FDA Recalls Scraper

FDA Recalls Scraper

Scrape FDA recalls for food, drugs, and medical devices, filtered by classification, status, state, or date. Each recall comes with its reason, classification, recalling firm, and distribution pattern. No API key. Export to CSV, JSON, Excel, or XML.

The FDA's recall data is spread across multiple pages and formats, and the official API requires registration and rate limits. This Actor reads the public recall database directly, filtered by product type, classification, status, state, or date range, and returns each recall in one fixed schema. It covers food, drug, and medical device recalls, including Class I, II, and III.

Who uses it	What they scrape FDA Recalls for
Food safety managers	Monitor recalls for ingredients or suppliers that affect their products
Pharmacovigilance teams	Track drug recalls that may impact patient safety or inventory
Medical device manufacturers	Watch for recalls of similar devices to assess design or supplier risks
Regulatory compliance consultants	Build a searchable archive of recalls for client audits
Journalists and researchers	Analyze recall trends by product type, state, or classification over time

What it does

This Actor collects FDA recall records by product type, keyword, classification, status, state, or date range, and returns each recall as a flat row.

• 🔍 Keyword search: Search across all recall fields for terms like 'salmonella', 'peanut butter', or 'insulin'.
• 🏷️ Classification filter: Narrow to Class I (most serious), Class II, or Class III recalls.
• 📅 Date range: Limit results to recalls reported within a specific period using YYYYMMDD format.
• 📍 State filter: Focus on recalls from firms in a particular state, such as CA, TX, or NY.
• 📦 Product type: Choose food, drugs, medical devices, or all types.

Results export to CSV, JSON, Excel, or XML, or straight from the API.

What you can do with FDA Recalls data

📈 Track recall trends over time.

A food safety analyst runs the Actor weekly with productType=food and no date filter, then charts the number of Class I recalls by month to spot emerging hazards.

🔔 Monitor for specific products or ingredients.

A manufacturer sets searchQuery='peanut butter' and classification='Class I' to receive alerts whenever a serious recall involving peanut butter is posted.

🗺️ Assess regional risk.

A compliance consultant filters by state='CA' and status='Ongoing' to build a list of active recalls for California-based clients.

📊 Build a recall intelligence dashboard.

A data engineer schedules daily runs with productType='drug' and exports the results to a database to power an internal dashboard for pharmacovigilance.

Why choose this scraper

	What you get
No API key or registration	Access the public FDA recall database without signing up for an API key or dealing with rate limits.
Structured output	Every recall is returned as a flat row with consistent fields, ready for analysis or export.
Flexible filtering	Combine product type, keyword, classification, status, state, and date range to target exactly the recalls you need.
Scalable	Fetch up to 1,000,000 recalls per run for paid users, or preview with 10 items for free.

How it compares

No other Store actor targets FDA Recalls the same way, so the honest comparison is with the alternatives teams actually weigh.

	FDA Recalls Scraper	Build it in-house	By hand
Setup	Run it now, zero config	Days of engineering	None, but hours per pull
When FDA Recalls changes	Maintained for you	You fix it	You re-learn the page
Proxies, retries, anti-bot	Built in	Your problem	Browser only
Output	Fixed JSON schema, CSV/Excel export	Whatever you build	Copy-paste
Cost	Pay per result	Engineering time	Analyst hours

Configure the run

Drive the Actor with a product type, search query, classification, status, state, and date range, alone or together, and filters run as each recall is read so only matches reach your dataset. The Input tab lists every parameter.

A first run with the defaults:

{
  "productType": "all",
  "maxItems": 10
}

A larger pull:

{
  "productType": "all",
  "maxItems": 200
}

Pricing

Pay-per-result: $0.0065 per result collected. You pay only for the results written to your dataset.

Results collected	Approximate cost
100 results	$0.65
1,000 results	$6.50
10,000 results	$65.00

New Apify accounts start with $5 in free credit.

Free users

Free-plan runs return up to 10 results as a preview. Upgrade your Apify plan to collect up to 1,000,000 results per run.

Run it

1. Create a free Apify account with $5 in credit.
2. Open the FDA Recalls Scraper.
3. Set your inputs and any filters, then click Start.
4. Export the results as CSV, Excel, JSON, or XML from the Dataset tab.

Run it programmatically through the Apify API (run-sync-get-dataset-items) or the ApifyClient for JavaScript and Python.

Use with AI agents (MCP)

Give an AI agent live access to FDA Recalls through the Model Context Protocol. Add the Actor to Claude, Cursor, or any MCP client:

claude mcp add --transport http apify "https://mcp.apify.com?tools=parseforge/fda-recalls-scraper"

Then prompt it in plain language to run the scraper and read back the results.

Troubleshooting

Why am I getting no results?

Check your filters. If you set a searchQuery, classification, status, state, or date range, they may be too restrictive. Try clearing one filter at a time to see which one is excluding all recalls.

Why am I only getting 10 items?

Free users are limited to 10 items as a preview. To get more, upgrade to a paid plan and set maxItems to a higher number.

The date filter is not working as expected.

Make sure you are using YYYYMMDD format without dashes or slashes, for example '20250101'. Also check that dateFrom is not after dateTo.

I searched for a term but got unrelated recalls.

The searchQuery searches across all fields, so a term like 'apple' may match a firm name or address. Try a more specific term or combine with other filters like productType.

The run is taking too long.

If you set a very high maxItems, the Actor may take longer. Reduce maxItems or narrow your filters to speed up the run.

FAQ

Question	Answer
What is an FDA recall?	An FDA recall is an action taken by a firm to remove a product from the market or correct a violation. The FDA oversees recalls of food, drugs, medical devices, and other regulated products.
What is the difference between Class I, II, and III recalls?	Class I is the most serious, involving a reasonable probability of serious health consequences or death. Class II involves temporary or medically reversible adverse effects. Class III is unlikely to cause adverse health effects.
Does this Actor require an API key?	No. It reads the public FDA recall database directly, so no registration or API key is needed.
Can I search for a specific product or ingredient?	Yes. Use the searchQuery field to search across all recall fields, such as 'salmonella' or 'insulin'.
How do I filter by date?	Use dateFrom and dateTo in YYYYMMDD format, for example '20250101' for January 1, 2025. Both are optional.
Can I filter by state?	Yes. The state field filters by the state where the recalling firm is located, using two-letter abbreviations like 'CA' or 'TX'.
What product types are covered?	You can choose food, drugs, medical devices, or all types. The Actor returns recalls for the selected product type.
How many recalls can I get in one run?	Free users are limited to 10 items as a preview. Paid users can set maxItems up to 1,000,000.
What format is the output?	The Actor returns a flat row per recall with fields like reason, classification, recalling firm, and distribution pattern. You can export to CSV, JSON, Excel, or XML.
Is the data live?	Yes, the Actor reads the current FDA recall database at the time of the run, so you get the latest published recalls.

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Browse the full ParseForge collection for more scrapers.

🆘 Need help? Email parseforge@protonmail.com with your run ID, your input, and what you expected.

⚠️ Disclaimer. This Actor is unofficial and is not affiliated with, endorsed by, or sponsored by U.S. Food and Drug Administration. It collects only publicly available data. You are responsible for using the collected data in compliance with the source's terms of service and applicable data-protection laws, including GDPR, CCPA, and PIPL. Do not use it to collect personal data unlawfully.