# eBay Scraper + AI Flip Finder & Market Analysis (`buseta/ebay-scraper`) Actor

Scrape eBay listings with AI-powered flip analysis. Get product prices, seller feedback, shipping costs, and condition. AI scores each listing for resale potential with estimated market value and profit potential. AI market report identifies best deals and flip opportunities.

- **URL**: https://apify.com/buseta/ebay-scraper.md
- **Developed by:** [buseta](https://apify.com/buseta) (community)
- **Categories:** E-commerce, Automation, AI
- **Features:** Limited permissions
- **Stats:** 42 total users, 1 monthly users, 100.0% runs succeeded, 1 bookmarks
- **User rating**: No ratings yet

## Pricing

from $6.00 / 1,000 products

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

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

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
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.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## 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.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## eBay Scraper + AI Flip Finder & Market Analysis

Scrape eBay listings with **AI-powered resale analysis**. Extract prices, seller feedback, shipping, and condition — then let AI score each listing for flip potential, estimate market value, and flag risks before you buy.

### Who Is This For?

- **Resellers & arbitrage hunters** — Find underpriced listings with AI flip scores and estimated market values
- **E-commerce businesses** — Monitor competitor pricing and sourcing opportunities on eBay
- **Buyers** — Compare prices across hundreds of listings and get AI verdict on which are real deals
- **Market researchers** — Track pricing trends, condition distribution, and seller quality at scale

### Features

- **Full product data** — name, price, condition, shipping cost, availability, seller feedback, location
- **2 modes** — search by keyword or scrape specific product URLs
- **Condition filter** — new / used / refurbished
- **Multiple sort options** — best match, lowest price, highest price, newly listed, ending soonest
- **AI Flip Finder** — per-listing AI score (0-100) with estimated market value, profit potential, and risk flags
- **AI Market Report** — one-click analysis of the whole dataset: best deals, pricing insights, flip opportunities
- **CSV-friendly output** — ready for Excel, Google Sheets, or your CRM

### Use Cases

#### 1. Find Underpriced Items to Flip

```json
{
    "scrape_type": "search",
    "search": "vintage Nintendo GameBoy",
    "sort_by": "price_lowest",
    "max_products": 50,
    "ai_flip_analysis": true,
    "ai_market_report": true
}
```

Each listing gets a flip score with AI reasoning:

```json
{
    "ai_flip_score": 85,
    "ai_estimated_market_value": "$120-150",
    "ai_profit_potential": "high",
    "ai_flip_verdict": "Listed at $65 with original box and working condition — comparable sold listings average $135. Strong flip candidate.",
    "ai_risks": [
        "Seller feedback only 94% — verify return policy",
        "Photos don't show screen condition clearly",
        "Shipping cost adds $12 to effective price"
    ]
}
```

#### 2. Price Comparison for Buyers

```json
{
    "scrape_type": "search",
    "search": "iPhone 15 Pro 256GB",
    "condition": "used",
    "max_products": 30,
    "ai_market_report": true
}
```

Returns 30 used iPhones plus an AI market summary: best deals, average price, overpriced listings to avoid.

#### 3. Sourcing Research for Resellers

```json
{
    "scrape_type": "search",
    "search": "Air Jordan 1 size 10",
    "sort_by": "ending_soonest",
    "max_products": 100,
    "ai_flip_analysis": true
}
```

Scores 100 listings ending soon with flip potential — target the auctions with best score-to-price ratio.

#### 4. Competitor Price Monitoring

```json
{
    "scrape_type": "search",
    "search": "mechanical keyboard custom",
    "max_products": 100,
    "ai_market_report": true
}
```

Track how competitors price a category and identify pricing gaps.

#### 5. Scrape Specific Listings

```json
{
    "scrape_type": "product",
    "product_urls": [
        "https://www.ebay.com/itm/174076604918",
        "https://www.ebay.com/itm/123456789012"
    ],
    "ai_flip_analysis": true
}
```

### AI Flip Analysis

When `ai_flip_analysis` is enabled, every listing is analyzed by Claude (via OpenRouter) and enriched with:

| Field | Description |
|-------|-------------|
| `ai_flip_score` | Resale potential 0-100 |
| `ai_estimated_market_value` | AI's estimate of typical resale price |
| `ai_profit_potential` | low / medium / high |
| `ai_flip_verdict` | 2-3 sentence reasoning |
| `ai_risks` | Up to 3 risk flags to check before buying |

### AI Market Report

When `ai_market_report` is enabled, the full dataset is analyzed once and you get a market-wide summary pushed to the dataset + saved as `AI_MARKET_ANALYSIS` in the Key-Value Store:

- **Market summary** — pricing landscape, condition mix, seller quality
- **Best deals** — specific listings to flag as high-value
- **Pricing insights** — average, median, outliers
- **Flip opportunities** — categories or conditions with biggest spreads

### Pricing

| Event | Price |
|-------|-------|
| Product scraped | $6.00 / 1,000 |
| AI Flip Analysis | $4.00 / 1,000 |
| AI Market Report | $1.00 / 1,000 analyzed |
| Platform usage | Free |

#### Typical Run Costs

| Use Case | Products | AI Flip | AI Report | Total |
|----------|----------|---------|-----------|-------|
| Quick price check (20 listings) | $0.12 | — | — | **$0.12** |
| Flip research (50 listings + flip scoring) | $0.30 | $0.20 | — | **$0.50** |
| Market analysis (100 listings + report) | $0.60 | — | $0.10 | **$0.70** |
| Full pipeline (100 listings + flip + report) | $0.60 | $0.40 | $0.10 | **$1.10** |
| Deep research (500 listings + flip + report) | $3.00 | $2.00 | $0.50 | **$5.50** |

### Output Fields

Each listing in the dataset includes:

| Field | Description |
|-------|-------------|
| `name` | Product title |
| `item_id` | eBay item ID |
| `item_url` | Direct listing URL |
| `price.amount` | Numeric price |
| `price.currency` | Currency code (USD, etc.) |
| `price.condition` | New / Used / Refurbished |
| `price.shipping_cost` | Shipping cost (0 if free) |
| `price.availability` | InStock / OutOfStock |
| `description_snippet` | First 300 chars of description |
| `seller.name` | Seller username |
| `seller.feedback_percent` | Positive feedback % |
| `location` | Item location |
| `ai_flip_score` | AI resale score (if enabled) |
| `ai_estimated_market_value` | AI's market value estimate |
| `ai_profit_potential` | low / medium / high |
| `ai_flip_verdict` | AI reasoning |
| `ai_risks` | Array of risk flags |

### Tips

- **Start small** — Test with `max_products: 20` to verify data quality before running larger scrapes
- **Use `ending_soonest`** for flip hunting — auctions closing soon often have the best deals
- **Combine flip + report** — Flip scoring tells you which individual listings are good; the market report shows category-wide patterns
- **Check shipping costs** — A "cheap" listing with $30 shipping may not be the deal it appears
- **Filter by condition** — Use `condition: "used"` or `"refurbished"` for better flip margins vs new

### Keywords

eBay scraper, eBay product scraper, eBay price scraper, eBay listing scraper, eBay resale tool, eBay flip finder, eBay arbitrage, eBay price comparison, eBay seller data, eBay market analysis, eBay AI analysis, eBay profit calculator, eBay sourcing tool

# Actor input Schema

## `scrape_type` (type: `string`):

Type of scraping to perform: Search or Product List

## `search` (type: `string`):

(if Search): Keyword to search on eBay

## `product_urls` (type: `array`):

(if Product List): List of eBay product URLs to scrape

## `sort_by` (type: `string`):

Products will be sorted by this option (search mode only)

## `max_products` (type: `integer`):

Maximum number of products to scrape

## `condition` (type: `string`):

Filter by item condition (search mode only)

## `proxy_config` (type: `object`):

Select proxies to be used for scraping

## Actor input object example

```json
{
  "scrape_type": "search",
  "search": "wireless headphones",
  "product_urls": [
    "https://www.ebay.com/itm/174076604918"
  ],
  "sort_by": "best_match",
  "max_products": 5,
  "condition": "",
  "proxy_config": {
    "useApifyProxy": false
  }
}
```

# Actor output Schema

## `results` (type: `string`):

Product data including prices, seller info, and shipping costs from eBay.

# 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 = {
    "scrape_type": "search",
    "search": "wireless headphones",
    "product_urls": [
        "https://www.ebay.com/itm/174076604918"
    ],
    "max_products": 5,
    "proxy_config": {
        "useApifyProxy": false
    }
};

// Run the Actor and wait for it to finish
const run = await client.actor("buseta/ebay-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 = {
    "scrape_type": "search",
    "search": "wireless headphones",
    "product_urls": ["https://www.ebay.com/itm/174076604918"],
    "max_products": 5,
    "proxy_config": { "useApifyProxy": False },
}

# Run the Actor and wait for it to finish
run = client.actor("buseta/ebay-scraper").call(run_input=run_input)

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

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

```

## CLI example

```bash
echo '{
  "scrape_type": "search",
  "search": "wireless headphones",
  "product_urls": [
    "https://www.ebay.com/itm/174076604918"
  ],
  "max_products": 5,
  "proxy_config": {
    "useApifyProxy": false
  }
}' |
apify call buseta/ebay-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,buseta/ebay-scraper"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/lwsifvEpTZugYXVkZ/builds/CgL1ec4zEJgEm8oKo/openapi.json