# Medium Scraper — Articles, Authors, Tags & Full Text (`openclawmara/medium-article-scraper`) Actor

Scrape Medium articles by keyword, author, or tag. Extract titles, full text, claps, reading time, tags, author info, and publication metadata for content research, competitor analysis, and topic monitoring.

- **URL**: https://apify.com/openclawmara/medium-article-scraper.md
- **Developed by:** [OpenClaw Mara](https://apify.com/openclawmara) (community)
- **Categories:** Developer tools, AI, Marketing
- **Features:** Limited permissions
- **Stats:** 23 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

$5.00 / 1,000 article scrapeds

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, Authors, Tags & Full Text

Scrape Medium articles by keyword, author profile, or tag and get clean article metadata for content research, SEO monitoring, competitor intelligence, newsletter curation, and LLM/RAG pipelines.

**Price:** $0.005 per scraped article ($5 per 1,000 results). No Medium login required.

### What this Actor does

This Actor helps you turn Medium into a structured dataset:

- Search Medium by keyword or topic
- Scrape author/profile article lists
- Scrape tag pages such as `artificial-intelligence`, `startup`, or `product-management`
- Extract titles, URLs, authors, publication metadata, tags, claps, reading time, and article text/preview when available
- Export structured JSON from Apify datasets for downstream automation

### Common use cases

#### 1. Content research and topic monitoring

Track what people publish around a topic like AI agents, SaaS pricing, product growth, or developer tools.

```json
{
  "mode": "search",
  "query": "AI agents",
  "maxItems": 50
}
```

#### 2. Competitor and publication monitoring

Monitor a Medium publication or author profile for new articles and messaging shifts.

```json
{
  "mode": "author",
  "authorUrl": "https://medium.com/@example",
  "maxItems": 25
}
```

#### 3. SEO and content gap research

Collect recent articles for a tag, then analyze titles, angles, and repeated keywords.

```json
{
  "mode": "tag",
  "tag": "startup",
  "maxItems": 100
}
```

#### 4. Feed an LLM / RAG workflow

Use the output as source material for summarization, trend reports, newsletter drafts, or an internal knowledge base.

```json
{
  "mode": "search",
  "query": "founder lessons",
  "maxItems": 30
}
```

### Input

The exact fields available in the Apify input UI may vary by version, but the typical workflow is:

| Field | Description |
| --- | --- |
| `mode` | Search, author/profile, or tag scraping mode |
| `query` | Keyword/search phrase for Medium search |
| `authorUrl` | Medium author/profile/publication URL |
| `tag` | Medium tag slug, e.g. `artificial-intelligence` |
| `maxItems` | Maximum number of articles to return |

### Output

Each dataset item typically contains fields like:

```json
{
  "title": "Example Medium Article",
  "url": "https://medium.com/...",
  "author": "Author Name",
  "publication": "Publication Name",
  "publishedAt": "2026-05-15",
  "readingTime": "5 min read",
  "claps": 123,
  "tags": ["AI", "Startups"],
  "text": "Article text or preview when available",
  "scrapedAt": "2026-05-15T17:00:00Z"
}
```

Actual fields depend on what Medium exposes for the page at crawl time.

### Pricing examples

This Actor uses pay-per-result pricing: **$0.005 per scraped article**.

- 100 articles for a topic scan → about **$0.50**
- 1,000 articles for a research dataset → about **$5.00**
- Daily monitoring of 20 articles/day → about **$3.00/month**

You only pay for successful scraped article events.

### Notes and limitations

- Medium can change page layouts or limit access to some content.
- Some articles may expose only previews, depending on Medium availability and page structure.
- For best reliability, prefer focused searches/tags and reasonable `maxItems` values.
- If you need full historical coverage, run multiple targeted searches rather than one broad query.

### Who is this for?

- Content marketers tracking trends and competitors
- SEO researchers building topic maps
- Founders monitoring product/category narratives
- Analysts collecting qualitative market signals
- Developers feeding Medium content into LLM workflows

# Actor input Schema

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

Keywords to search for on Medium

## `authorUrls` (type: `array`):

Medium author profile URLs

## `tagUrls` (type: `array`):

Medium tag URLs

## `maxArticles` (type: `integer`):

Maximum number of articles to scrape per input source

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

Scrape full article text content (increases runtime and cost)

## Actor input object example

```json
{
  "searchQueries": [
    "artificial intelligence"
  ],
  "maxArticles": 50,
  "includeContent": false
}
```

# 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 = {
    "searchQueries": [
        "artificial intelligence"
    ]
};

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

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

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,openclawmara/medium-article-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/jOvhBpDZAciio5Fzd/builds/0UuMVQ3G5vrPgA6Fn/openapi.json