# Medium Scraper - Articles by Tag, Author & Publication (`scrapesage/medium-scraper`) Actor

Scrape Medium articles by tag, author (@handle) or publication via public RSS. Get title, author, date, tags, subtitle, full content and reading time. No login, no key. Export JSON, CSV, Excel.

- **URL**: https://apify.com/scrapesage/medium-scraper.md
- **Developed by:** [Scrape Sage](https://apify.com/scrapesage) (community)
- **Categories:** News, AI, Automation
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $1.65 / 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.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#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 Scraper - Articles by Tag, Author & Publication

Scrape **Medium** articles by **tag**, **author** (`@handle`) or **publication**, straight from Medium's public RSS feeds. Get the title, author, publish date, tags, subtitle, **full article content** and reading time - as clean JSON, CSV or Excel. No login, no API key, no browser.

> **Why this actor exists (demand):** the "Medium scraper" niche draws **~256 monthly users** on Apify Store across a fragmented field; the leader holds ~217 with **zero reviews**. This actor is a clean, reliable RSS-based reader that returns full content and metadata for content monitoring, research, newsletters and **RAG / LLM ingestion**.

### What you can scrape

- **By tag** - the latest articles for any topic, e.g. `artificial-intelligence`, `python`, `startup`.
- **By author** - any Medium `@handle`, e.g. `@dhh`.
- **By publication** - any publication, e.g. `better-programming`.
- **By URL** - paste any `medium.com` tag / author / publication URL and it is auto-detected.

Medium serves the **10 most recent** articles per feed. Author and publication feeds include the **full article body** (clean text + HTML, word count, reading time); tag feeds are metadata-only (title, author, tags, date, URL) - that's Medium's RSS design, and the actor documents which fields that affects.

### Example input

Latest AI articles by topic:

```json
{ "sourceType": "tag", "sources": ["artificial-intelligence", "machine-learning"], "maxResults": 20 }
```

Full articles from specific authors:

```json
{ "sourceType": "user", "sources": ["@dhh", "@benthompson"], "includeContent": true }
```

From a publication, or by URL:

```json
{ "sources": ["better-programming", "https://medium.com/tag/python"] }
```

You can also import a list of tags / authors / publications / URLs from a pasted block or a linked `.txt`/`.csv`/Google Sheet via **Import sources from a file**.

### Output fields

`title`, `url`, `author`, `publishedAt`, `tags`, `subtitle`, `content` (clean text), `contentHtml`, `wordCount`, `readingTimeMin`, `sourceType`, `source`, `guid`, `scrapedAt`.

Every run finishes with a clear status message; empty runs never crash and never bill.

### Use with AI assistants (MCP)

This actor is available through the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp), so assistants like Claude can pull "the latest 20 articles tagged machine-learning" or "@dhh's recent posts" as structured, LLM-ready data.

### Agent-ready: autonomous payments (x402 & Skyfire)

This actor is **agent-ready** - AI agents can discover it, run it, and **pay for it autonomously**, with no Apify account and no human in the loop. It uses [pay-per-event](https://docs.apify.com/platform/actors/publishing/monetize/pay-per-event) pricing and [limited permissions](https://docs.apify.com/platform/actors/development/permissions), so it qualifies for Apify's agentic-payment standards:

- **[x402](https://docs.apify.com/platform/integrations/x402)** - an open, HTTP-native payment protocol. Agents pay per run in USDC on the Base network directly through the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp) - no account, no API key.
- **[Skyfire](https://docs.apify.com/platform/integrations/skyfire)** - agent-to-service payments for fully autonomous AI-agent workflows.

Building an AI agent, MCP tool, or autonomous content pipeline? This scraper is ready to plug in and pay as it goes.

### Pricing

Pay-per-event, tiered by volume: **$0.003** per article at the free tier, dropping to **$0.00075** at the top tier. You pay only for articles actually returned.

### FAQ

**Where does the data come from?** Medium's own public RSS feeds (`medium.com/feed/...`). No private API, no login.

**Why only 10 articles per source?** That is the number Medium publishes in each RSS feed. Add more tags / authors / publications to get more articles per run.

**Do tag feeds include the article text?** No - Medium omits the body from tag feeds. Use an author or publication source to get full content.

***

*This is an independent scraper for publicly available RSS data. It is not affiliated with, endorsed by, or sponsored by Medium. "Medium" is a trademark of A Medium Corporation, used here for descriptive purposes only. Use the data in compliance with Medium's terms and applicable law.*

# Actor input Schema

## `sourceType` (type: `string`):

How to interpret each plain-text entry in Sources. <b>Tag</b> = a topic (e.g. <code>artificial-intelligence</code>). <b>Author</b> = a Medium @handle. <b>Publication</b> = a publication slug (e.g. <code>better-programming</code>). Full Medium URLs are auto-detected regardless of this setting.

## `sources` (type: `array`):

Tags, @authors, publication slugs, or full Medium URLs. Examples: <code>artificial-intelligence</code>, <code>@dhh</code>, <code>better-programming</code>, <code>https://medium.com/tag/python</code>. Medium serves the 10 latest articles per feed.

## `sourcesFromFile` (type: `string`):

Paste a block of tags / @authors / publications / Medium URLs (one per line), or a single link to a .txt/.csv file or Google Sheet of them.

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

Include the full article body (clean text + HTML) and word count / reading time. Available on author and publication feeds; Medium's tag feeds are metadata-only (title, author, tags, date, URL).

## `maxResults` (type: `integer`):

Maximum number of articles to return across all sources.

## `proxyConfiguration` (type: `object`):

Proxies to use. Medium RSS feeds are public, so the default Apify datacenter proxy is plenty.

## Actor input object example

```json
{
  "sourceType": "tag",
  "sources": [
    "artificial-intelligence",
    "@dhh"
  ],
  "includeContent": true,
  "maxResults": 50,
  "proxyConfiguration": {
    "useApifyProxy": true
  }
}
```

# Actor output Schema

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

All scraped Medium article records as JSON items in the default dataset.

# 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 = {
    "sourceType": "tag",
    "sources": [
        "artificial-intelligence",
        "@dhh"
    ],
    "maxResults": 50,
    "proxyConfiguration": {
        "useApifyProxy": true
    }
};

// Run the Actor and wait for it to finish
const run = await client.actor("scrapesage/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 = {
    "sourceType": "tag",
    "sources": [
        "artificial-intelligence",
        "@dhh",
    ],
    "maxResults": 50,
    "proxyConfiguration": { "useApifyProxy": True },
}

# Run the Actor and wait for it to finish
run = client.actor("scrapesage/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 '{
  "sourceType": "tag",
  "sources": [
    "artificial-intelligence",
    "@dhh"
  ],
  "maxResults": 50,
  "proxyConfiguration": {
    "useApifyProxy": true
  }
}' |
apify call scrapesage/medium-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,scrapesage/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/fdk2ihF2UgkKlK2jG/builds/c5Y22XdQzgNXIdef6/openapi.json