Mexico VIN/NIV Finder by Year, Make, Model

Here is one real result, with every field the actor returns:

{
  "id": "1",
  "year": 2023,
  "make": "Chirey",
  "model": "Tiggo 8PRO",
  "version": "Luxury",
  "engine": null,
  "transmission": null,
  "fuel": null,
  "vin": "LVTDB21B4SD273072",
  "vinYear": 2025,
  "sourceUrl": "https://www.autocosmos.com.mx/auto/usado/chirey/tiggo-8-pro-max/premium-4x4/5992666011a945d3b3dfd59f22ce3ac5",
  "source": "autocosmos.com.mx",
  "confidence": "Baja",
  "status": "validado",
  "capturedAt": "2026-08-10T14:19:17.868Z"
}

The most complete Mexico VIN/NIV finder available. For each vehicle you provide, it returns a real observed VIN from public used-car listings plus the source URL, decoded VIN model year, engine, transmission, fuel and a confidence level, and it accepts structured input, a pasted table, or an uploaded CSV/Excel file for bulk lookup.

📥 Input · 📤 Output · 💰 Pricing · ▶️ Examples

Table of contents

• What it does
• Quickstart
• Input reference
• Output reference
• Example output record
• Run via API and CLI
• Fetch results
• Billing and limits
• FAQ and troubleshooting

What it does

For each vehicle you provide (year, make, model, version), the actor searches public Mexican used-car listings for a matching vehicle and returns a real observed VIN/NIV, the listing URL it came from, the decoded VIN model year, and a confidence level. Engine, transmission and fuel are added when the source listing exposes them, and returned as null otherwise. You can supply vehicles as a structured JSON array, a pasted CSV/TSV table, or an uploaded CSV/Excel file; non-standard column names in a table or file are mapped by a low-cost AI normalization step.

VINs are real values observed on public listings, not generated. Match confidence reflects how closely the listing matches your requested vehicle.

Quickstart

Open the actor, paste this into the input, and press Run. It looks up VINs for three Mexican vehicles.

{
  "vehicles": [
    { "id": "1", "year": 2023, "make": "Chirey", "model": "Tiggo 8PRO", "version": "Luxury" },
    { "id": "2", "year": 2024, "make": "BYD", "model": "Dolphin", "version": "Base" },
    { "id": "3", "year": 2024, "make": "GWM", "model": "Ora 03", "version": "Luxury" }
  ],
  "aiNormalize": true
}

To skip the AI normalization charge when using a table or file, name your columns exactly id, year, make, model, version in English.

Input reference

Field	Type	Required	Default	Description
vehicles	object[]	no	(see quickstart)	List of vehicles to look up, each an object with year, make, model, version and an optional id. Use this or one of the table/file inputs below.
tableText	string	no	(empty)	Paste a CSV or TSV table of vehicles. Use standard columns id, year, make, model, version (English) to skip the AI normalization charge.
file	string	no	(empty)	Upload a CSV or Excel (.xlsx) file of vehicles. Standard English columns skip the AI charge; other names or languages are mapped by AI.
fileUrl	string	no	(empty)	Public link to a CSV or Excel file of vehicles. Standard English columns skip the AI charge.
aiNormalize	boolean	no	true	When on, non-standard table/file columns are mapped by a low-cost AI step. Charged only when it actually runs; skipped and free when columns already match.
maxVehicles	integer	no	(all)	Maximum number of vehicle rows to process.

Output reference

One dataset item per vehicle. Types: string, integer, or null when the source value is absent.

Field	Type	Description
id	string	The id you passed for this vehicle (echoed back for joining).
year	integer	Requested model year.
make	string	Requested make.
model	string	Requested model.
version	string	Requested version / trim.
engine	string	Engine from the source listing, or null.
transmission	string	Transmission from the source listing, or null.
fuel	string	Fuel type from the source listing, or null.
vin	string	Real observed VIN/NIV from a public listing, or null if none was found.
vinYear	integer	Model year decoded from the VIN, or null.
sourceUrl	string	URL of the listing the VIN was observed on.
source	string	Source site the listing came from.
confidence	string	Match confidence (Alta, Media, Baja).
status	string	Lookup status, for example validado when a VIN was found and checked.
capturedAt	string	ISO 8601 timestamp of when the record was collected.

Example output record

Real record from a live run (input the three-vehicle quickstart above):

{
  "id": "1",
  "year": 2023,
  "make": "Chirey",
  "model": "Tiggo 8PRO",
  "version": "Luxury",
  "engine": null,
  "transmission": null,
  "fuel": null,
  "vin": "LVTDB21B4SD273072",
  "vinYear": 2025,
  "sourceUrl": "https://www.autocosmos.com.mx/auto/usado/chirey/tiggo-8-pro-max/premium-4x4/5992666011a945d3b3dfd59f22ce3ac5",
  "source": "autocosmos.com.mx",
  "confidence": "Baja",
  "status": "validado",
  "capturedAt": "2026-08-10T14:19:17.868Z"
}

Run via API and CLI

Start a run and wait for it to finish, then read the dataset. Replace <TOKEN> with your Apify API token.

Run synchronously and get dataset items in one call:

curl -X POST "https://api.apify.com/v2/acts/scrapers_lat~mexico-vin-finder/run-sync-get-dataset-items?token=<TOKEN>" \
  -H "Content-Type: application/json" \
  -d '{"vehicles":[{"id":"1","year":2023,"make":"Chirey","model":"Tiggo 8PRO","version":"Luxury"}]}'

Start a run asynchronously:

curl -X POST "https://api.apify.com/v2/acts/scrapers_lat~mexico-vin-finder/runs?token=<TOKEN>" \
  -H "Content-Type: application/json" \
  -d '{"vehicles":[{"id":"2","year":2024,"make":"BYD","model":"Dolphin","version":"Base"}]}'

Apify CLI:

apify call scrapers_lat/mexico-vin-finder \
  --input '{"vehicles":[{"id":"3","year":2024,"make":"GWM","model":"Ora 03","version":"Luxury"}]}'

Fetch results

Every run writes to a dataset. Fetch items as JSON, CSV, or Excel by changing format:

# JSON
curl "https://api.apify.com/v2/datasets/<DATASET_ID>/items?token=<TOKEN>&clean=true&format=json"

# CSV
curl "https://api.apify.com/v2/datasets/<DATASET_ID>/items?token=<TOKEN>&clean=true&format=csv"

# Paginate large datasets
curl "https://api.apify.com/v2/datasets/<DATASET_ID>/items?token=<TOKEN>&offset=1000&limit=1000"

<DATASET_ID> is returned as defaultDatasetId in the run object. Use offset and limit to page through large result sets. clean=true drops empty and internal fields.

Billing and limits

• Pay per result. Each vehicle lookup is billed as an attempt. A vin-validated charge applies only when a real VIN is found and checked. See the pricing tab for current prices.
• AI normalization add-on. If your pasted table or uploaded file uses non-standard column names, a low-cost ai-normalization charge applies once. Use the standard English columns to avoid it entirely.
• No charge on failure. If a run errors, the actor writes a single item with a populated error field and does not charge for it.
• Spend cap respected. Set maxTotalChargeUsd on the run; once reached, the actor stops looking up, charging and emitting further vehicles.
• Free Apify plans are capped at 10 vehicles per run. Upgrade for higher maxVehicles.

FAQ and troubleshooting

Is the VIN real or generated? Real. Each VIN is observed on a public used-car listing, and sourceUrl links to that listing. If no matching listing is found, vin is null.

What does the confidence level mean? Alta, Media or Baja reflect how closely the found listing matches your requested year, make, model and version. Lower confidence usually means the closest available match differed on trim or year.

How do I avoid the AI normalization charge on a table or file? Name your columns exactly id, year, make, model, version in English. When columns already match, the AI step is skipped and free.

Can I bulk-look-up many vehicles? Yes. Pass a large vehicles array, paste a table into tableText, or upload a CSV/Excel file. Use maxVehicles to cap how many rows are processed.

Why are engine and transmission null? The matching listing did not publish those fields. Missing source values are returned as null, never invented.

Is this an official VIN registry? No. This actor is independent and has no affiliation with any registry or manufacturer. It reads only data that is publicly available on used-car listings. Use it in accordance with the source terms of service.

Related scrapers

• Autocosmos Scraper: Mexican and Latin American vehicle listings.
• Kavak Used Cars Scraper: used-car inventory and pricing.
• Mexico Business Directory Scraper: Mexican business phone and address leads.
• Copart Scraper: salvage vehicle auction lots.
• FAA Aircraft Registry Scraper: US aircraft registrations.
• Carroya Colombia Scraper: Colombian vehicle listings.

More scrapers at scrapers.lat

Built and maintained by scrapers.lat, where we publish scrapers for US and Latin American public platforms: company registries, government data, finance, e-commerce and more. Browse the catalog or request a custom scraper at scrapers.lat.

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Independent tool, not affiliated with any vehicle registry or manufacturer. Accesses only publicly available used-car listing data. Use in accordance with the source terms of service.