NHTSA Vehicle Recalls & Complaints Scraper

NHTSA Vehicle Recalls & Complaints Scraper

Scrape vehicle safety recalls and consumer complaints from the NHTSA database, filtered by make, model, and year. Get official defect descriptions, remedy information, affected units, and complaint narratives. Export structured data to CSV, JSON, Excel, or XML.

The NHTSA recall and complaint database is the authoritative source for U.S. vehicle safety defects, but manually searching it across multiple makes and models is slow and repetitive. This actor reads the public NHTSA feeds directly, letting you pull up to a million recall records or consumer complaints in a single run. Filter by manufacturer, model, and model year so only the vehicles you care about land in your dataset.

Who uses it	What they scrape NHTSA for
Automotive journalists	Researching defect trends and recall histories for specific vehicle models.
Fleet managers	Monitoring active recalls across their vehicle inventory to schedule repairs.
Used car dealers	Checking a vehicle's recall and complaint history before listing it for sale.
Safety researchers	Aggregating complaint narratives to identify emerging defect patterns.
Legal professionals	Gathering evidence of known defects for lemon law and product liability cases.

What it does

This Actor collects NHTSA vehicle recall records or safety complaints by make, model, and model year, and returns each one as a structured flat row.

• 🚗 Dual mode: switch between recall records and consumer complaint data in one actor.
• 🔍 Vehicle filters: narrow results by make, model, and model year before the run starts.
• 📦 Bulk collection: pull up to one million records per run for large-scale analysis.
• 📄 Structured output: every row follows a fixed schema ready for spreadsheets and databases.

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

What you can do with NHTSA data

📋 Audit a used car lot.

A dealer runs the actor for every VIN-implied make, model, and year on the lot, then cross-references open recalls to decide which cars need service before sale.

📰 Build a recall watchlist.

An automotive reporter pulls all recalls for a set of popular models each month and publishes a roundup of the most serious defects.

⚖️ Support a lemon law case.

A lawyer collects every complaint and recall for a client's vehicle to establish a documented pattern of the same defect.

🚛 Keep a fleet compliant.

A logistics company scrapes recalls for their truck makes and models weekly, flagging any new safety campaign that requires immediate grounding.

📊 Analyze defect trends.

A researcher aggregates five years of recall data across all manufacturers to study which component categories fail most often.

Why choose this scraper

	What you get
Official NHTSA data	Recall numbers, defect summaries, remedy descriptions, and affected unit counts straight from the regulator.
No API key required	Reads the public NHTSA feeds without registration, OAuth, or rate-limit headaches.
Flexible filtering	Target one specific model or pull every recall for an entire manufacturer across all years.
Complaint narratives	When you choose complaints mode, get the full consumer-reported problem description for each case.

How it compares

This actor focuses on high-volume recall and complaint collection with simple make-model-year filtering, while the listed competitors add VIN decoding, crash ratings, or multi-agency product safety signals.

Feature	ParseForge	NHTSA Vehicle Intelligence	NHTSA Vehicle Complaints Scraper
Recall data by make, model, year	Yes	Yes	Not listed
Consumer complaint data	Yes	Yes	Yes
VIN decoding	Not listed	Yes	Not listed
NCAP crash test ratings	Not listed	Yes	Not listed
Up to 1M records per run	Yes	Not listed	Not listed
No API key required	Yes	Not listed	Not listed

Configure the run

Drive the Actor by selecting recalls or complaints mode, then optionally filter by vehicle make, model, and model year so only matching records are collected. The Input tab lists every parameter.

A first run with the defaults:

{
  "mode": "recalls",
  "maxItems": 10,
  "make": "Toyota",
  "model": "Camry",
  "modelYear": 2020
}

A larger pull:

{
  "mode": "recalls",
  "maxItems": 200,
  "make": "Toyota",
  "model": "Camry",
  "modelYear": 2020
}

Pricing

Pay-per-result: $0.0055 per result collected. You pay only for the results written to your dataset.

Results collected	Approximate cost
100 results	$0.55
1,000 results	$5.50
10,000 results	$55.00

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 NHTSA Vehicle Recalls & Complaints 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 NHTSA 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/nhtsa-vehicle-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 that your make, model, and year combination is valid. Try leaving model and year empty and searching only by make to verify the manufacturer name is spelled correctly. Also confirm you have selected the correct mode, recalls or complaints, for the data you expect.

The actor returns fewer records than my maxItems setting.

The actor stops when it has collected all matching records from the NHTSA database. If fewer records exist than your maxItems value, you will receive everything available. Try broadening your filters by removing the model or year constraint.

I entered a make name but the actor did not recognize it.

Use the official NHTSA manufacturer name. For example, use 'Toyota' not 'Toyota Motor Corporation', and 'Ford' not 'Ford Motor Company'. Check the NHTSA website for the exact spelling if you are unsure.

The run timed out before reaching my maxItems.

Large requests with broad filters can take time. Increase the actor's timeout setting in the run options, or narrow your filters to a smaller set of vehicles and run multiple targeted jobs.

Complaints mode returns different fields than recalls mode.

This is expected. Recall records contain campaign numbers, defect summaries, and remedy information. Complaint records contain consumer narratives, incident dates, and failure descriptions. The schema changes based on the mode you select.

FAQ

Question	Answer
What is the difference between recalls mode and complaints mode?	Recalls mode returns official NHTSA safety recall campaigns with the defect description, remedy, and affected vehicle count. Complaints mode returns consumer-submitted reports describing problems they experienced, which may or may not have led to a recall.
Can I search by VIN instead of make and model?	This actor filters by make, model, and model year. If you need VIN decoding with recall lookup, consider a VIN-specific actor. You can still get all recalls for a vehicle by entering its make, model, and year.
Does this cover Canadian or European recalls?	No. This actor pulls data from the U.S. National Highway Traffic Safety Administration database, which covers vehicles sold or registered in the United States.
How many records can I pull in one run?	You can set the maximum up to one million records. The actual number returned depends on how many recalls or complaints match your filters.
Do I need an API key or NHTSA account?	No. The actor reads publicly available NHTSA data feeds and requires no registration, API key, or authentication.
Can I leave the make, model, and year fields empty?	Yes. Leaving all three empty returns every available record across all manufacturers and years, up to your maxItems limit.
What export formats are supported?	Your dataset can be exported to CSV, JSON, Excel, or XML from the Apify platform after the run completes.
Does the actor include the recall remedy and repair instructions?	Yes. Recall records include the official NHTSA defect summary and remedy description as provided by the manufacturer.
How fresh is the data?	The actor reads the live NHTSA database on each run, so you always get the latest published recalls and complaints.
Can I schedule this to run automatically?	Yes. You can set up a recurring schedule in Apify to run the actor daily, weekly, or monthly and receive new recall or complaint records as they appear.

Related actors

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 National Highway Traffic Safety 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.