# Medium Blog Scraper (`lafuan/medium-blog-scraper`) Actor

Extract Medium articles by topic via RSS. Get titles, authors, author URLs, article URLs, tags, publication date, publication name, and summary — clean JSON output.

- **URL**: https://apify.com/lafuan/medium-blog-scraper.md
- **Developed by:** [Muhammad Naufal](https://apify.com/lafuan) (community)
- **Categories:** News, Developer tools
- **Stats:** 2 total users, 0 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $0.50 / 1,000 results

This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage.

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 Blog Scraper

Extract articles from Medium by topic via RSS feed. Get titles, authors, author URLs, article URLs, tags, publication date, publication name, summary, cover images, language, claps, and reading time — clean JSON, no Cloudflare issues.

### Sample output

```json
{
  "title": "AWS Compute Options: Lambda and ECS",
  "author": "Rhuturaj Takle",
  "authorUrl": "https://medium.com/@rhutu.takle",
  "authorImageUrl": "https://miro.medium.com/v2/...",
  "url": "https://medium.com/@rhutu.takle/aws-compute-options-lambda-and-ecs-be23da0a096d",
  "tags": ["devops", "programming", "learning", "aws"],
  "publishedDate": "Tue, 14 Jul 2026 16:31:58 GMT",
  "updatedDate": "2026-07-14T16:31:58.837Z",
  "publication": "",
  "summary": "A practical guide to two of AWS's core compute services — Lambda for serverless, event-driven code execution, and ECS for orchestrating…",
  "topicUrl": "https://medium.com/feed/tag/programming",
  "imageUrl": "https://miro.medium.com/v2/...",
  "language": "en",
  "claps": 347,
  "readingTime": "5 min read",
  "readingTimeMinutes": 5,
  "subtitle": "A comparison of AWS Lambda and ECS for different workloads",
  "responsesCount": 12,
  "type": "article",
  "source": "medium"
}
```

### Input

| Field | Type | Default | Description |
|-------|------|---------|-------------|
| `topic` | string | `programming` | Medium topic tag (e.g. programming, ai, technology) or full Medium/custom domain URL |
| `maxResults` | integer | `10` | Max articles (1-50) |
| `fetchDetails` | boolean | `true` | Fetch article pages for claps, images, reading time (slower but richer) |
| `detailConcurrency` | integer | `5` | Concurrent detail fetches (1-20) |

### How it works

Two-phase extraction:

1. **RSS feed** (`medium.com/feed/tag/{topic}`) — returns structured XML with titles, authors, tags, dates, and summaries. Fast and not blocked by anti-bot. Supports full URLs and custom domains.
2. **Article pages** (one HTTP request per article) — extracts actual clap counts, images, author avatars, language, and reading time from the article HTML.

### Use cases

- Content curation for newsletters
- Trend analysis in tech topics
- Competitive research
- Building reading lists by topic
- Monitoring new articles in your niche

### Pricing

$0.0005 per article ($0.50 per 1k articles).

## Actor input object example

```json
{}
```

# 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 = {};

// Run the Actor and wait for it to finish
const run = await client.actor("lafuan/medium-blog-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 = {}

# Run the Actor and wait for it to finish
run = client.actor("lafuan/medium-blog-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 '{}' |
apify call lafuan/medium-blog-scraper --silent --output-dataset

```

## MCP server setup

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

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/Ymz5oLguQJSDynn9w/builds/weqtUPhMDW65CYlYk/openapi.json