Medium Scraper

Collect posts for any topic across a date range. One clean row per post with claps, responses, author and publication. No login and no API key.

What it does

• Engagement on every row - claps, the number of people who clapped, and response count, so you can rank by what actually landed.
• Content stats - word count, reading time and image count, useful for working out what length performs.
• Author and publication on every post, with a link to the author.
• Any date range - archives go back years, so you can build a large historical dataset in one run.
• Filters for minimum claps, members only or free, and language.
• Every tag on the post, not just the one you searched.

Around 200 posts are published per tag per day, so a wide date range returns a lot of material.

Common uses: content and topic research, finding what performs in a niche, tracking authors and publications, competitor content monitoring, and building a writing dataset.

Input

Field	Type	Description
tags	array	Topics to collect. Enter them normally, for example Artificial Intelligence.
dateFrom	string	First day, YYYY-MM-DD. Defaults to seven days before the end date.
dateTo	string	Last day, YYYY-MM-DD. Defaults to yesterday.
maxResultsPerTag	integer	Cap per tag. Default 200, up to 20000.
minClaps	integer	Only posts with at least this many claps.
paywall	string	any, free or paid.
language	string	Two letter language code, for example en.
proxyConfiguration	object	Optional. Enable to spread requests across IPs.

Example input

{
  "tags": ["Artificial Intelligence", "Data Science"],
  "dateFrom": "2026-07-01",
  "dateTo": "2026-07-15",
  "maxResultsPerTag": 1000,
  "minClaps": 50,
  "paywall": "any"
}

Output

Each item is one post.

{
  "id": "0123456789ab",
  "title": "An Example Post Title",
  "subtitle": "The standfirst that appears under the title.",
  "author": "Jane Doe",
  "authorUsername": "example_user",
  "authorUrl": "https://medium.com/@example_user",
  "publication": "Example Publication",
  "claps": 468,
  "voters": 34,
  "responses": 2,
  "wordCount": 1868,
  "readingTimeMinutes": 7.25,
  "imageCount": 1,
  "tags": ["Artificial Intelligence", "Programming"],
  "isPaid": true,
  "language": "en",
  "publishedAt": "2026-07-15T09:14:02Z",
  "url": "https://medium.com/@example_user/an-example-post-title-0123456789ab",
  "searchTag": "artificial-intelligence"
}

publication is null for posts published under an author's own name rather than in a publication.

Notes

• No login and no API key. Enter a tag and run.
• Tags are entered in plain English and converted to the form the site uses, so Artificial Intelligence and artificial-intelligence both work.
• Posts are deduplicated across every tag and day, so a post carrying two of your tags is delivered once and charged once.
• Days with no posts are skipped, and a long run of empty days ends that tag early rather than burning the whole range.
• Claps come from the post record itself, so they are the real totals rather than an estimate.

To improve our actors we collect anonymized usage telemetry (run stats and input patterns). No personal account data is collected.