# FDA Recalls Scraper - Food, Drug & Device (`benthepythondev/openfda-scraper`) Actor

Scrape FDA recall / enforcement reports for food, drugs or medical devices: recall number, classification, status, product description, reason for recall, recalling firm, distribution, dates and location. Fast and reliable via the public openFDA API. For product-safety monitoring.

- **URL**: https://apify.com/benthepythondev/openfda-scraper.md
- **Developed by:** [Ben](https://apify.com/benthepythondev) (community)
- **Categories:** Business, Other, Automation
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $2.40 / 1,000 results

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/platform/actors/running/actors-in-store#pay-per-event

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
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.
Actors are written with capital "A".

## 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.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

## 💊 FDA Recalls Scraper

Scrape **FDA** recall / enforcement reports for **food, drugs or medical devices** — recall number, classification, status, product description, reason for recall, recalling firm, distribution, quantity, dates and location. Powered by the public openFDA API, so it's fast and reliable: no browser, no login, no API key.

Built for product-safety monitoring, compliance, supply-chain risk and research. Export to JSON/CSV/Excel, run on a schedule, call via API, or connect to Make, Zapier or n8n.

### 🔎 What is the FDA Recalls Scraper?

Choose a dataset (food, drug or device recalls), optionally filter by keyword or classification, and it returns matching recall reports as structured rows — so you can monitor what's being recalled and why, in real time.

#### What data does it extract?

- **Recall number**, **status** and **classification** (Class I/II/III)
- **Product description** and **reason for recall**
- **Recalling firm**, brand and manufacturer
- **Distribution pattern** and **product quantity**
- **Code info** and voluntary/mandated flag
- **Initiation / report / termination dates**
- **City, state and country**

### ⬇️ Input

| Field | Type | Description |
|-------|------|-------------|
| `dataset` | string | `food-recalls`, `drug-recalls` or `device-recalls`. |
| `search` | string | Optional keyword/firm, e.g. `salmonella`. |
| `classification` | string | Optional class, e.g. `Class I`. |
| `maxResults` | integer | Max recalls to return. Default `50`. |

#### Example input

```json
{
  "dataset": "food-recalls",
  "search": "listeria",
  "maxResults": 100
}
```

### ⬆️ Output

One record per recall:

```json
{
  "recall_number": "F-1234-2026",
  "product_type": "Food",
  "status": "Ongoing",
  "classification": "Class I",
  "product_description": "Brand X frozen vegetables, 12 oz bag",
  "reason_for_recall": "Potential Listeria monocytogenes contamination",
  "recalling_firm": "Acme Foods Inc.",
  "brand_name": "Brand X",
  "distribution_pattern": "Nationwide",
  "product_quantity": "10,500 cases",
  "voluntary_mandated": "Voluntary: Firm initiated",
  "recall_initiation_date": "20260415",
  "report_date": "20260501",
  "city": "Springfield",
  "state": "IL",
  "country": "United States",
  "query": "listeria"
}
```

### 💡 Use cases

- 🛡️ **Product-safety monitoring** — watch recalls in your category in real time.
- ✅ **Compliance** — keep a record of relevant recalls for audits.
- 🔗 **Supply-chain risk** — flag recalls from suppliers and brands you rely on.
- 🤖 **Automation** — push new recalls to Slack/email via Make/Zapier/n8n.

### ❓ FAQ

**Do I need an API key or login?** No — it uses the public openFDA API.

**Food, drugs and devices?** Yes — set `dataset`.

**Can I filter by reason or firm?** Yes — use `search`.

**What are Class I/II/III?** FDA severity classes — Class I is the most serious.

**Are dates included?** Yes — initiation, report and termination dates.

**How does pricing work?** Pay per recall returned. No subscription.

**Is it legal?** openFDA is public US government data. Use responsibly and within openFDA's terms.

### ⚙️ How it works

The scraper calls the openFDA enforcement endpoints directly and returns clean rows — no browser and no key. It paginates through results, normalizing each recall into consistent fields (classification, reason, firm, dates, location) so you get a tidy table. Runs are fast and dependable, which is why the actor keeps passing its daily health check. The same input shape works for a quick check or a full historical pull — only `maxResults` changes.

### 👥 Who uses FDA recall data?

Recall data is valuable to quality and compliance teams, retailers, importers, insurers and researchers. A grocery chain watches food recalls in its categories; a pharmacy monitors drug recalls; an importer tracks device recalls from its suppliers; a researcher studies recall trends over time. Because every record is plain JSON with consistent fields, it drops straight into a spreadsheet, database, BI tool or alerting workflow with no custom parsing.

### 📤 Export, schedule & integrate

Every run is saved to a dataset you can export to **JSON, CSV, Excel, XML or RSS**, or pull through the **Apify API**. Wire it into **Make, Zapier, n8n, Google Sheets, Slack** or your **own database**, run it on a **schedule** (hourly, daily or weekly) to catch new recalls, and call it from AI agents through the **Apify MCP server**.

### 💡 Tips for best results

- Run all three datasets to cover food, drugs and devices.
- Filter by `classification: Class I` to focus on the most serious recalls.
- Schedule a daily run and diff the output to get a recall alert feed.
- Use `search` with a supplier or brand name to monitor your supply chain.

### ❓ More FAQ

**How fresh is the data?** It is fetched live on each run — schedule runs to catch new recalls.

**Can I get more results?** Yes — raise `maxResults`; it paginates automatically.

**Can I run it automatically?** Yes — use Apify Schedules (cron).

**Which export formats?** JSON, CSV, Excel, XML and RSS, plus the Apify API.

**Can AI agents use it?** Yes — via the Apify API and MCP server.

### 🔗 You might also like

- [PubMed Papers Scraper](https://apify.com/benthepythondev/pubmed-papers-scraper) — biomedical citations.
- [SEC EDGAR Filings Scraper](https://apify.com/benthepythondev/sec-edgar-filings-scraper) — company filings.
- [Food Product Scraper](https://apify.com/benthepythondev/open-food-facts-scraper) — barcode & nutrition data.

***

**Keywords:** fda recalls scraper, openfda api, food recalls, drug recalls, device recalls, product safety, recall monitoring, fda enforcement, compliance data, supply chain risk, recall alerts, fda data, class i recall, health data

# Actor input Schema

## `dataset` (type: `string`):

Which recalls to scrape.

## `search` (type: `string`):

Keyword/firm to filter, e.g. 'salmonella', 'listeria'.

## `classification` (type: `string`):

Recall class, e.g. 'Class I', 'Class II', 'Class III'.

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

Maximum recalls to return.

## Actor input object example

```json
{
  "dataset": "food-recalls",
  "maxResults": 50
}
```

# 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 = {
    "dataset": "food-recalls"
};

// Run the Actor and wait for it to finish
const run = await client.actor("benthepythondev/openfda-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 = { "dataset": "food-recalls" }

# Run the Actor and wait for it to finish
run = client.actor("benthepythondev/openfda-scraper").call(run_input=run_input)

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

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

```

## CLI example

```bash
echo '{
  "dataset": "food-recalls"
}' |
apify call benthepythondev/openfda-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=benthepythondev/openfda-scraper",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/q5JLHSwisEqgRjBSm/builds/IqrdtAdxJQvzYeHiD/openapi.json