# Medium Scraper: Articles, Claps & Full Text (`scrapemint/medium-scraper`) Actor

Medium articles from tags, keyword search, authors, publications or URLs: title, author and followers, publication, claps, responses, reading time, word count, tags, dates and optionally the full text. Hot, newest or top feeds. $0.002 per article.

- **URL**: https://apify.com/scrapemint/medium-scraper.md
- **Developed by:** [Ken M](https://apify.com/scrapemint) (community)
- **Categories:** Social media, News
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $2.00 / 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

## Medium Scraper: Articles, Claps & Full Text

Articles from **Medium** as clean rows: title, subtitle, **author and their follower count**, **publication and its follower count**, published and updated dates, **claps, responses, reading time and word count**, tags, cover image and, if you want it, the **article text** with headings, lists and code blocks.

Read from any mix of sources:

- **Tags** (topics) with the feed you choose: recommended, newest, or top this week, month, year or all time
- **Keyword search**
- **Authors** by username or profile URL
- **Publications** by slug, URL or custom domain
- **Article URLs**

No Medium account, no API key, no proxy. $0.002 per article, no start fee.

### What you get per article

- `articleId`, `url`, `title`, `subtitle`
- `authorName`, `authorUsername`, `authorUrl`, `authorFollowers`, `authorBio`
- `publicationName`, `publicationSlug`, `publicationUrl`, `publicationFollowers`
- `publishedAt`, `updatedAt`
- `claps`, `responses`, `readingTimeMinutes`, `wordCount`, `isMembersOnly`, `tags`, `imageUrl`

With **Article text** on: `text` and `contentIsPreview`.

### Example input

The newest Python articles and a keyword search, with text:

```json
{
  "tags": ["python"],
  "tagSort": "new",
  "searchQueries": ["vector database"],
  "includeContent": true
}
```

Top articles of the month in three topics:

```json
{
  "tags": ["artificial-intelligence", "startup", "productivity"],
  "tagSort": "top_month",
  "maxItemsPerSource": 200
}
```

Everything an author or publication has published:

```json
{
  "authors": ["https://karpathy.medium.com/"],
  "publications": ["data-science-collective"]
}
```

### Example output

```json
{
  "articleId": "6ed2048c7167",
  "url": "https://diogo-ribeiro-1975.medium.com/game-and-auction-theory-for-data-scientists-6ed2048c7167",
  "title": "Game and Auction Theory for Data Scientists",
  "subtitle": "Part 1 of 6: Payoffs, Best Responses and Nash Equilibrium ...",
  "authorName": "Diogo Ribeiro",
  "authorUsername": "diogo-ribeiro-1975",
  "authorFollowers": 331,
  "publishedAt": "2026-10-11T15:51:01.503Z",
  "claps": 0,
  "responses": 0,
  "readingTimeMinutes": 17.1,
  "wordCount": 4348,
  "isMembersOnly": true,
  "tags": ["game-theory", "data-science", "pricing", "python", "economics"],
  "imageUrl": "https://miro.medium.com/v2/resize:fit:1200/1*AlyaWl7bXsg2jzUHBPH2uw.png",
  "source": "tag python (new)",
  "text": "## Game and Auction Theory for Data Scientists\n\n### Part 1 of 6 ...",
  "contentIsPreview": true
}
```

### Uses

- **Content and SEO teams:** what performs in your topic, by claps, responses and reading time
- **Influencer and author research:** writers in a niche with their follower counts and bios
- **Trend tracking:** the newest articles in a tag on a schedule
- **AI and NLP datasets:** article text with structure kept (headings, lists, code)
- **Brand monitoring:** keyword search for your product or company

### Pricing

- **$0.002** per article
- **$0.004** per article with **Article text** on (charged instead of the $0.002, not on top)
- No start fee. A source with no articles is free.

### Notes

- **Members-only articles:** Medium shows a logged-out reader only their opening paragraphs, so `text` is a preview and `contentIsPreview` is `true`. `wordCount` and `readingTimeMinutes` are for the whole article.
- An article that appears in two of your sources is kept once.
- Publications that moved off Medium (for example Towards Data Science in 2025) are no longer on Medium's API.

# Actor input Schema

## `tags` (type: `array`):

Medium tags (topics), e.g. artificial-intelligence, python, startup, productivity, or medium.com/tag/... URLs.

## `tagSort` (type: `string`):

Which feed of each tag to read. Newest with a schedule collects new articles as they are published.

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

Medium article search, e.g. vector database, remote work, ozempic.

## `authors` (type: `array`):

Usernames, @usernames or profile URLs, e.g. karpathy, medium.com/@username, username.medium.com. Returns their articles, newest first.

## `publications` (type: `array`):

Publication slugs, URLs or custom domains, e.g. data-science-collective, medium.com/better-programming, towardsdatascience.com.

## `articleUrls` (type: `array`):

Individual Medium articles, on medium.com or a publication's own domain.

## `includeContent` (type: `boolean`):

Adds each article's text with headings, lists and code blocks. Members-only articles give only their opening paragraphs. Costs $0.004 per article instead of $0.002.

## `maxItemsPerSource` (type: `integer`):

Stop each tag, search, author or publication after this many articles.

## Actor input object example

```json
{
  "tags": [
    "artificial-intelligence"
  ],
  "tagSort": "hot",
  "searchQueries": [],
  "authors": [],
  "publications": [],
  "articleUrls": [],
  "includeContent": false,
  "maxItemsPerSource": 100
}
```

# Actor output Schema

## `articles` (type: `string`):

Title, subtitle, author and followers, publication, dates, claps, responses, reading time, word count, tags, image, and optionally the text.

## `summary` (type: `string`):

Articles per source and any sources that failed.

# 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 = {
    "tags": [
        "artificial-intelligence"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("scrapemint/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 = { "tags": ["artificial-intelligence"] }

# Run the Actor and wait for it to finish
run = client.actor("scrapemint/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 '{
  "tags": [
    "artificial-intelligence"
  ]
}' |
apify call scrapemint/medium-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,scrapemint/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/BG79gcJglYbJkKzn3/builds/ItWrBaE6xp9wFruFE/openapi.json