# Epicshare Discovery Extractor (`getdataforme/epicshare-discovery-extractor`) Actor

Epicshare Discovery Spider is a web scraping tool designed for extracting high-quality data from Epicshare's CMS....

- **URL**: https://apify.com/getdataforme/epicshare-discovery-extractor.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, 0 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 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

***

## Epicshare Discovery Spider

### Introduction

Epicshare Discovery Spider is a powerful web scraping tool designed to extract high-quality data from Epicshare's CMS. It provides reliable and efficient data extraction capabilities, enabling users to gather valuable insights for various applications.

### Features

- **Comprehensive Data Extraction**: Extracts detailed information including news titles, descriptions, images, authors, and publication dates.
- **High-Quality Data**: Ensures data accuracy and reliability with structured output formats.
- **Efficient Performance**: Optimized for speed and efficiency in data retrieval processes.
- **Customizable Parameters**: Allows users to specify input parameters for tailored data extraction.
- **Versatile Applications**: Supports a wide range of use cases from market research to academic studies.

### Input Parameters Table

| Parameter   | Type     | Required | Description                                                                 | Example                  |
|-------------|----------|----------|-----------------------------------------------------------------------------|--------------------------|
| `maxItems`  | Integer  | No       | Maximum number of items to extract.                                         | `10`                     |
| `startFrom` | String   | No       | Starting point for extraction, can be a specific date or page number.        | `"2023-01-01"`           |
| `endAt`     | String   | No       | Ending point for extraction, can be a specific date or page number.          | `"2023-12-31"`           |

### Example Usage

```json
{
  "maxItems": 10,
  "startFrom": "2023-01-01",
  "endAt": "2023-12-31"
}
```

**Example Output:**

```json
[
  {
    "Published Date": "2024-05-28T07:00:00",
    "Category": "Epic Talks",
    "News Title": "Q: How can we help patients better understand and manage medical bills? ~_**A:** Offer conversational AI billing support in MyChart._~",
    "News Details": "Patients can get answers to their billing questions—such as why they owe the amount that they do—and set up payment plans using Emmie, MyChart’s AI assistant. Emmie reduces staff workload while improving patient access to financial support. One organization saw a 48% reduction in billing customer service messages and 2,000+ conversations in the first few weeks after going live. [1]To learn more…Your team can refer to the Emmie Setup and Support Guide on the UserWeb or review the Artificial Intelligence roadmap to see what’s available and where we’re headed next. They can also reach out to the EpicShare team , and we will connect them with the experts at Epic.[1] Customer-reported outcome",
    "Image": "https://epicshare.blob.core.windows.net/cms-uploads/media/emmie-billing-assistant-853x480.jpg",
    "actor_id": "26zziCMX7ibwcqQJY",
    "run_id": "0AdocOnPQQfK7r3ss"
  }
]
```

### Use Cases

- **Market Research and Analysis**: Gather insights from Epicshare's content for market trends.
- **Competitive Intelligence**: Monitor competitor activities and strategies through their published content.
- **Price Monitoring**: Track pricing information and updates in the healthcare sector.
- **Content Aggregation**: Compile news articles and announcements for analysis or reporting.
- **Academic Research**: Use data for studies related to healthcare communication and technology.
- **Business Automation**: Automate data collection processes for operational efficiency.

### Installation and Usage

1. Search for "Epicshare Discovery Spider" in the Apify Store.
2. Click "Try for free" or "Run".
3. Configure input parameters as needed.
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 data is structured with key fields such as `Published Date`, `Category`, `News Title`, `News Details`, `Image`, `actor_id`, and `run_id`. Each entry provides comprehensive information about the extracted content.

### Support

For custom/simplified outputs or bug reports, please contact:

- Email: support@getdataforme.com
- Subject line: "custom support"
- Contact form: [Contact Us](https://getdataforme.com/contact/)

We're here to help you get the most out of this Actor!

***

# Actor input Schema

## `Urls` (type: `array`):

The urls for the spider.

## `item_limit` (type: `integer`):

Maximum items to scrape per actor run. Set to 0 for no limit.

## Actor input object example

```json
{
  "Urls": [
    "https://www.epicshare.org/search?tags=artificial-intelligence&searchText=education"
  ],
  "item_limit": 10
}
```

# 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("getdataforme/epicshare-discovery-extractor").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("getdataforme/epicshare-discovery-extractor").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/epicshare-discovery-extractor --silent --output-dataset

```

## MCP server setup

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

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/B11mSUMg4eaElzksa/builds/64PgpJSdHSOwUydds/openapi.json