Kelley Blue Book Scraper

Kelley Blue Book Scraper

Scrape Kelley Blue Book vehicle valuations and data for any car by year, make, and model. Get fair market price, MSRP, trade-in value, safety scores, consumer reviews, specs, and trim details. No API key needed. Export to CSV, JSON, Excel, or XML.

Kelley Blue Book's website is the go-to source for car valuations, but extracting data manually page by page is slow and error-prone. This scraper reads public KBB vehicle pages directly, returning structured data for any car you specify by year, make, and model. Each run delivers a clean dataset with pricing, ratings, and specs.

Who uses it	What they scrape Kelley Blue Book for
Car dealers	Compare KBB fair market prices against their inventory to set competitive asking prices.
Auto researchers	Gather historical and current vehicle valuations for market analysis reports.
Data analysts	Build datasets of car specs, safety scores, and consumer reviews for predictive models.
Car buyers	Check trade-in values and fair purchase prices before negotiating with a dealer.

What it does

This Actor collects Kelley Blue Book vehicle data by year, make, and model, and returns each vehicle as a flat row with pricing, ratings, specs, and reviews.

• 🚗 Batch lookup: Provide a list of vehicles by year, make, and model, and the scraper processes them all in one run.
• 📍 Localized pricing: Optionally enter a ZIP code to get pricing specific to your area instead of national averages.
• 📊 Full vehicle profile: Each result includes MSRP, fair market price, trade-in value, safety crash test scores, consumer reviews, specs, and trim details.

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

What you can do with Kelley Blue Book data

📈 Build a vehicle valuation database.

A used car dealer runs the scraper weekly with their inventory list to track KBB fair market prices and adjust listings.

🔍 Analyze safety and specs across models.

An auto researcher collects crash test scores and specs for all 2024 sedans to compare safety ratings.

💰 Estimate trade-in values for customers.

A car buyer inputs their current vehicle's year, make, and model to get a trade-in value before visiting a dealership.

📊 Monitor consumer review trends.

A market analyst scrapes consumer reviews for popular SUVs to identify common complaints and praises.

Why choose this scraper

	What you get
Structured data	Every vehicle returns a consistent schema with pricing, ratings, specs, and reviews.
No API key	Scrapes public KBB pages directly, no registration or API token required.
Localized pricing	Enter a ZIP code to get pricing specific to your area.
Batch processing	Look up dozens of vehicles in a single run by providing a list.

How it compares

This scraper focuses on vehicle valuation data (pricing, ratings, specs) from Kelley Blue Book, while the competitors below target car listings for sale.

Feature	ParseForge	Kelley Blue Book Scraper	KBB Cars for Sale Scraper - Kelley Blue Book Listings	Kbb Cars Search Scraper
Vehicle valuations (MSRP, trade-in, fair market)	Yes	Yes	Not listed	Not listed
Safety crash test scores	Yes	Yes	Not listed	Not listed
Consumer reviews	Yes	Yes	Not listed	Not listed
Car listings for sale (price, mileage, VIN)	Not listed	Not listed	Yes	Yes
Dealer info and deal rating	Not listed	Not listed	Yes	Not listed
Batch lookup by year, make, model	Yes	Not listed	Not listed	Not listed
Localized pricing by ZIP code	Yes	Not listed	Not listed	Not listed

Configure the run

Drive the Actor from a list of vehicles (year, make, model) or a single KBB URL. Optionally set a ZIP code for localized pricing and a maximum number of vehicles to collect. The Input tab lists every parameter.

A first run with the defaults:

{
  "vehicles": [
    {
      "year": 2022,
      "make": "toyota",
      "model": "camry"
    },
    {
      "year": 2020,
      "make": "ford",
      "model": "f-150"
    }
  ],
  "maxItems": 10
}

A larger pull:

{
  "vehicles": [
    {
      "year": 2022,
      "make": "toyota",
      "model": "camry"
    },
    {
      "year": 2020,
      "make": "ford",
      "model": "f-150"
    }
  ],
  "maxItems": 200
}

Pricing

Pay-per-result: $0.05466 per result collected. You pay only for the results written to your dataset.

Results collected	Approximate cost
100 results	$5.47
1,000 results	$54.66
10,000 results	$546.60

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 Kelley Blue Book 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 Kelley Blue Book 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/kelley-blue-book-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 vehicle list has correct year, make, and model values. Also verify that the KBB URL is valid and points to a vehicle page.

The scraper is returning incomplete data for some vehicles.

Some vehicle pages may lack certain fields (e.g., safety scores for older models). The scraper returns what is available.

How do I scrape a specific trim level?

Include the trim in the vehicle list if possible, or use a direct KBB URL that specifies the trim.

The run is taking too long.

Reduce the maximum number of vehicles in the input. Large batches take longer to process.

I'm getting an error about rate limiting.

Kelley Blue Book may block frequent requests. Increase the delay between requests or reduce the number of vehicles per run.

FAQ

Question	Answer
Do I need an API key or login to use this scraper?	No. The scraper reads public Kelley Blue Book pages directly, so no API key or account is required.
Can I scrape pricing for multiple vehicles at once?	Yes. Provide a list of vehicles with year, make, and model in the input, and the scraper will process them all in one run.
What data does each vehicle result include?	Each result includes MSRP, fair market price, trade-in value, safety crash test scores, consumer reviews, specs, and trim details.
How do I get localized pricing?	Enter a ZIP code in the input field. The scraper will fetch pricing specific to that area instead of national averages.
What is the maximum number of vehicles I can scrape per run?	You can set a maximum up to 1,000,000 vehicles per run, but be mindful of your Apify platform limits.
Can I use a direct KBB URL instead of a vehicle list?	Yes. If you provide a single KBB URL (e.g., for a specific vehicle page), the scraper will use that instead of the list.
What export formats are supported?	You can export the dataset to CSV, JSON, Excel, or XML from the Apify platform.
Is this scraper legal to use?	Scraping public data from websites is generally legal, but you should review Kelley Blue Book's terms of service and respect their robots.txt.
How often can I run the scraper?	There is no hard limit from the scraper itself, but frequent runs may be rate-limited by KBB. We recommend spacing runs out.
What if a vehicle is not found?	The scraper will skip vehicles that return no data and continue with the rest. Check the run log for details.

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 Kelley Blue Book Co., Inc. 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.