Car Data Scraper

Car Data Scraper builds one consolidated technical and performance record per car variant by aggregating four automotive reference sources (auto-data.net, ultimatespecs.com, carperformancedata.com and zeperfs.com). Ask for a whole brand or a list of models and get a clean, deduplicated row for every engine variant, with each value traced back to the source it came from.

Type Audi (or a list like Audi RS3, Audi TT) and get back one row per variant with power, torque, 0-100 km/h, top speed, weight, dimensions, fuel economy, gearbox, brakes and tyres, plus a per-field source tag and a conflict flag when two sources disagree. A full brand pull exports straight to JSON, CSV or Excel, no API key and no HTML parsing on your side.

What is Car Data Scraper?

Car Data Scraper resolves a brand or model into its full list of engine variants, scrapes each one from every enabled source, then matches and merges the results into a single consolidated row per physical variant. auto-data.net acts as the backbone catalog; the other sources enrich and cross-check its data.

The consolidated model is built so you can trust and audit every figure: each field carries the source it came from, competing values from other sources are kept as alternatives, and a hasConflict flag is raised when numeric values diverge beyond a built-in tolerance.

Car Data Scraper supports the following:

• Scrape a whole brand: one entry like Audi expands to every model, generation and engine variant.
• Scrape a model list: Audi TT expands to all TT generations and engine variants; mix several models in one run.
• Consolidate across four sources: power, torque, acceleration, top speed, dimensions, weight, fuel economy, transmission and chassis, merged per variant.
• Trace and reconcile every value: per-field source tag, alternative values, and a conflict flag with the maximum deviation between sources.

What data can I extract with Car Data Scraper?

Group	Example fields
⚡ Performance	0-100 km/h, 0-60 mph, quarter mile, top speed, power-to-weight, peak G
🔧 Engine	power (hp / kW), torque, displacement, cylinders, aspiration, fuel type
⚙️ Transmission	drive wheels, gearbox type, number of gears
📏 Dimensions	length, width, height, wheelbase, kerb weight, drag coefficient
⛽ Fuel economy	combined / urban / extra-urban consumption, CO2, fuel tank
🛞 Chassis	front / rear brakes, tyres, suspension, steering

How can I use data scraped from car reference sites?

Build pricing and residual-value models, power a vehicle comparison or configurator, feed a performance database or enthusiast site, enrich a dealer or marketplace catalog, or run engineering and market research across an entire brand history. Because the output is one tidy row per variant, it drops straight into a spreadsheet, a database or a BI tool.

How to use Car Data Scraper

Here's how to use Car Data Scraper in 5 steps:

1. Create a free Apify account using your email.
2. Open Car Data Scraper.
3. Pick the Input mode (Brand or Model names list), then add a brand (for example Audi) or a list of models (for example Audi TT), and optionally set a year range or a max items cap.
4. Click the Start button and wait for the data to be extracted.
5. Download your data in JSON, XML, CSV, Excel or HTML.

How much will scraping car data cost you?

Car Data Scraper uses a pay-per-event pricing model. You are charged once per car data record successfully emitted. Failed fetches, parse errors and unresolved variants are returned as visible error rows but are never charged.

See the Pricing tab for the full price table by Apify subscription tier (Free, Starter, Scale, Business), where higher tiers unlock automatic discounts.

You can cap the spend of any single run from the Apify Console with ACTOR_MAX_TOTAL_CHARGE_USD, and the maxItems input gives you a hard limit on how many variants are emitted.

As a rule of thumb, a single-model run (a few dozen variants) costs roughly $0.10 to $0.30, and a full brand a few dollars; the exact figure depends on your subscription tier.

⬇️ Input

The input is a JSON object specifying which brands or models to scrape, plus optional filters and source settings. See the Input tab for the full schema with all fields and defaults.

Car Data Scraper input examples

Scrape a list of specific models (set inputMode to models):

{
  "inputMode": "models",
  "models": ["Audi RS3", "Audi TT"],
  "yearMin": 2015,
  "maxItems": 200
}

Scrape a whole brand (set inputMode to brand):

{
  "inputMode": "brand",
  "brand": "Audi",
  "maxItems": 500
}

Only the field matching inputMode is used; the other is ignored. Always set inputMode to match how you are targeting cars. Year bounds and an excludeModels filter are available under Advanced options.

⬆️ Output

Car Data Scraper stores results in a dataset, one car data record per row. Each numeric or text field is an object carrying its value, canonical unit, the source the reference value came from, and any alternatives from other sources. Error rows (carrying _error: true) are returned for visibility and are never charged.

For programmatic access in Python, Node.js or PHP, see the Apify API reference.

Sample output

A real row from an Audi RS3 run, which returns 8 variants across four generations (8PA to 8Y). This one is consolidated from two sources: auto-data.net supplies the full spec sheet, and carperformancedata.com adds measured performance (quarter mile, peak G) and disagrees on the 0-60 mph time, which is kept as a conflict with both values. Each row carries flat summary columns (for easy browsing, filtering and spreadsheet export), a stable canonicalVariantId, a numeric dedupeConfidence, plus nested sections that keep the per-field source and alternative values.

{
  "canonicalVariantId": "audi-rs3-sedan-2.5l-400hp-2021",
  "make": "Audi",
  "model": "RS3",
  "generation": "RS3 Sedan (8Y)",
  "modification": "2.5 TFSI (400 Hp) quattro S tronic",
  "yearStart": 2021,
  "yearEnd": 2024,
  "bodyType": "Sedan",
  "powerHp": 400,
  "torqueNm": 500,
  "zeroToHundredS": 3.8,
  "topSpeedKmh": 250,
  "engineCc": 2480,
  "cylinders": 5,
  "transmission": "automatic transmission S tronic",
  "driveType": "All wheel drive (4x4)",
  "curbWeightKg": 1575,
  "fuelConsumptionL100": 8.9,
  "co2GKm": 201,
  "sources": ["autodata", "carperformancedata"],
  "dedupeConfidence": 0.99,
  "scrapedAt": "2026-06-25T13:04:06.431Z",
  "engine": {
    "power_hp": { "value": 400, "unit": "hp", "source": "autodata", "alternatives": [{ "value": 401, "source": "carperformancedata" }] },
    "engine_code": { "value": "EA855 evo / DNWC", "source": "autodata" }
  },
  "performance": {
    "accel_0_100_kmh": { "value": 3.8, "unit": "s", "source": "autodata" },
    "accel_0_60_mph": { "value": 3.6, "unit": "s", "source": "autodata", "alternatives": [{ "value": 3.4, "source": "carperformancedata" }] },
    "quarter_mile_s": { "value": 11.7, "unit": "s", "source": "carperformancedata" },
    "peak_g": { "value": 0.982, "source": "carperformancedata" }
  },
  "sourcesDetail": [
    { "source": "autodata", "sourceUrl": "https://www.auto-data.net/en/audi-rs3-sedan-8y-2.5-tfsi-400hp-quattro-s-tronic-44004" },
    { "source": "carperformancedata", "sourceUrl": "https://carperformancedata.com/cars/37" }
  ],
  "flags": {
    "hasConflict": true,
    "conflicts": [{ "field": "accel_0_60_mph", "maxDeviationPct": 5.9, "values": [{ "value": 3.6, "source": "autodata" }, { "value": 3.4, "source": "carperformancedata" }] }],
    "matchConfidence": { "autodata": "exact", "carperformancedata": "exact", "ultimatespecs": "none", "zeperfs": "none" }
  }
}

Flat summary columns also include fuelType, powerKw, valves, gears, lengthMm, widthMm, heightMm, wheelbaseMm, doors, seats and more, each mirrored by a fully traced entry in the engine, transmissionDetail, dimensions, fuelEconomy and chassis sections.

Benchmarks

A measured run on the current build, input Audi RS3:

• 8 variants returned, one per RS3 generation from the 8PA (340 hp, 2011) to the 8Y facelift (400 hp, 2024), in 33 seconds for about $0.04, with 0 errors.
• The current-generation Sedan is cross-checked against carperformancedata.com, which adds a measured quarter mile and peak G and surfaces a 0-60 mph conflict (3.6 s vs 3.4 s) instead of silently picking one value.
• Every row carries a stable canonicalVariantId and, when a second source is merged, a numeric dedupeConfidence (0.99 on the cross-checked row).

Cross-source coverage depends on the model. Mainstream models match ultimatespecs.com and carperformancedata.com more often than niche performance variants such as the RS3, which ultimatespecs.com nests under the A3 line, so those stay single-source more often. A full-brand pull returns a couple hundred variants in a few minutes.

Known limitations

• Coverage varies by source. auto-data.net is the backbone and is always present; ultimatespecs.com, carperformancedata.com and zeperfs.com enrich a variant only when they have it and are reachable. zeperfs.com is rate-limited and can be unavailable on a given run; when a source is unavailable it is logged and counted, not emitted as a data row, and the variant is still returned with whatever resolved.
• Cross-source matching is fingerprint-based (make, model, displacement, power, production years). Near-identical variants (facelifts, regional or market versions, AWD vs FWD, DIN vs SAE power ratings) can occasionally stay single-source or, more rarely, be matched too loosely. The matchConfidence and sources fields let you audit this on every row.
• Figures are reported as published by each source. Values are normalized to a canonical metric unit (each field carries its unit), but regional and market differences are not reconciled.
• No market or region field. The sources describe each variant by generation and chassis code (for example 8V or 8Y), not by sales market, so there is no reliable per-variant market or region signal to extract and the output does not carry one.
• Source priority and the conflict tolerance are fixed (auto-data, then ultimatespecs, then zeperfs, then carperformancedata; conflicts flagged at a built-in deviation tolerance), not per-run configurable.

Frequently asked questions

How does Car Data Scraper work?

It resolves each requested brand or model into its full list of engine variants on auto-data.net (the backbone catalog), scrapes each variant from every enabled source, then matches records across sources by a fingerprint (make, model, displacement, power and production years) and merges them into one row, picking a reference value per field by a fixed source priority (auto-data, then ultimatespecs, then zeperfs, then carperformancedata).

Which sources does it cover?

Four: auto-data.net and ultimatespecs.com (full technical sheets), carperformancedata.com (acceleration and quarter-mile figures with original-source attribution) and zeperfs.com (European performance figures). auto-data.net is always enabled as the backbone; ultimatespecs.com and carperformancedata.com enrich by default. zeperfs.com is off by default (it is rate-limited and has stricter access terms).

What happens when two sources disagree?

The reference value is taken from the highest-priority source (a fixed order: auto-data, then ultimatespecs, then zeperfs, then carperformancedata), every other source's value is kept under alternatives, and a hasConflict flag plus the maximum deviation is recorded when numeric values differ beyond a built-in tolerance. Nothing is silently dropped.

Can I integrate Car Data Scraper with other apps?

Yes. Results can flow into Make, Zapier, n8n, Google Sheets, Looker Studio or Power BI through Apify's integrations, or be pulled directly with the Apify API.

Can I use Car Data Scraper as its own API?

Yes. Use apify-client for Node.js or Python to start runs and fetch the dataset. See the API tab on the Actor page.

Can I use Car Data Scraper via MCP?

Yes. Car Data Scraper can be accessed by AI assistants like Claude or ChatGPT through the Apify MCP server. Go to the MCP tab on the Actor page for setup, or connect to mcp.apify.com and add Car Data Scraper as a tool.

Your feedback

We're always working on improving the performance of our Actors. So if you've got any technical feedback for Car Data Scraper or simply found a bug, please create an issue on the Actor's Issues tab.

More free tools, scrapers, MCP servers and data studies from the same team: mr-bridge.com.

Legal & responsible use

Car Data Scraper extracts vehicle technical specifications and measured performance figures, which are factual data, not personal data. It does not extract names, contact details or any private user information.

Each source has its own terms of use, and some restrict automated access or commercial reuse. For this reason zeperfs.com is disabled by default, and the input includes a rights-confirmation checkbox. Before enabling additional sources or using the output commercially, confirm that your use is permitted by each source you rely on.

We believe that scraping public factual data for ethical purposes is safe. You remain responsible for how you use the results and for complying with each source's terms and with the laws that apply to you. If you're unsure whether your use is legitimate, consult your lawyers. You can also read the Apify blog post on the legality of web scraping.