MercadoLibre Data API: Extract Structured JSON in 2026

This guide covers extracting publicly accessible data. Always review a site's robots.txt and Terms of Service before scraping.

TL;DR

Use AlterLab's Extract API to get typed JSON from MercadoLibre product pages. Define a JSON schema for the fields you need (title, price, currency, SKU, availability), POST the URL and schema, and receive validated data—no HTML parsing required.

Why use MercadoLibre data?

MercadoLibre hosts millions of listings across Latin America, making it a rich source for e‑commerce insights. Teams use this data to:

• Train price‑prediction models for competitive analysis
• Build catalog enrichment pipelines for marketplaces
• Monitor inventory changes and promotional trends in near real time

What data can you extract?

From a typical product page you can pull publicly visible attributes such as:

• title – product name as shown to buyers
• price – current sale price as a string
• currency – ISO code (e.g., USD, ARS, BRL)
• sku – seller‑provided stock keeping unit
• availability – in stock, limited, or out of stock status
• rating – average star rating from user reviews

These fields are safe to scrape because they appear on public listing pages without authentication.

The extraction approach

Raw HTTP requests followed by HTML parsing are fragile: MercadoLibre updates its markup frequently, and anti‑bot measures can block simple scrapers. A data API layer solves these problems by:

• Handling JavaScript rendering and bot challenges automatically
• Returning data that conforms to a user‑defined JSON schema
• Eliminating the need for custom parsers or regex

AlterLab's Extract API acts as a data API, not a scraper. You specify the shape of the output, and the service delivers validated JSON.

Quick start with AlterLab Extract API

First, install the official Python client (or use cURL directly). The examples below show how to request structured data from a MercadoLibre product page.

import alterlab

client = alterlab.Client("YOUR_API_KEY")

schema = {
  "type": "object",
  "properties": {
    "title": {
      "type": "string",
      "description": "The title field"
    },
    "price": {
      "type": "string",
      "description": "The price field"
    },
    "currency": {
      "type": "string",
      "description": "The currency field"
    },
    "sku": {
      "type": "string",
      "description": "The sku field"
    },
    "availability": {
      "type": "string",
      "description": "The availability field"
    },
    "rating": {
      "type": "string",
      "description": "The rating field"
    }
  }
}

result = client.extract(
    url="https://mercadolibre.com/example-page",
    schema=schema,
)
print(result.data)

The same request works with cURL:

curl -X POST https://api.alterlab.io/v1/extract \
  -H "X-API-Key: YOUR_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "url": "https://mercadolibre.com/example-page",
    "schema": {"properties": {"title": {"type": "string"}, "price": {"type": "string"}, "currency": {"type": "string"}}}
  }'

For high‑volume workloads you can launch asynchronous jobs and poll for completion, or use webhooks to push results to your server.

import alterlab
import time

client = alterlab.Client("YOUR_API_KEY")

urls = [
    "https://mercadolibre.com/product/1",
    "https://mercadolibre.com/product/2",
    "https://mercadolibre.com/product/3",
]

jobs = []
for u in urls:
    job = client.extract_async(
        url=u,
        schema={"type": "object", "properties": {"title": {"type": "string"}, "price": {"type": "string"}}},
    )
    jobs.append(job.id)

# Poll until all jobs finish
done = False
while not done:
    done = all(client.get_job(j).status == "completed" for j in jobs)
    time.sleep(2)

results = [client.get_job(j).data for j in jobs]
print(results)

See the Extract API docs for full parameter details.

Define your schema

The Extract API uses JSON Schema to validate and coerce the output. By declaring each field's type and description you guarantee that the returned data matches expectations. For example, marking price as a string prevents accidental numeric conversion that could drop leading zeros or currency symbols.

AlterLab applies the schema after extraction, stripping any extra properties and ensuring required fields are present. If a field cannot be resolved, the API returns an error with a helpful message, letting you adjust the selector or fallback logic.

Handle pagination and scale

MercadoLibre search results span many pages. To collect large datasets:

1. Batch requests – group up to 100 URLs per async job to reduce overhead.
2. Rate limiting – stay within the limits shown in your dashboard; AlterLab automatically retries with exponential backoff.
3. Cost control – each successful extraction costs between $0.001 and $0.50. View predictions with the cost‑estimation endpoint before scaling. See AlterLab pricing for details.
4. Storage – stream results directly to a data warehouse or object store to avoid holding large payloads in memory.

For continuous monitoring, combine the Extract API with AlterLab's Scheduling feature to run extractions on a cron‑like schedule and trigger webhooks when new data arrives.

Key takeaways

• Use a data API to get typed JSON from MercadoLibre without writing parsers.
• Define a JSON schema to shape the output and enforce correctness.
• Start with a single URL, then scale with async jobs, pagination, and scheduling.
• Always verify that your extraction complies with the site's robots.txt and Terms of Service.

Start building your MercadoLibre data pipeline today—sign up for an API key and run the first extract in under a minute.