# Mercado Libre Reviews Scraper — Reviews & Opiniones to JSON (`omao/mercado-libre-reviews-scraper`) Actor

Scrape Mercado Libre product reviews into clean JSON: rating, text, date and helpful votes. Great for sentiment analysis and product research.

- **URL**: https://apify.com/omao/mercado-libre-reviews-scraper.md
- **Developed by:** [Marouane Oulabass](https://apify.com/omao) (community)
- **Categories:** E-commerce
- **Stats:** 1 total users, 0 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $2.88 / 1,000 review scrapeds

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.

Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

## Mercado Libre Reviews Scraper — Product Reviews & Opiniones to JSON, CSV & Excel

**Scrape Mercado Libre product reviews by URL and get the star rating, full review text, date and helpful votes — as clean JSON, CSV or Excel, one row per review.** Ratings tell you *how much* customers like a product; review text tells you *why*. Use it for sentiment analysis, product research and competitor monitoring across Latin America's biggest marketplace.

> AI-agent ready: this Actor is callable and payable by AI agents via [x402](https://docs.apify.com/platform/integrations/x402) (USDC on Base), no Apify account required.

### How to get Mercado Libre reviews as JSON or CSV

Mercado Libre shows reviews ("opiniones del producto") on each product page, but there's no export button and no public API for them. This scraper takes any list of product URLs and returns every highlighted review as structured data — rating (1–5), full text, relative date, helpful-vote count — tied to the product ID and a clean permalink. Export in one click to **JSON, CSV, Excel or HTML**, or pull it live via the API into Google Sheets, a database or your app.

### How to analyze Mercado Libre customer sentiment

One clean row per review means the data drops straight into your analysis stack:

- **Sentiment analysis** — feed `reviewText` + `ratingValue` to your NLP model or LLM and quantify perception by product or brand.
- **Product research** — surface recurring complaints and praise before sourcing or launching a product.
- **Competitor monitoring** — schedule runs on rival listings and track how their review sentiment moves over time.
- **AI / RAG pipelines** — real customer language in Spanish and Portuguese, ready for embeddings.

### What you get — one row per review

```json
{
  "productId": "MLM66623726",
  "permalink": "https://www.mercadolibre.com.mx/.../p/MLM66623726",
  "ratingValue": 5,
  "reviewText": "Para ser una laptop portátil es bastante potente, muy buena opción...",
  "reviewDate": "Hace 1 mes",
  "likes": 23,
  "reviewRank": 1,
  "scrapedAt": "2026-07-11T17:00:00Z"
}
```

### Input options

| Field | Type | Description |
|---|---|---|
| `productUrls` | array of strings | Mercado Libre product URLs whose reviews to scrape. Required. |
| `maxReviewsPerProduct` | integer | Optional cap per product. |

```json
{ "productUrls": ["https://www.mercadolibre.com.mx/.../p/MLM66623726"] }
```

Works across the Latin American Mercado Libre sites (MX, AR, BR, CL, CO and more).

### Why this reviews scraper

- 💬 **Full review data** — star rating, complete text, relative date and "helpful" vote count, not just an average score.
- 🔗 **Clean provenance** — every row carries the product ID and a clean permalink, so multi-product runs stay organized.
- 💸 **Fair billing** — you pay per review actually returned; anti-bot challenges and failed pages cost nothing.
- 🧰 **Part of a toolkit** — pair with the [Mercado Libre Scraper](https://apify.com/omao/mercado-libre-scraper) (product discovery by keyword) for search-to-sentiment pipelines.

### FAQ

**How do I scrape reviews from Mercado Libre?**
Paste product URLs into `productUrls`, run the Actor, and export the dataset. No account, cookies or API key needed.

**Does it include the review rating and helpful votes?**
Yes — `ratingValue` (1–5) and `likes` come straight from each review.

**Which reviews does it return?**
The reviews Mercado Libre surfaces on the product page (highlighted "opiniones"). Density varies by product — popular products expose more.

**Does it work on all Mercado Libre country sites?**
Yes — any `mercadolibre.com.*` / `mercadolivre.com.br` product URL.

**What about anti-bot blocks?**
Mercado Libre serves anti-bot challenges to some traffic; the Actor retries with residential proxies and skips — never charges — pages it can't load.

### Support

Open an issue on the **Issues** tab — we respond within 48h.

# Actor input Schema

## `productUrls` (type: `array`):

Mercado Libre product URLs whose reviews to scrape.

## `maxReviewsPerProduct` (type: `integer`):

Cap the number of reviews collected per product. Leave empty for all shown.

## `debugSnapshots` (type: `boolean`):

Save an HTML snapshot of the first product page to the key-value store for diagnostics.

## `healthCheckMode` (type: `boolean`):

Internal monitoring: verify extraction thresholds and fail the run if broken (no billing).

## Actor input object example

```json
{
  "productUrls": [
    "https://www.mercadolibre.com.mx/laptop-lenovo-153-ideapad-slim-3-15arp10-16gb-ram-ssd-1tb/p/MLM66623726"
  ],
  "debugSnapshots": true,
  "healthCheckMode": false
}
```

# Actor output Schema

## `reviews` (type: `string`):

All scraped reviews (rating, text, date, helpful votes) tied to the product.

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "productUrls": [
        "https://www.mercadolibre.com.mx/laptop-lenovo-153-ideapad-slim-3-15arp10-16gb-ram-ssd-1tb/p/MLM66623726"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("omao/mercado-libre-reviews-scraper").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = { "productUrls": ["https://www.mercadolibre.com.mx/laptop-lenovo-153-ideapad-slim-3-15arp10-16gb-ram-ssd-1tb/p/MLM66623726"] }

# Run the Actor and wait for it to finish
run = client.actor("omao/mercado-libre-reviews-scraper").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "productUrls": [
    "https://www.mercadolibre.com.mx/laptop-lenovo-153-ideapad-slim-3-15arp10-16gb-ram-ssd-1tb/p/MLM66623726"
  ]
}' |
apify call omao/mercado-libre-reviews-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=omao/mercado-libre-reviews-scraper",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/qqJYHg8ehgH9zRz3x/builds/uSY8XD5ns6aIlKNOf/openapi.json