# Substack Scraper — Newsletter Posts & Content (`fast_api/substack-scraper`) Actor

Extract Substack newsletter posts, titles, subtitles, publication dates, engagement metrics, and optional full text. Useful for media monitoring, creator research, market intelligence, and AI/RAG datasets.

- **URL**: https://apify.com/fast\_api/substack-scraper.md
- **Developed by:** [Fast API](https://apify.com/fast_api) (community)
- **Categories:** News
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $10.00 / 1,000 substack posts

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

## Substack Scraper — Newsletter Posts & Content

Extract clean, structured JSON from **Substack API + HTML fallback**. This Actor is built for media monitoring, creator research, market intelligence, newsletter datasets.

### What you can do with it

- Media monitoring
- Creator research
- Market intelligence
- Newsletter datasets

### Features

- Newsletter archive extraction
- Titles, subtitles, URLs, dates, and engagement metrics
- Optional full text extraction
- Useful for media/RAG datasets

### Example input

```json
{
  "newsletterUrl": "stratechery",
  "maxPosts": 20,
  "includeContent": true
}
```

### Example output

```json
{
  "title": "Example Newsletter Post",
  "subtitle": "A post subtitle",
  "url": "https://example.substack.com/p/post",
  "publishDate": "2026-07-01",
  "reactionCount": 42,
  "wordCount": 1800
}
```

### Output

Results are saved to the default Apify dataset as structured JSON. The actor includes an output schema so results are easy to preview, export, and consume from API clients.

### Pricing

This Actor is configured for pay-per-result monetization using Apify's pay-per-event model. Users pay for dataset items/results rather than a large fixed upfront fee.

### Common use cases

- AI/RAG dataset creation
- Market research and competitive intelligence
- Trend monitoring
- Data enrichment pipelines
- Scheduled data extraction

### Keywords

substack scraper, newsletter scraper, creator economy data, media monitoring, newsletter dataset

### Notes

This Actor focuses on practical structured data extraction with clean defaults and low overhead. For large runs, start with a small `maxItems` value, verify the output, then scale up.

# Actor input Schema

## `newsletterUrl` (type: `string`):

Substack URL or slug (e.g. 'stratechery' or full URL)

## `maxPosts` (type: `integer`):

The maxPosts parameter.

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

Fetch full post body text (slower)

## Actor input object example

```json
{
  "newsletterUrl": "stratechery",
  "maxPosts": 20,
  "includeContent": true
}
```

# 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("fast_api/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 = {}

# Run the Actor and wait for it to finish
run = client.actor("fast_api/substack-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 fast_api/substack-scraper --silent --output-dataset

```

## MCP server setup

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

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/1DPclCCuPDWj3Cs5T/builds/xpmFTlbwwtPbFdrUT/openapi.json