# Logobrands Product Url Parser Spider (`getdataforme/logobrands-product-url-parser-spider`) Actor
The Logobrands Product Url Parser Spider extracts detailed product data from Logobrands URLs, ideal for businesses needing comprehensive information for analysis or integration....
- **URL**: https://apify.com/getdataforme/logobrands-product-url-parser-spider.md
- **Developed by:** [GetDataForMe](https://apify.com/getdataforme) (community)
- **Categories:** AI, Automation, E-commerce
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks
- **User rating**: No ratings yet
## Pricing
from $9.00 / 1,000 results
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/platform/actors/running/actors-in-store#pay-per-event
## What's an Apify Actor?
Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases.
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.
In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md):
```bash
npm install apify-client
```
In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md):
```bash
pip install apify-client
```
In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md):
````bash
# MacOS / Linux
curl -fsSL https://apify.com/install-cli.sh | bash
# Windows
irm https://apify.com/install-cli.ps1 | iex
```bash
In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md).
If your project is in a different language, use 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
## Logobrands Product Url Parser Spider
The Logobrands Product Url Parser Spider is a powerful tool designed to extract detailed product information from Logobrands URLs. This actor is ideal for businesses and individuals looking to gather comprehensive product data for analysis, research, or integration into other systems.
### Features
- **Accurate Data Extraction**: Extracts detailed product information including titles, descriptions, prices, and images.
- **High Performance**: Efficiently processes multiple URLs to deliver results quickly.
- **Reliable Output**: Provides consistent and structured data output for easy integration.
- **Customizable Inputs**: Accepts a list of URLs to target specific products.
- **Comprehensive Data**: Captures additional product details such as tags, variants, and vendor information.
- **User-Friendly**: Simple configuration and setup process.
- **Scalable**: Handles large volumes of URLs with ease.
### Input Parameters
| Parameter | Type | Required | Description | Example |
|-----------|--------|----------|--------------------------------------|---------|
| Urls | Array | Yes | The URLs for the spider to scrape. | `["https://logobrands.com/products/inter-miami-cf-2025-mls-cup-champions-16oz-pint-glass?_pos=1&_sid=4ab221859&_ss=r"]` |
### Example Usage
#### Example Input JSON
```json
{
"Urls": [
"https://logobrands.com/products/inter-miami-cf-2025-mls-cup-champions-16oz-pint-glass?_pos=1&_sid=4ab221859&_ss=r"
]
}
````
#### Example Output JSON
```json
[
{
"product_id": 9472755368167,
"title": "Inter Miami CF 2025 MLS Cup Champions 16oz Pint Glass",
"description_raw": "This classic 16 oz. pint glass is perfect all-purpose glass for serving a variety of beverages to your guests.
\n- Holds up to 16 oz.
\n- Made from pressed glass for added durability
\n- Chip resistant rim
\n- 0
\n
",
"description_text": "This classic 16 oz. pint glass is perfect all-purpose glass for serving a variety of beverages to your guests.\nHolds up to 16 oz.\nMade from pressed glass for added durability\nChip resistant rim\n0",
"vendor": "Logo Brands",
"product_type": "Drinkware",
"created_at": "2026-03-04T02:51:14-06:00",
"updated_at": "2026-05-07T06:16:37-05:00",
"published_at": "2026-03-23T09:34:35-05:00",
"handle": "inter-miami-cf-2025-mls-cup-champions-16oz-pint-glass",
"tags": "16oz Pint Glass, Clear, G16P - 16ozPintGlass, MLS, MLS Playoffs, Needs Teams Metafield",
"variants": [
{
"variant_id": 51833848135911,
"title": "Default Title",
"price": "5.99",
"compare_at_price": null,
"sku": "C4715-G16P-MI25C",
"barcode": "197381052671",
"available": true,
"requires_shipping": true,
"weight": 0.87,
"weight_unit": "lb"
}
],
"image_urls": [
"https://cdn.shopify.com/s/files/1/0480/9470/7866/files/C4715-G16P-MI25C.jpg?v=1772636333",
"https://cdn.shopify.com/s/files/1/0480/9470/7866/files/C4715-G16P-MI25C_fullwarp.jpg?v=1772636334"
],
"primary_image": "https://cdn.shopify.com/s/files/1/0480/9470/7866/files/C4715-G16P-MI25C.jpg?v=1772636333",
"actor_id": "wqMXaOafeaHIAa9oa",
"run_id": "6tpHajZDrU3lNnJPg"
}
]
```
### Use Cases
- **Market Research and Analysis**: Gather data for market trends and consumer preferences.
- **Competitive Intelligence**: Monitor competitor products and pricing strategies.
- **Price Monitoring**: Track price changes over time for strategic pricing decisions.
- **Content Aggregation**: Compile product information for content creation or updates.
- **Academic Research**: Analyze product data for research projects.
- **Business Automation**: Integrate product data into business workflows for automation.
### Installation and Usage
1. Search for "Logobrands Product Url Parser Spider" in the Apify Store.
2. Click "Try for free" or "Run".
3. Configure input parameters.
4. Click "Start" to begin extraction.
5. Monitor progress in the log.
6. Export results in your preferred format (JSON, CSV, Excel).
### Output Format
The output is a structured JSON array containing detailed product information. Key fields include `product_id`, `title`, `description_raw`, `description_text`, `vendor`, `product_type`, `variants`, `image_urls`, and more. This format ensures easy integration and analysis.
### Support
For custom/simplified outputs or bug reports, please contact:
- Email: support@getdataforme.com
- Subject line: "custom support"
- Contact form:
We're here to help you get the most out of this Actor!
# Actor input Schema
## `Urls` (type: `array`):
The urls for the spider.
## Actor input object example
```json
{
"Urls": [
"https://logobrands.com/products/inter-miami-cf-2025-mls-cup-champions-16oz-pint-glass?_pos=1&_sid=4ab221859&_ss=r"
]
}
```
# 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 '' with your token
const client = new ApifyClient({
token: '',
});
// Prepare Actor input
const input = {};
// Run the Actor and wait for it to finish
const run = await client.actor("getdataforme/logobrands-product-url-parser-spider").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 '' with your token.
client = ApifyClient("")
# Prepare the Actor input
run_input = {}
# Run the Actor and wait for it to finish
run = client.actor("getdataforme/logobrands-product-url-parser-spider").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 getdataforme/logobrands-product-url-parser-spider --silent --output-dataset
```
## MCP server setup
```json
{
"mcpServers": {
"apify": {
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.apify.com/?tools=getdataforme/logobrands-product-url-parser-spider",
"--header",
"Authorization: Bearer "
]
}
}
}
```
## OpenAPI specification
```json
{
"openapi": "3.0.1",
"info": {
"title": "Logobrands Product Url Parser Spider",
"description": "The Logobrands Product Url Parser Spider extracts detailed product data from Logobrands URLs, ideal for businesses needing comprehensive information for analysis or integration....",
"version": "0.0",
"x-build-id": "3S2SVqxAP6D9R9fVq"
},
"servers": [
{
"url": "https://api.apify.com/v2"
}
],
"paths": {
"/acts/getdataforme~logobrands-product-url-parser-spider/run-sync-get-dataset-items": {
"post": {
"operationId": "run-sync-get-dataset-items-getdataforme-logobrands-product-url-parser-spider",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
},
"/acts/getdataforme~logobrands-product-url-parser-spider/runs": {
"post": {
"operationId": "runs-sync-getdataforme-logobrands-product-url-parser-spider",
"x-openai-isConsequential": false,
"summary": "Executes an Actor and returns information about the initiated run in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK",
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/runsResponseSchema"
}
}
}
}
}
}
},
"/acts/getdataforme~logobrands-product-url-parser-spider/run-sync": {
"post": {
"operationId": "run-sync-getdataforme-logobrands-product-url-parser-spider",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
}
},
"components": {
"schemas": {
"inputSchema": {
"type": "object",
"properties": {
"Urls": {
"title": "Urls",
"minItems": 1,
"type": "array",
"description": "The urls for the spider.",
"default": [
"https://logobrands.com/products/inter-miami-cf-2025-mls-cup-champions-16oz-pint-glass?_pos=1&_sid=4ab221859&_ss=r"
],
"items": {
"type": "string"
}
}
}
},
"runsResponseSchema": {
"type": "object",
"properties": {
"data": {
"type": "object",
"properties": {
"id": {
"type": "string"
},
"actId": {
"type": "string"
},
"userId": {
"type": "string"
},
"startedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"finishedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"status": {
"type": "string",
"example": "READY"
},
"meta": {
"type": "object",
"properties": {
"origin": {
"type": "string",
"example": "API"
},
"userAgent": {
"type": "string"
}
}
},
"stats": {
"type": "object",
"properties": {
"inputBodyLen": {
"type": "integer",
"example": 2000
},
"rebootCount": {
"type": "integer",
"example": 0
},
"restartCount": {
"type": "integer",
"example": 0
},
"resurrectCount": {
"type": "integer",
"example": 0
},
"computeUnits": {
"type": "integer",
"example": 0
}
}
},
"options": {
"type": "object",
"properties": {
"build": {
"type": "string",
"example": "latest"
},
"timeoutSecs": {
"type": "integer",
"example": 300
},
"memoryMbytes": {
"type": "integer",
"example": 1024
},
"diskMbytes": {
"type": "integer",
"example": 2048
}
}
},
"buildId": {
"type": "string"
},
"defaultKeyValueStoreId": {
"type": "string"
},
"defaultDatasetId": {
"type": "string"
},
"defaultRequestQueueId": {
"type": "string"
},
"buildNumber": {
"type": "string",
"example": "1.0.0"
},
"containerUrl": {
"type": "string"
},
"usage": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "integer",
"example": 1
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
},
"usageTotalUsd": {
"type": "number",
"example": 0.00005
},
"usageUsd": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "number",
"example": 0.00005
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
}
}
}
}
}
}
}
}
```