., 'salmonella', 'listeria', 'peanut', 'undeclared').

## `status` (type: `string`):

Filter by recall status.

## `maxResults` (type: `integer`):

Maximum number of recall records to retrieve (1 to 100).

## Actor input object example

```json
{
  "searchQuery": "salmonella",
  "status": "all",
  "maxResults": 20
}
```

# Actor output Schema

## `results` (type: `string`):

No description

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "searchQuery": "salmonella",
    "status": "all",
    "maxResults": 20
};

// Run the Actor and wait for it to finish
const run = await client.actor("litezero/fda-food-recalls-scraper").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {
    "searchQuery": "salmonella",
    "status": "all",
    "maxResults": 20,
}

# Run the Actor and wait for it to finish
run = client.actor("litezero/fda-food-recalls-scraper").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "searchQuery": "salmonella",
  "status": "all",
  "maxResults": 20
}' |
apify call litezero/fda-food-recalls-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,litezero/fda-food-recalls-scraper"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/piyKlCnj9Ys6feUDz/builds/YNjS0jdKnp06fUGsg/openapi.json