# Substack Newsletters and Creator Scraper (`adaptive_nightmare/substack-scraper`) Actor

Scrape Substack publications, writer profiles, subscription pricing, top rankings, and post engagement metrics for outreach and research.

- **URL**: https://apify.com/adaptive_nightmare/substack-scraper.md
- **Developed by:** [Darim Quraishi](https://apify.com/adaptive_nightmare) (community)
- **Categories:** Lead generation, Business, For creators
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

$1.00 / 1,000 results

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

## Substack Newsletters and Creator Scraper

Extract data on Substack newsletters, authors, subscription pricing plans, contact links, and reader engagement metrics.

### Features

- Scrapes publication profiles across 30+ official Substack categories, including Technology, Business, Finance, and Crypto.
- Supports leaderboard filtering by featured publications, top paid, top free, and highest grossing bestsellers.
- Accepts direct Substack URLs, including publications with custom domains.
- Pulls recent article titles, publication dates, like counts, and comment counts to measure reader engagement.
- Extracts monthly, annual, and founding subscription rates with currency codes.
- Queries public endpoints directly without requiring residential proxies.

### Input parameters

| Parameter | Type | Default | Description |
| :--- | :--- | :--- | :--- |
| `categories` | Array of Strings | `["technology", "business"]` | Substack categories to crawl (e.g. `technology`, `business`, `finance`, `crypto`, etc.). |
| `leaderboardType` | String | `"all"` | Leaderboard filter: `all` (Popular/Featured), `paid` (Top Paid), `free` (Top Free), or `bestseller` (Top ARR). |
| `startUrls` | Array of Objects | `[]` | Optional direct Substack publication URLs (e.g., `https://bytebytego.substack.com`). |
| `maxPublications` | Integer | `50` | Maximum total publications to extract. |
| `includeRecentPosts` | Boolean | `true` | Extract recent post engagement (titles, publish dates, likes/reactions, comments). |
| `maxRecentPosts` | Integer | `3` | Number of recent articles to analyze per newsletter. |

### Output format

`json
{
  "name": "The Pragmatic Engineer",
  "url": "https://newsletter.pragmaticengineer.com",
  "subdomain": "pragmaticengineer",
  "customDomain": "newsletter.pragmaticengineer.com",
  "category": "Technology",
  "leaderboardType": "all",
  "categoryRank": 1,
  "tagline": "Big tech and high-growth startups: advice from an engineering manager who has been there.",
  "authorName": "Gergely Orosz",
  "authorHandle": "gergelyorosz",
  "authorTwitter": "GergelyOrosz",
  "authorBio": "Engineering manager and software engineer at Uber, Skype, Skyscanner.",
  "subscribersCount": 850000,
  "pricing": {
    "monthly": 15,
    "annual": 150,
    "founding": 250,
    "currency": "USD"
  },
  "recentPosts": [
    {
      "title": "State of Software Engineering in 2026",
      "publishedAt": "2026-10-15T12:00:00.000Z",
      "likesCount": 1840,
      "commentsCount": 312
    }
  ],
  "scrapedAt": "2026-10-20T12:00:00.000Z"
}
`

### Use cases

- Sponsorship research: Identify relevant publications and verify reader engagement before buying ad slots.
- Media outreach: Connect with newsletter writers and editors covering your industry.
- Market benchmarking: Compare subscription tiers, pricing, and publishing cadence across categories.
- Creator directories: Build clean databases for outreach and research.

### Pricing and efficiency

- Typical runtime: 2 to 4 seconds per execution.
- Zero proxy costs: Runs over public REST and RSS endpoints without residential proxy pools.
- Suitable for scheduled runs and continuous monitoring under standard platform limits.

# Actor input Schema

## `categories` (type: `array`):

Select or enter Substack categories to scrape from official leaderboards.

## `leaderboardType` (type: `string`):

Choose which leaderboard ranking to extract from each category.

## `startUrls` (type: `array`):

Direct URLs of specific Substack publications to scrape (e.g. https://bytebytego.substack.com or custom domain like https://blog.bytebytego.com).

## `maxPublications` (type: `integer`):

Maximum total number of publications to scrape.

## `includeRecentPosts` (type: `boolean`):

If enabled, extracts recent post titles, publish dates, reaction counts (likes), and comments for each publication.

## `maxRecentPosts` (type: `integer`):

Number of recent posts to scrape per publication (ignored if 'Include Recent Posts' is off).

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

Select proxies to use when running on Apify Cloud. Default datacenter proxies work great.

## Actor input object example

```json
{
  "categories": [
    "technology",
    "business"
  ],
  "leaderboardType": "all",
  "startUrls": [],
  "maxPublications": 50,
  "includeRecentPosts": true,
  "maxRecentPosts": 3,
  "proxyConfiguration": {
    "useApifyProxy": 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 = {
    "categories": [
        "technology",
        "business"
    ],
    "startUrls": []
};

// Run the Actor and wait for it to finish
const run = await client.actor("adaptive_nightmare/substack-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 = {
    "categories": [
        "technology",
        "business",
    ],
    "startUrls": [],
}

# Run the Actor and wait for it to finish
run = client.actor("adaptive_nightmare/substack-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 '{
  "categories": [
    "technology",
    "business"
  ],
  "startUrls": []
}' |
apify call adaptive_nightmare/substack-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,adaptive_nightmare/substack-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/MnD9JrgYYsUBfaLYx/builds/e7WAs83Z6EcIyaNdG/openapi.json