# Medium Scraper (`mina_safwat/medium-scraper`) Actor

Scrapes Medium articles from tag pages, author profiles, publications and article links: title, subtitle, author, publication, date, reading time, claps, responses, tags and member-only flag, with optional full text of free articles.

- **URL**: https://apify.com/mina_safwat/medium-scraper.md
- **Developed by:** [Mina](https://apify.com/mina_safwat) (community)
- **Categories:** News, For creators, Marketing
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

$3.00 / 1,000 articles

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

### What does Medium Scraper do?

**Medium Scraper** collects **articles from [Medium](https://medium.com)**: from **tag pages, author profiles, publications and single article links**. For every article you get the **title, subtitle, author, publication, publish date, reading time, claps, responses, tags, member-only flag, cover image and link**, and optionally the **full text of free articles**. No Medium account is needed.

Try it with the prefilled tag: open the Actor, click **Start**, and 20 Python articles arrive in a few seconds. Because it runs on the Apify platform, you also get API access, scheduled runs, integrations (Google Sheets, Make, Zapier, Slack, webhooks) and run monitoring.

### Why scrape Medium?

- **Content research.** See what gets written and clapped for on any topic, which writers lead it, and which publications carry them.
- **Trend tracking.** Run a tag on a schedule with its `/latest` link to follow new articles as they appear.
- **Influencer and writer discovery.** Rank authors in a niche by claps and responses, and follow their output over time.
- **Publication monitoring.** Track everything a publication releases, its reading times and how readers respond.
- **Datasets for analysis and AI.** Full text of free articles, with clean metadata, ready for NLP, summarization or search indexes.

### How to scrape Medium articles

1. Open a tag, author, publication or article on Medium and copy the link from your browser's address bar. Or just type a tag word, such as `python` or `machine learning`.
2. Paste it into **Medium links or tags**, one per line. Mix tags, authors, publications and articles freely.
3. Set **Max articles per link** and, if you want the article bodies, turn on **Include full article text**.
4. Click **Start**, then download the results when the run finishes.

### Input

Everything is set on the Input tab. In JSON, the input looks like this:

```json
{
    "start_urls": [
        "https://medium.com/tag/python",
        "https://medium.com/tag/javascript/latest",
        "machine learning",
        "https://medium.com/@karpathy",
        "https://medium.com/data-science-collective",
        "levelup.gitconnected.com",
        "https://medium.com/@piotr.kalanski/time-series-feature-engineering-why-positional-lags-silently-break-on-sparse-data-416c540b07c8"
    ],
    "max_articles_per_input": 50,
    "include_full_text": false
}
```

| Field | What it does |
|---|---|
| `start_urls` | Medium links or tag words, one per line. **Tags:** `https://medium.com/tag/python` lists articles in Medium's recommended order; `/tag/python/latest` lists the newest first; a plain word such as `python`, `machine learning` or `node.js` is read as a tag. **Authors:** `https://medium.com/@karpathy`, `karpathy.medium.com` or `@karpathy`. **Publications:** `https://medium.com/data-science-collective`, or the publication's own domain such as `levelup.gitconnected.com`. **Articles:** any article link, including `medium.com/p/<id>` and links on a publication's own domain. Links work without `https://`, and API callers can also send `{"url": "..."}` objects. |
| `max_articles_per_input` | Stops after this many articles for each link or tag, in the order Medium lists them. Default: 50. |
| `include_full_text` | Adds the full text and word count of every free article. Member-only articles keep all their other details, with no text. Default: off. |

### Output

Each article becomes one row. Here is a real example from the run with full text on, with the text shortened:

```json
{
    "id": "a64152b37c35",
    "url": "https://karpathy.medium.com/software-2-0-a64152b37c35",
    "title": "Software 2.0",
    "subtitle": "I sometimes see people refer to neural networks as just “another tool in your machine learning toolbox”. They have some pros and cons, they…",
    "author_name": "Andrej Karpathy",
    "author_username": "karpathy",
    "author_url": "https://medium.com/@karpathy",
    "publication_name": null,
    "publication_url": null,
    "published_at": "2017-11-11T22:18:53+00:00",
    "updated_at": "2021-03-13T18:18:43+00:00",
    "reading_time_minutes": 9,
    "claps": 61029,
    "responses": 194,
    "tags": ["machine-learning", "artificial-intelligence", "programming", "software-development", "future"],
    "is_member_only": false,
    "image": "https://miro.medium.com/v2/resize:fit:1200/1*CHcu2L0NmAZwCpQgmS1ByA.jpeg",
    "language": "en",
    "text": "I sometimes see people refer to neural networks as just “another tool in your machine learning toolbox”. They have some pros and cons, they work here or there, …",
    "word_count": 2127,
    "input": "https://medium.com/@karpathy",
    "position": 1
}
```

You can download the dataset in various formats such as JSON, HTML, CSV, or Excel. The Output tab has two views: **Articles** (the main columns) and **Full details** (every field, including the text).

### Data fields

| Field | Description |
|---|---|
| `id` | Medium's ID of the article. |
| `url` | Link to the article. |
| `title` | Article title. |
| `subtitle` | The subtitle as Medium shows it in article previews. When the author set none, Medium uses the article's opening line instead. |
| `author_name`, `author_username`, `author_url` | The writer's name, Medium username and profile link. |
| `publication_name`, `publication_url` | The publication the article appeared in; empty for articles published on the author's own profile. |
| `published_at` | When the article was first published, in UTC (ISO 8601). |
| `updated_at` | When the author last published a change to it, in UTC; the same as `published_at` if never edited. |
| `reading_time_minutes` | Reading time as Medium shows it ("9 min read"). |
| `claps` | Number of claps. |
| `responses` | Number of responses (comments). |
| `tags` | The article's tags, as they appear in tag links (`machine-learning`). |
| `is_member_only` | `true` for member-only (paywalled) articles. |
| `image` | The article's cover image; empty when it has none. |
| `language` | Language Medium detected for the article, as a code such as `en`. |
| `text` | Full text of a free article, as plain paragraphs. Only with **Include full article text**; empty for member-only articles. |
| `word_count` | Number of words in `text`. Only with **Include full article text**. |
| `input` | The link or tag that led to this article. |
| `position` | The article's place in the list Medium showed for that input (1 = first). |

### How much does it cost to scrape Medium?

The Actor uses **pay-per-event** pricing: you pay **per article saved**, and the exact price is on the **Pricing** tab. The full text of free articles is included at no extra charge, and there is no proxy cost to add.

It is fast: a test run saved 1,227 articles from five tags, authors and publications in 25 seconds, and the prefilled run takes about 4 seconds. Links that return nothing are never charged as results, and if you set a maximum cost for a run, the Actor stops as soon as it is reached. Apify's free plan includes monthly credit you can use to try it.

### Tips for scraping Medium

- **Use `/latest` for fresh articles and for depth.** A tag's own page lists about 500 recommended articles; `https://medium.com/tag/<tag>/latest` lists the tag's articles newest first and goes much further back.
- **Schedule a tag's `/latest` link** with a small maximum to monitor a topic every day.
- **Turn on full text only when you need it.** The rows are the same otherwise, and runs without text return smaller datasets.
- **Paste several tags at once.** An article found under two of your links is saved only once, under the first link that reached it, so overlapping tags don't cost twice.
- **Publications list articles in the order they were added to the publication**, which is usually, but not always, publish order.

### FAQ, disclaimers and support

**Does it unlock member-only articles?** **No.** The Actor never bypasses Medium's paywall and uses no account or cookies. Member-only articles are saved with everything Medium shows to readers who are not logged in (title, subtitle, author, dates, reading time, claps, responses, tags and image), marked `is_member_only: true`, and without text.

**What links are not supported?** Search pages, reading lists, tag pages inside a publication, tag archives by date and Medium app share links (`link.medium.com/...`: open one and paste the article address from your browser instead). They are listed in the **FAILED_INPUTS** record with a suggestion of what to paste instead.

**What happens to links that return nothing?** Unknown tags, authors and publications, deleted articles, authors who have published nothing, and links that are not Medium links are not saved as rows, so you are not charged for them. Each one is listed with its reason in the **FAILED_INPUTS** record of the run's key-value store, and the status message gives the counts. A run is marked failed only when nothing was saved because Medium could not be reached for every input.

**Do I need a Medium account or a proxy?** No. The Actor reads only what Medium shows to readers who are not logged in, and chooses its own connection: it retries through Apify Proxy on its own if Medium refuses.

**Is it legal to scrape Medium?** The Actor collects only articles that anyone can read on Medium without an account. Articles carry **authors' public names and usernames, which are personal data** under rules such as the GDPR and CCPA: only collect what you need, store it securely, have a lawful reason to process it, and don't use it to spam or profile people. Article texts are protected by copyright, so don't republish them without permission. Medium's terms restrict automated access, so you are responsible for how you use the data. If you are unsure, ask a lawyer.

**Found a problem or need a custom solution?** Open an issue on the **Issues** tab and we will look into it. Custom scrapers and content data feeds are available on request.

# Actor input Schema

## `start_urls` (type: `array`):

One per line: a tag page (https://medium.com/tag/python, or /tag/python/latest for the newest first), or simply a tag word such as python or machine learning; an author (https://medium.com/@karpathy, karpathy.medium.com or @karpathy); a publication (https://medium.com/data-science-collective, or its own domain such as levelup.gitconnected.com); or a single article link. Links without https:// work too. Entries that cannot be read are listed in the FAILED_INPUTS record.

## `max_articles_per_input` (type: `integer`):

Stops after this many articles for each link or tag, in the order Medium lists them. A tag page's recommended list holds about 500 articles; use the tag's /latest link to go further back.

## `include_full_text` (type: `boolean`):

Adds the full text and word count of every free article. Member-only articles are never unlocked: they keep their title, subtitle and other details, with no text.

## Actor input object example

```json
{
  "start_urls": [
    "https://medium.com/tag/python"
  ],
  "max_articles_per_input": 20,
  "include_full_text": false
}
```

# Actor output Schema

## `dataset` (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 = {
    "start_urls": [
        "https://medium.com/tag/python"
    ],
    "max_articles_per_input": 20
};

// Run the Actor and wait for it to finish
const run = await client.actor("mina_safwat/medium-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 = {
    "start_urls": ["https://medium.com/tag/python"],
    "max_articles_per_input": 20,
}

# Run the Actor and wait for it to finish
run = client.actor("mina_safwat/medium-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 '{
  "start_urls": [
    "https://medium.com/tag/python"
  ],
  "max_articles_per_input": 20
}' |
apify call mina_safwat/medium-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,mina_safwat/medium-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/sfzohOWCciwj4Yhk1/builds/lQcMIJ1ocRXthhVNZ/openapi.json