# Substack Discovery Scraper (`getdataforme/substack-discovery-scraper`) Actor
The Substack Discovery Scraper efficiently extracts and analyzes data from Substack publications, supporting market research, competitive intelligence, and content aggregation....
- **URL**: https://apify.com/getdataforme/substack-discovery-scraper.md
- **Developed by:** [GetDataForMe](https://apify.com/getdataforme) (community)
- **Categories:** AI, Other, E-commerce
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks
- **User rating**: No ratings yet
## Pricing
from $9.00 / 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/platform/actors/running/actors-in-store#pay-per-event
## What's an Apify Actor?
Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases.
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.
In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md):
```bash
npm install apify-client
```
In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md):
```bash
pip install apify-client
```
In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md):
````bash
# MacOS / Linux
curl -fsSL https://apify.com/install-cli.sh | bash
# Windows
irm https://apify.com/install-cli.ps1 | iex
```bash
In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md).
If your project is in a different language, use 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 Discovery Scraper
The Substack Discovery Scraper is a powerful tool designed to efficiently extract and analyze data from Substack publications. Whether you're conducting market research, gathering competitive intelligence, or aggregating content, this Actor provides reliable and comprehensive data to support your needs.
### Features
- **Efficient Data Extraction**: Quickly scrape data from Substack publications using customizable search queries.
- **High Data Quality**: Ensures accurate and up-to-date information with detailed metadata.
- **Scalable Performance**: Capable of handling large volumes of data with configurable limits.
- **Proxy Support**: Utilizes Apify's residential proxies to maintain anonymity and avoid IP bans.
- **Versatile Output**: Provides data in multiple formats, including JSON, CSV, and Excel.
- **User-Friendly Interface**: Easy setup and configuration through the Apify platform.
- **Comprehensive Metadata**: Extracts detailed information about publications, authors, and content.
### Input Parameters
| Parameter | Type | Required | Description | Example |
|--------------------|---------|----------|-----------------------------------------------------------------------------|-----------------|
| `searchQuery` | String | Yes | The search query to use for finding relevant Substack content. | "project" |
| `maxItems` | Integer | No | Maximum number of items to scrape. | 100 |
| `proxyConfiguration` | Object | No | Configuration for proxy servers to hide the scraper's origin. | See below |
#### Proxy Configuration Example
```json
{
"useApifyProxy": true,
"apifyProxyGroups": ["RESIDENTIAL"]
}
````
### Example Usage
#### Input
```json
{
"searchQuery": "project",
"maxItems": 100,
"proxyConfiguration": {
"useApifyProxy": true,
"apifyProxyGroups": ["RESIDENTIAL"]
}
}
```
#### Output
```json
[
{
"id": 193517257,
"title": "The ICE \"Box\" Tactic: Unhinged, Reckless, and Designed for Disaster",
"subtitle": " April 7, 2026 | PATTERSON, CA ",
"slug": "the-ice-box-tactic-unhinged-reckless",
"type": "podcast",
"audience": "everyone",
"canonical_url": "https://eyesonice.substack.com/p/the-ice-box-tactic-unhinged-reckless",
"post_date": "2026-04-07T23:05:28.866Z",
"wordcount": 645,
"truncated_body_text": "The Mechanics of the \u201cBox\u201d",
"description": "April 7, 2026 | PATTERSON, CA",
"cover_image": "https://substack-video.s3.amazonaws.com/video_upload/post/193517257/86d9024c-d8d2-4124-99d5-b617c32a7e27/transcoded-00001.png",
"reaction_count": 140,
"comment_count": 19,
"restacks": 86,
"podcast_duration": 34.403267,
"podcast_url": "https://api.substack.com/api/v1/audio/upload/f732039a-8785-4653-8c02-4149e2eb7048/src",
"podcast_episode_image_url": "https://substack-post-media.s3.amazonaws.com/public/images/78468f63-e8d8-4d7f-b9f8-91c873d2059d_1400x1400.png",
"author_name": "Eyes On Ice",
"author_handle": "eyesonice",
"author_bio": "Humanist, and Seeker of Truth. Sharing updates on immigration policies, migrant rights, and fostering discussions. Stand in solidarity with immigrants. https://t.co/nrmNF5KQFv",
"author_photo_url": "https://substack-post-media.s3.amazonaws.com/public/images/2b0044b1-5417-4e76-9229-1c32631348aa_1024x1024.png",
"author_twitter": "CantStopPoppin",
"publication_id": 4363505,
"publication_name": "Eyes On ICE",
"publication_subdomain": "eyesonice",
"publication_logo": "https://substack-post-media.s3.amazonaws.com/public/images/5e3b87f3-826c-4cb1-8edd-40b71b346f98_1024x1024.png",
"publication_hero_text": "Welcome to a space where compassion meets accountability. This substack is dedicated to monitoring immigration policies, advocating for migrant rights, and fostering informed, respectful discussions about one of the most pressing issues of our time.",
"scraped_at": "2026-04-17T07:16:42.897Z"
}
]
```
### Use Cases
- **Market Research and Analysis**: Gather insights on trending topics and audience engagement.
- **Competitive Intelligence**: Monitor competitor publications and strategies.
- **Content Aggregation**: Compile articles and podcasts for newsletters or reports.
- **Academic Research**: Analyze publication trends and author networks.
- **Business Automation**: Automate data collection for business intelligence tools.
### Installation and Usage
1. Search for "Substack Discovery Scraper" in the Apify Store.
2. Click "Try for free" or "Run".
3. Configure input parameters.
4. Click "Start" to begin extraction.
5. Monitor progress in the log.
6. Export results in your preferred format (JSON, CSV, Excel).
### Output Format
The output is a JSON array containing objects with detailed information about each Substack post, including metadata such as title, author, publication date, and more. Key fields include `id`, `title`, `author_name`, `post_date`, and `canonical_url`.
### Support
For custom/simplified outputs or bug reports, please contact:
- Email: support@getdataforme.com
- Subject line: "custom support"
- Contact form:
We're here to help you get the most out of this Actor!
# Actor input Schema
## `searchQuery` (type: `string`):
The search query to use.
## `maxItems` (type: `integer`):
Maximum number of items that can be scraped by this crawler.
## `proxyConfiguration` (type: `object`):
Specifies proxy servers that will be used by the scraper in order to hide its origin.
## Actor input object example
```json
{
"searchQuery": "project",
"maxItems": 100,
"proxyConfiguration": {
"useApifyProxy": true,
"apifyProxyGroups": [
"RESIDENTIAL"
]
}
}
```
# 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 '' with your token
const client = new ApifyClient({
token: '',
});
// Prepare Actor input
const input = {
"proxyConfiguration": {
"useApifyProxy": true,
"apifyProxyGroups": [
"RESIDENTIAL"
]
}
};
// Run the Actor and wait for it to finish
const run = await client.actor("getdataforme/substack-discovery-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 '' with your token.
client = ApifyClient("")
# Prepare the Actor input
run_input = { "proxyConfiguration": {
"useApifyProxy": True,
"apifyProxyGroups": ["RESIDENTIAL"],
} }
# Run the Actor and wait for it to finish
run = client.actor("getdataforme/substack-discovery-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 '{
"proxyConfiguration": {
"useApifyProxy": true,
"apifyProxyGroups": [
"RESIDENTIAL"
]
}
}' |
apify call getdataforme/substack-discovery-scraper --silent --output-dataset
```
## MCP server setup
```json
{
"mcpServers": {
"apify": {
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.apify.com/?tools=getdataforme/substack-discovery-scraper",
"--header",
"Authorization: Bearer "
]
}
}
}
```
## OpenAPI specification
```json
{
"openapi": "3.0.1",
"info": {
"title": "Substack Discovery Scraper",
"description": "The Substack Discovery Scraper efficiently extracts and analyzes data from Substack publications, supporting market research, competitive intelligence, and content aggregation....",
"version": "0.0",
"x-build-id": "1M2GfIMLs5daFHytW"
},
"servers": [
{
"url": "https://api.apify.com/v2"
}
],
"paths": {
"/acts/getdataforme~substack-discovery-scraper/run-sync-get-dataset-items": {
"post": {
"operationId": "run-sync-get-dataset-items-getdataforme-substack-discovery-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
},
"/acts/getdataforme~substack-discovery-scraper/runs": {
"post": {
"operationId": "runs-sync-getdataforme-substack-discovery-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor and returns information about the initiated run in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK",
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/runsResponseSchema"
}
}
}
}
}
}
},
"/acts/getdataforme~substack-discovery-scraper/run-sync": {
"post": {
"operationId": "run-sync-getdataforme-substack-discovery-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
}
},
"components": {
"schemas": {
"inputSchema": {
"type": "object",
"properties": {
"searchQuery": {
"title": "Search Query",
"type": "string",
"description": "The search query to use.",
"default": "project"
},
"maxItems": {
"title": "Max Items",
"type": "integer",
"description": "Maximum number of items that can be scraped by this crawler.",
"default": 100
},
"proxyConfiguration": {
"title": "Proxy configuration",
"type": "object",
"description": "Specifies proxy servers that will be used by the scraper in order to hide its origin.",
"default": {
"useApifyProxy": true,
"apifyProxyGroups": [
"RESIDENTIAL"
]
}
}
}
},
"runsResponseSchema": {
"type": "object",
"properties": {
"data": {
"type": "object",
"properties": {
"id": {
"type": "string"
},
"actId": {
"type": "string"
},
"userId": {
"type": "string"
},
"startedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"finishedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"status": {
"type": "string",
"example": "READY"
},
"meta": {
"type": "object",
"properties": {
"origin": {
"type": "string",
"example": "API"
},
"userAgent": {
"type": "string"
}
}
},
"stats": {
"type": "object",
"properties": {
"inputBodyLen": {
"type": "integer",
"example": 2000
},
"rebootCount": {
"type": "integer",
"example": 0
},
"restartCount": {
"type": "integer",
"example": 0
},
"resurrectCount": {
"type": "integer",
"example": 0
},
"computeUnits": {
"type": "integer",
"example": 0
}
}
},
"options": {
"type": "object",
"properties": {
"build": {
"type": "string",
"example": "latest"
},
"timeoutSecs": {
"type": "integer",
"example": 300
},
"memoryMbytes": {
"type": "integer",
"example": 1024
},
"diskMbytes": {
"type": "integer",
"example": 2048
}
}
},
"buildId": {
"type": "string"
},
"defaultKeyValueStoreId": {
"type": "string"
},
"defaultDatasetId": {
"type": "string"
},
"defaultRequestQueueId": {
"type": "string"
},
"buildNumber": {
"type": "string",
"example": "1.0.0"
},
"containerUrl": {
"type": "string"
},
"usage": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "integer",
"example": 1
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
},
"usageTotalUsd": {
"type": "number",
"example": 0.00005
},
"usageUsd": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "number",
"example": 0.00005
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
}
}
}
}
}
}
}
}
```