# Wish Scraper MCP Server (`axlymxp/wish-scraper-mcp`) Actor

MCP server + scraper for Wish.com. Let Claude, ChatGPT & Cursor search Wish products, get detail, reviews, categories & autocomplete live via Model Context Protocol — or run it as a classic scraper. Fast direct API. Pay per tool call.

- **URL**: https://apify.com/axlymxp/wish-scraper-mcp.md
- **Developed by:** [axly](https://apify.com/axlymxp) (community)
- **Categories:** E-commerce, AI
- **Stats:** 1 total users, 0 monthly users, 0.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

Pay per event + usage

This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage.

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

## Wish Scraper MCP Server

Give your AI assistant **live access to Wish.com**. This actor runs as a **Model
Context Protocol (MCP) server** so Claude, ChatGPT, Cursor, n8n, and other agents
can search Wish products, pull full detail and reviews, browse categories, and get
autocomplete suggestions — in conversation, no code. It also runs as a **classic
scraper** for scheduled dataset jobs.

### Who it's for

- **AI-assistant users** — ask Claude/ChatGPT/Cursor for Wish products, prices,
  and reviews and get structured answers instantly.
- **Agent & automation builders** — a hosted MCP tool for Wish in LangChain, n8n,
  or custom agents.
- **Developers** — one endpoint for Wish product search + detail + reviews.

### MCP tools

| Tool | What it does |
|---|---|
| `search_wish_products(query, limit, fetch_detail)` | Search Wish by keyword; optional detail enrichment |
| `get_wish_product(product_id_or_url, with_reviews)` | Full product detail: price, variations, images, sold-out |
| `get_wish_reviews(product_id_or_url, limit)` | Customer reviews for a product |
| `wish_autocomplete(query)` | Search-box suggestions for a partial query |
| `get_wish_categories()` | Category tree (names + handles) |
| `browse_wish_category(category_handle, limit)` | Products within a category |

### Connect it

Run the actor in **Standby mode** and point your MCP client at the server URL:

```
<ACTOR_STANDBY_URL>/mcp
```

Example Claude Desktop / Cursor config (Streamable HTTP):

```json
{
  "mcpServers": {
    "wish": {
      "url": "https://<your-standby-url>/mcp"
    }
  }
}
```

Then ask: *"Search Wish for wireless earbuds under $10 and show ratings"* or
*"Get the detail and reviews for this Wish product URL."*

### Output fields

Product tools return normalized rows: `product_id`, `name`, `url`, `image_url`,
`price_usd`, `price_local`, `currency`, `crossed_price_usd`, `rating`,
`review_count`, `num_bought`, `merchant_id`, `merchant_name`, `is_sold_out`,
`variation_count`, `images`, and (on request) `reviews`.

### Classic run mode

Prefer a one-shot dataset job? Provide `searchQueries` / `productIds` in the input
and run it like any scraper — rows land in the dataset. See the companion
**Wish Product Scraper** actor for the full multi-mode dataset scraper (category,
collection, bulk IDs, reviews).

### FAQ

**What is MCP?** The Model Context Protocol — an open standard that lets AI
assistants call external tools. This actor is an MCP server for Wish.com.

**Do I need an account or proxies?** No. It calls Wish's public mobile API
directly and works out of the box.

**How fresh is the data?** Live — every tool call fetches current data.

**Which assistants work?** Any MCP-capable client: Claude Desktop, Cursor,
ChatGPT (via connectors), n8n, LangChain, and custom agents.

**Is it reliable?** It calls the API directly (no fragile browser automation) and
serializes calls safely; per-item failures are skipped and logged.

# Actor input Schema

## `searchQueries` (type: `array`):

Keywords to search (classic run mode only — ignored when connected as an MCP server).

## `productIds` (type: `array`):

Direct Wish product IDs or URLs to fetch (classic run mode only).

## `maxItems` (type: `integer`):

Max products to push in classic run mode.

## `fetchDetail` (type: `boolean`):

Enrich each product with the detail page in classic run mode.

## Actor input object example

```json
{
  "searchQueries": [
    "phone case"
  ],
  "productIds": [],
  "maxItems": 50,
  "fetchDetail": true
}
```

# 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 = {};

// Run the Actor and wait for it to finish
const run = await client.actor("axlymxp/wish-scraper-mcp").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 = {}

# Run the Actor and wait for it to finish
run = client.actor("axlymxp/wish-scraper-mcp").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 '{}' |
apify call axlymxp/wish-scraper-mcp --silent --output-dataset

```

## MCP server setup

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

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/lKEkI2BsSisu58c6q/builds/K14UYOCHfHvNSeWNz/openapi.json