# Medium Articles Scraper (`ef12/medium-articles-scraper`) Actor

Scrape Medium articles by tag or author using the public JSON API. Get titles, subtitles, authors, claps, reading time, and tags.

- **URL**: https://apify.com/ef12/medium-articles-scraper.md
- **Developed by:** [Daniel Wilson](https://apify.com/ef12) (community)
- **Categories:** Developer tools
- **Stats:** 3 total users, 2 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

Pay per event

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

## Medium Articles Scraper

### What does Medium Articles Scraper do?

**Medium Articles Scraper** extracts articles from [Medium](https://medium.com) using Medium's public JSON API — no authentication required. Given a **tag** (e.g., "python", "ai", "programming") or an **author username**, it returns structured data for each article: title, URL, author, publication date, reading time, clap count, tags, and a preview snippet.

Unlike browser-based scrapers that load JavaScript and render pages, this Actor uses Medium's internal JSON feed endpoints. By sending an `Accept: application/json` header, Medium returns structured JSON instead of HTML, making the scraper faster, cheaper, and more reliable. Each run delivers clean, pre-formatted data straight to your Apify dataset where you can download it as JSON, CSV, HTML, or Excel — or pipe it into any API-connected tool.

### Why use Medium Articles Scraper?

Medium hosts millions of articles across technology, data science, design, business, self-improvement, and hundreds of other topics. Its recommendations engine surfaces high-quality content daily, but accessing that content at scale — for research, analysis, content curation, or monitoring — requires automation.

**Use cases:**

- **Content curation and newsletters** — Automatically collect trending articles from your niche (e.g., "ai", "blockchain", "startups") every day and build a curated newsletter or digest without manual copy-pasting.
- **Market and competitive intelligence** — Monitor what authors in your industry are publishing. Track article topics, publishing frequency, and engagement (claps) to identify content gaps and understand what resonates with readers.
- **Data science and NLP research** — Gather a corpus of articles by topic for sentiment analysis, topic modeling, trend detection, or training language models. The structured output (title, tags, preview text) gives you clean data to work with.
- **SEO and content strategy** — Analyze which article structures, titles, and topics perform best in your domain. Use the data to inform your own content strategy, identify high-engagement topics, and study successful authors.
- **Academic research** — Collect articles on specific subjects for literature reviews, citation analysis, or sociological studies of online publishing trends.
- **Personal knowledge base** — Archive articles from your favorite authors or tags for offline reading, reference, or personal study.
- **Social media and marketing** — Find trending content in your industry to share on social media, identify influencers (authors with high clap counts), and track content themes over time.

### How to use Medium Articles Scraper

Using this Actor is straightforward. Follow these steps:

1. **Open the Actor** in Apify Console. You'll see the Input tab with a form.
2. **Configure the input:**
   - Enter a **tag** such as "python", "machine-learning", or "design" to fetch trending or latest articles in that topic.
   - Optionally enter a **username** (without the @ symbol) to fetch articles by a specific author.
   - Choose **sort order**: "trending" (top recommended articles) or "newest" (latest published).
   - Set **max results** to limit the number of articles returned (up to 100).
3. **Run the Actor**. The scraper will call Medium's JSON API, parse the response, and push each article as a dataset item.
4. **Download results** from the dataset tab. You can export as JSON, CSV, HTML, or Excel.

You can also run it programmatically via Apify API — useful for scheduled runs or integration into larger data pipelines.

### Input

The Actor accepts the following input parameters. Configure them in the **Input** tab before running.

| Field | Type | Default | Description |
| ------- | ------ | --------- | ------------- |
| `tag` | string | "programming" | Medium tag to search (e.g., "python", "ai", "javascript"). Optional if username is provided. |
| `username` | string | — | Medium username to fetch articles by a specific author (without @). Optional if tag is provided. |
| `sort` | string | "trending" | Sort order: "trending" (recommended) or "newest" (latest). |
| `max_results` | integer | 25 | Maximum articles to return (1–100). |

### Output

Each article is stored as an item in the default dataset. Here's an example of a single result:

```json
{
  "title": "10 Python Libraries Every Developer Should Know",
  "url": "https://medium.com/@pythoncoder/10-python-libraries-every-developer-should-know-abc123def456",
  "subtitle": "A curated list of essential Python libraries for 2025",
  "author": "Python Coder",
  "author_url": "https://medium.com/@pythoncoder",
  "published_at": "2025-06-15T08:30:00+00:00",
  "reading_time_minutes": 8,
  "claps": 1420,
  "tags": ["python", "programming", "data-science"],
  "preview_text": "A curated list of essential Python libraries for 2025"
}
```

You can download the dataset in various formats such as JSON, HTML, CSV, or Excel from the **Dataset** tab after each run.

### Data table

| Field | Type | Description |
| ------- | ------ | ------------- |
| `title` | string | Article title |
| `url` | string | Full medium.com URL |
| `subtitle` | string | null | Subtitle or brief description |
| `author` | string | Author's display name |
| `author_url` | string | Link to author's Medium profile |
| `published_at` | string | ISO 8601 publication timestamp |
| `reading_time_minutes` | integer | Estimated reading time in minutes |
| `claps` | integer | null | Number of claps (likes) |
| `tags` | array of strings | Article tags/categories |
| `preview_text` | string | First 200 characters of the subtitle |

### Pricing / Cost estimation

This Actor uses **Pay Per Event (PPE)** pricing:

- **First 10 results per run are free.** No charge.
- **Beyond 10 results, each additional result costs $0.003** (charged via `apify-actor-start` and `result` events).
- **Starting a run costs $0.00005** (apify-actor-start event).

A typical run with 25 articles would cost approximately $0.00005 (start) + 15 × $0.003 (15 chargeable results) = **$0.045**. For 100 articles: $0.00005 + 90 × $0.003 = **$0.27**.

### Tips and Advanced options

- **Use specific tags** for better results. "machine-learning" returns more focused articles than "ML" or "AI".
- **Keep max\_results at 25 or lower** for quick exploratory runs, then increase for production batch runs.
- **Combine with other Apify Actors** — pipe the output dataset into an NLP Actor for text analysis, or into a Google Sheets integration for live dashboards.
- **Schedule regular runs** via Apify Console to monitor trending content in your niche daily.

### FAQ, disclaimers, and support

**Q: Is authentication required?**\
No. This Actor uses Medium's public JSON endpoints which do not require API keys or login.

**Q: Can I scrape paywalled article content?**\
This Actor extracts metadata only — title, URL, author, claps, etc. It does not bypass paywalls or extract full article text behind the paywall.

**Q: Is this against Medium's Terms of Service?**\
This Actor accesses publicly available data from Medium's public feeds. You should review Medium's Terms of Service and use the tool responsibly. Do not republish scraped content without permission.

**Q: Why use JSON API instead of a browser?**\
Medium returns JSON data when you set `Accept: application/json` on certain URLs. This is significantly faster and cheaper than running a full browser (Playwright/Puppeteer) — no JavaScript rendering overhead, no memory spikes, and no complex selector maintenance.

**Known limitations:**

- Medium may rate-limit requests from certain IP ranges. Running on Apify's platform with proxy rotation provides the best reliability.
- The JSON API endpoints are not officially documented and may change. This Actor is maintained to adapt to any changes.

**Need help or have feedback?** Open an issue on the [GitHub repository](https://github.com/apify/medium-articles-scraper) or contact the author. Custom scrapers, integrations, and enterprise solutions are also available on request.

# Actor input Schema

## `tag` (type: `string`):

Medium tag to fetch articles for (e.g., "python", "ai", "programming"). Optional if username is provided.

## `username` (type: `string`):

Medium username to fetch articles from a specific author (without @). Optional if tag is provided.

## `sort` (type: `string`):

Sort order — trending (top recommendations) or newest (latest articles).

## `max_results` (type: `integer`):

Maximum number of articles to return (max 100).

## Actor input object example

```json
{
  "tag": "python",
  "sort": "trending",
  "max_results": 25
}
```

# Actor output Schema

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

No description

# 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 = {
    "tag": "python",
    "username": ""
};

// Run the Actor and wait for it to finish
const run = await client.actor("ef12/medium-articles-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 = {
    "tag": "python",
    "username": "",
}

# Run the Actor and wait for it to finish
run = client.actor("ef12/medium-articles-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 '{
  "tag": "python",
  "username": ""
}' |
apify call ef12/medium-articles-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=ef12/medium-articles-scraper",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/3GBtthJGm9N5OMINi/builds/2b8giE1KBMZeTHgNo/openapi.json