# Substack Scraper — Posts, Comments & Paraphrase with AI (`confidential_gnat/substack-newsletter-scraper`) Actor

Scrape Substack (substack.com) posts by keyword search, publication or post URL: title, author, date, full text, tags, reactions and comments with free sentiment, plus AI summaries. Cross-run caching returns only new posts. Export JSON, CSV, Excel or API.

- **URL**: https://apify.com/confidential\_gnat/substack-newsletter-scraper.md
- **Developed by:** [ActorFlow](https://apify.com/confidential_gnat) (community)
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $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.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.

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 Scraper — Newsletter Posts, Comments & Search with AI

**Scrape Substack newsletter posts and comments** from [substack.com](https://substack.com) search results, any Substack publication, or a single post — including publications on their own custom domain. This **Substack scraper** extracts the title, subtitle, author, publish date, full post text, tags, cover image, reactions, comment and restack counts, and can collect every **reader comment with a sentiment label** at no extra cost. Optionally **enrich every post with AI** — a summary, keywords, sentiment or full paraphrase. Export to JSON, CSV or Excel, or call it as a **Substack API** from Python, JavaScript or cURL. Paste a search, publication or post URL and press Start.

![Substack scraper exporting newsletter posts and comments to CSV, JSON and XML](./assets/featureimage.png)

> 🔁 **Only pay for new posts.** Give a run a `cacheProjectName` and this Substack scraper remembers every post it has already collected. Every later run with the same name **skips those posts and returns only newly published ones**, so they are never downloaded, enriched or billed twice. It makes this actor a low-cost **Substack monitor** for newsletters and keywords you track on a schedule.

### ✨ Features of this Substack newsletter scraper

- **Cross-run caching: scrape only new posts** — name a cache project and every later run skips posts it already collected, so scheduled runs return only fresh posts and you never pay twice for the same post
- **Substack search by keyword** — paste a `substack.com/search/{keyword}` URL to scrape matching posts from across every publication
- **Full post extraction** — title, subtitle, authors, publish date, body text, word count, tags, cover image and podcast URL
- **Substack comments scraper** — optionally collect every reader comment and reply, each tagged positive, negative, neutral or mixed at no extra charge
- **AI enrichment** — optional per-post summary, keywords, sentiment analysis, paraphrase, or your own custom instructions
- **Engagement metrics** — reaction, comment and restack counts for every post
- **Paywall detection** — paid posts are flagged with `isPaywalled` and can be skipped entirely
- **Custom domain support** — works with publications on their own domain, not just `*.substack.com`
- **Pagination support** — walks a whole publication archive or many pages of search results until your item limit is reached
- **Proxy support** — optional, and switched off by default
- **No browser required** — runs on plain HTTP requests, which makes it fast and cheap

### 🔁 Scrape only new Substack posts with cross-run caching

Most newsletter scrapers download the whole archive or search again every time they run. This one can **remember what it has already scraped**. Set `cacheProjectName` to any name, for example `ai-newsletters`, and the actor keeps a list of every post URL it collects under that name in your Apify account. The next run with the same name:

- **skips every post already collected**, whether it was found through a search, an archive or a direct post URL
- **counts only new posts toward `maxItems`**, so `maxItems: 20` means 20 posts you have not seen before
- **never re-runs AI enrichment or comment sentiment** on a cached post, so you are **never charged twice** for the same post
- **saves the list only after a run finishes successfully**. If a run fails part-way through, the next run fetches those posts again rather than missing them

**How to monitor Substack for new posts:**

1. Enter a search URL such as `https://substack.com/search/bitcoin`, or a publication archive.
2. Set `cacheProjectName` to a name you will reuse, such as `bitcoin-watch`.
3. Add an [Apify Schedule](https://docs.apify.com/platform/schedules) to run it daily or hourly.
4. Each run's dataset now holds **only the posts published since the last run**. Connect it to Slack, email, Google Sheets or a webhook to get alerts for new Substack posts.

Use a different `cacheProjectName` for each thing you track, or share one name across several start URLs so a post found through both a search and its publication archive is only scraped once. Leave it empty to scrape everything on every run.

### 🚀 How to scrape Substack newsletters in 5 steps

1. [Sign up](https://apify.com/sign-up) for a free Apify account — includes **$5 monthly credit**.
2. Open the actor page and click **Try for free**.
3. Paste one or more Substack search, publication or post URLs into **Start URLs**.
4. Click **Start** and wait for the run to complete.
5. Download results from the **Output** tab in JSON, CSV, or Excel format.

You can also run this actor via the [Apify API](https://docs.apify.com/api/v2) or integrate it directly into your workflows using [Zapier](https://zapier.com/apps/apify), [Make](https://www.make.com/), or [n8n](https://n8n.io/).

### 💰 How much does it cost to scrape Substack?

This actor uses **pay-per-result** billing based on the compute units a run consumes, plus a **pay-per-event** charge of $0.05 for each post enriched with AI.

- New Apify accounts include **$5 of free monthly credit**.
- It runs on plain HTTP requests rather than a headless browser, so it costs significantly less to run than browser-based newsletter scrapers.
- Proxies are disabled by default, which keeps runs at their cheapest.
- **Comment sentiment is free** — comments and their sentiment labels carry no extra charge.
- **AI enrichment is opt-in and only charged when it succeeds.** Posts no model could enrich, and paywalled previews, are never charged.
- **Caching cuts repeat-run costs.** With `cacheProjectName` set, posts already collected are skipped before they are fetched or enriched, so a scheduled run only pays for new posts.

### 🔧 Substack scraper input configuration

| Field                  | Type    | Required | Default                                  | Description                                                                                                  |
| ---------------------- | ------- | -------- | ---------------------------------------- | ------------------------------------------------------------------------------------------------------------ |
| `startUrls`            | array   | —        | `https://substack.com/search/bitcoin`    | Substack search, publication, archive, or single post URLs. Page type is detected automatically.             |
| `maxItems`             | integer | —        | `5`                                      | Maximum posts to scrape **per start URL**. Set to `0` for no limit.                                          |
| `includePaywalled`     | boolean | —        | `true`                                   | Keep paid posts (with an `isPaywalled` flag) or skip them entirely.                                          |
| `cacheProjectName`     | string  | —        | —                                        | **Cross-run cache.** Reuse the same name and later runs skip already-scraped posts, returning only new ones. |
| `scrapeComments`       | boolean | —        | `false`                                  | Also collect each post's comments and replies, each with a sentiment label.                                  |
| `maxCommentsPerPost`   | integer | —        | `50`                                     | Maximum comments per post, best first. Set to `0` for all.                                                   |
| `aiEnabled`            | boolean | —        | `false`                                  | Turn on AI enrichment for each post.                                                                         |
| `aiFeatures`           | array   | —        | `["summarize", "keywords", "sentiment"]` | Which enrichments to generate: summary, paraphrase, keywords, sentiment, or custom.                          |
| `aiModels`             | array   | —        | `["openai/gpt-4o-mini"]`                 | Models tried in order; the first usable result wins.                                                         |
| `aiCustomInstructions` | string  | —        | —                                        | Used only with the `custom` AI feature. Describe what to extract from each post.                             |
| `proxyConfiguration`   | object  | —        | `{"useApifyProxy": false}`               | Proxy settings. Off by default.                                                                              |

**Supported URL types:**

- Substack search — `https://substack.com/search/bitcoin?searching=all_posts`
- Publication archive — `https://astralcodexten.substack.com/archive`
- Publication home page — `https://astralcodexten.substack.com`
- Single post — `https://astralcodexten.substack.com/p/open-thread-450`
- Custom domain — `https://www.thefp.com/p/some-post`

### 📦 Substack scraper output data

Each result is a JSON object with the keys `url`, `title`, `subtitle`, `slug`, `publication`, `authors`, `publishedAt`, `audience`, `isPaywalled`, `type`, `description`, `body`, `wordCount`, `tags`, `coverImage`, `podcastUrl`, `reactionCount`, `commentCount` and `restackCount`, plus an `ai` object when enrichment is enabled and a `comments` array when comment scraping is enabled.

The dataset ships with four views: **Overview**, a compact table of title, authors, date and paywall status; **Full post details**, which adds the body text, tags and engagement counts; **AI enrichment**, which shows the generated summary, keywords and sentiment per post; and **Comments**, which lists each post's comments with their sentiment.

**Sample post output:**

```json
[
    {
        "url": "https://www.astralcodexten.com/p/royce-on-san-francisco",
        "title": "Royce On San Francisco",
        "subtitle": "...",
        "slug": "royce-on-san-francisco",
        "publication": "https://astralcodexten.substack.com",
        "authors": ["Scott Alexander"],
        "publishedAt": "2026-09-10T11:10:18.859Z",
        "audience": "everyone",
        "isPaywalled": false,
        "type": "newsletter",
        "description": "...",
        "body": "On housing prices:\n\nThe San Franciscans at this moment, living in their rag palaces, or renting them at figures that would have sounded possible in the Arabian Nights . . . seemed more like madmen than ever. A correspondent of the New York Post gives with a half-serious fury and contempt an amusing account of the landlords of San Francisco:\n\n“The people of San Francisco are mad, stark mad. A dozen times or more, duri …",
        "wordCount": 2393,
        "tags": [],
        "coverImage": "https://substack-post-media.s3.amazonaws.com/public/images/582979e2-4bb5-46aa-91ae-ce2ab6d05fa5_738x415.jpeg",
        "podcastUrl": null,
        "reactionCount": 155,
        "commentCount": 76,
        "restackCount": 2
    },
    {
        "url": "https://www.astralcodexten.com/p/god-help-us-lets-try-to-learn-about",
        "title": "God Help Us, Let’s Try To Learn About Mechanistic Interpretability Techniques",
        "subtitle": "...",
        "slug": "god-help-us-lets-try-to-learn-about",
        "publication": "https://astralcodexten.substack.com",
        "authors": ["Scott Alexander"],
        "publishedAt": "2026-09-08T12:04:21.658Z",
        "audience": "everyone",
        "isPaywalled": false,
        "type": "newsletter",
        "description": "...",
        "body": "The Story So Far\n\nMechanistic interpretability is the science of “reading an AI’s mind”.\n\nLarge language models are “grown, not built”. Researchers run training data through a neural network. Eventually this creates a working AI; nobody really knows how.\n\nBut a neural network is just a set of simulated neurons on a computer. The person with the computer can see the neurons, the connections between them, and which one …",
        "wordCount": 4695,
        "tags": [],
        "coverImage": "https://substackcdn.com/image/fetch/$s_!S-UV!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fe6dfd520-f8be-4174-8bd3-428c052b53a7_400x418.png",
        "podcastUrl": null,
        "reactionCount": 366,
        "commentCount": 208,
        "restackCount": 25
    }
]
```

**Sample `comments` array** (when `scrapeComments` is on). Replies keep a `parentId` and `depth`, so threads can be rebuilt from a flat CSV:

```json
[
    {
        "id": "277591836",
        "parentId": null,
        "depth": 0,
        "author": "Susie",
        "authorHandle": "susiiee",
        "date": "2026-06-16T22:33:47.934Z",
        "editedAt": null,
        "body": "I haven’t finished reading but this is so fricking relatable. I feel like I’m always watching through another lens of my life ykwim? …",
        "isDeleted": false,
        "reactionCount": 188,
        "replyCount": 3,
        "sentiment": "positive",
        "sentimentConfidence": 0.83
    },
    {
        "id": "278621506",
        "parentId": "277591836",
        "depth": 1,
        "author": "Vishesh Kashyap",
        "authorHandle": "visheshkashyap",
        "date": "2026-06-18T17:17:00.384Z",
        "editedAt": null,
        "body": "It's better this way, tat u r able to act better in the situation u loved ones need u the most. …",
        "isDeleted": false,
        "reactionCount": 12,
        "replyCount": 0,
        "sentiment": "positive",
        "sentimentConfidence": 0.98
    }
]
```

### 🐍 How to scrape Substack with Python, JavaScript or the API

Run the actor programmatically with the official Apify clients. Replace `<YOUR_API_TOKEN>` with the token from your [Apify Console](https://console.apify.com/account/integrations).

**Python** (`pip install apify-client`):

```python
from apify_client import ApifyClient

client = ApifyClient("<YOUR_API_TOKEN>")

run = client.actor("confidential_gnat/substack-newsletter-scraper").call(run_input={
    "startUrls": [{"url": "https://substack.com/search/artificial%20intelligence"}],
    "maxItems": 20,
    "scrapeComments": True,
})

for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item["title"], len(item.get("comments", [])))
```

**JavaScript** (`npm install apify-client`):

```javascript
import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: '<YOUR_API_TOKEN>' });

const run = await client.actor('confidential_gnat/substack-newsletter-scraper').call({
    startUrls: [{ url: 'https://astralcodexten.substack.com/archive' }],
    maxItems: 5,
    aiEnabled: false,
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);
```

**cURL** — start a run and wait for the dataset:

```bash
curl -X POST "https://api.apify.com/v2/acts/confidential_gnat~substack-newsletter-scraper/run-sync-get-dataset-items?token=<YOUR_API_TOKEN>" \
  -H "Content-Type: application/json" \
  -d '{"startUrls": [{"url": "https://astralcodexten.substack.com/archive"}], "maxItems": 5, "aiEnabled": false}'
```

### 💡 What you can use Substack newsletter data for

- **New-post monitoring** — get only new posts from newsletters or keywords you follow, using cross-run caching and a schedule
- **Content research** — track what a writer publishes and how often
- **Topic discovery** — search all of Substack for a keyword and see which newsletters cover it
- **Competitive analysis** — monitor rival newsletters in your niche
- **Audience sentiment analysis** — see how readers react to each post from the tone of their comments
- **Trend detection** — run AI keyword extraction across an archive to see recurring themes
- **Engagement benchmarking** — compare reactions, comments and restacks across posts and publications
- **Training and research datasets** — collect long-form writing with structured metadata

Media analysts, content marketers, researchers and newsletter operators use this Substack data across publishing, market research, competitive intelligence and academic work.

### ⚠️ Substack scraping limitations

- **Paywalled posts** — paid-subscriber posts return only the short public preview, not the full text. They are flagged with `isPaywalled` so you can filter them, and AI enrichment skips them so you are never charged to summarize a teaser. The actor does not log in or bypass paywalls.
- **Comments** — collected only when `scrapeComments` is on. On posts restricted to paid subscribers (`audience: "only_paid"`), Substack hides the comments from non-subscribers, so `comments` comes back empty even when the post text itself is public.
- **Search depth** — a search stops after 50 result pages (roughly 500 posts). Substack search mixes in notes and profiles; only posts are scraped.
- **Rate limiting** — very high-volume runs across many publications may be throttled; enable proxies if you hit limits.

### ❓ Frequently asked questions

#### Is it legal to scrape Substack?

This actor only collects data that is already publicly visible on Substack — no login, paywall bypass, or private content is accessed. Scraping publicly available data is generally considered lawful (see *hiQ Labs v. LinkedIn* as precedent). You remain responsible for complying with Substack's Terms of Service, each publication's own terms, and applicable copyright law when republishing content.

#### How do I search all of Substack by keyword?

Search on [substack.com](https://substack.com/search), copy the URL (for example `https://substack.com/search/bitcoin?searching=all_posts`) and paste it into **Start URLs**. The scraper collects matching posts from every publication, up to your `maxItems` limit.

#### Can I scrape Substack comments?

Yes. Turn on `scrapeComments` and every post gets a `comments` array with each comment's author, date, text, reactions and replies. Use `maxCommentsPerPost` to cap how many are collected, best comments first.

#### How is Substack comment sentiment calculated?

Each comment is classified by an AI model into one of four fixed labels — `positive`, `negative`, `neutral` or `mixed` — with a `sentimentConfidence` between 0 and 1. It is included free with comment scraping.

#### Does this scraper get paywalled Substack posts?

No — it collects what a logged-out visitor sees. For paid posts that is the public preview, which the actor flags with `isPaywalled: true`. Set `includePaywalled` to `false` to skip them entirely.

#### How many posts can I scrape from one Substack newsletter?

As many as the archive holds. `maxItems` limits results **per start URL**, so scraping three publications with `maxItems: 100` returns up to 300 posts. Set it to `0` for the entire archive.

#### How do I scrape only new Substack posts since the last run?

Set `cacheProjectName` and reuse the same name every run. The actor remembers every post it has collected under that name and skips them next time, so each run returns only newly published posts and never charges you twice for the same one. Pair it with [Apify Schedules](https://docs.apify.com/platform/schedules) to monitor a newsletter or a Substack keyword search daily or weekly.

### 🔗 Other actors you may find useful

- 🏠 **[University Living Housing Scraper](https://apify.com/confidential_gnat/universityliving-housing-scraper)** — Scrapes student housing listings and property details from universityliving.com.
- 🍷 **[Total Wine Scraper](https://apify.com/confidential_gnat/totalwine-scraper)** — Scrape Total Wine & More (totalwine.com) wine, liquor and beer prices, sizes, ratings, reviews, badges, ABV, origin and taste profile from search, category or product URLs.
- 🇩🇪 **[German Imprint (Impressum) Scraper with AI Extraction](https://apify.com/confidential_gnat/german-imprint-scraper)** — Finds the Impressum page on any German website and extracts the company's decision makers, legal name, address, email addresses, phone numbers, commercial register number and VAT ID as structured data using AI.
- ⭐ **[Google Play Store Reviews Scraper](https://apify.com/confidential_gnat/google-play-reviews-scraper)** — Scrapes user reviews from Google Play Store apps (play.google.com) including review text, star rating, author, date, replies and optional sentiment tagging, with app name, developer and overall rating attached to every review.
- 📜 **[Google Patents Scraper](https://apify.com/confidential_gnat/google-patents-scraper)** — Scrapes patent data from Google Patents (patents.google.com) by keyword or URL, including title, abstract, inventors, assignee, filing and publication dates, citations, figures and PDF links.

### 📰 Other news and article website scrapers

- 🗞️ **[Google News AI Scraper](https://apify.com/confidential_gnat/google-news-ai-scraper)** — Search Google News by keyword, optionally extract full article text and AI-generated summaries, and never re-scrape the same article twice across runs.
- 🦘 **[Sydney Morning Herald (SMH) News Scraper](https://apify.com/confidential_gnat/smh-news-scraper)** — Scrape news articles from The Sydney Morning Herald (smh.com.au) — headline, author, publish date, section, keywords, images and full public article text, with a paywall flag.
- 🇮🇩 **[Detik News Scraper](https://apify.com/confidential_gnat/detik-news-scraper)** — Scrapes news articles from Detik.com, including headline, author, publish date, category, images and full article text.

### 💬 Support & Contact

If you encounter any issues or have questions, please [open an issue](https://apify.com/confidential_gnat/substack-newsletter-scraper/issues/open)

You can also find more of our actors on the [Actor Flow ](https://apify.com/confidential_gnat).

# Actor input Schema

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

Substack search, publication or post URLs. Accepts a substack.com search (https://substack.com/search/bitcoin), a publication home page or archive (https://astralcodexten.substack.com), and single post URLs (https://astralcodexten.substack.com/p/some-post). Publications on custom domains work too. Page type is detected automatically.

## `maxItems` (type: `integer`):

Maximum number of posts to scrape per start URL. Set to 0 for no limit.

## `includePaywalled` (type: `boolean`):

Paid-subscriber posts return only a short public preview rather than the full text. Leave enabled to collect them with an isPaywalled flag, or disable to skip them entirely.

## `cacheProjectName` (type: `string`):

Scrape only new posts. Give this run a name (e.g. "ai-newsletters") and reuse it: every later run with the same name skips posts already collected and returns only newly published ones, so the same post is never scraped, enriched or billed twice. Ideal for scheduled monitoring. Leave empty to scrape everything every time.

## `scrapeComments` (type: `boolean`):

Also collect each post's reader comments and replies, each classified as positive, negative, neutral or mixed. Sentiment classification is included at no extra charge.

## `maxCommentsPerPost` (type: `integer`):

Maximum comments (including replies) to collect per post, best comments first. Set to 0 for all comments.

## `aiEnabled` (type: `boolean`):

Enrich each post with an AI-generated summary, keywords, sentiment or paraphrase. Only runs on posts with a full body — paywalled previews are skipped and never charged.

## `aiFeatures` (type: `array`):

Which enrichments to generate for each post.

## `aiModels` (type: `array`):

Models tried in order — the first that returns a usable result wins. A cheap primary with sturdier fallbacks behind it costs nothing extra on the happy path.

## `aiCustomInstructions` (type: `string`):

Used only when the 'custom' AI feature is selected. Describe what you want extracted from each post.

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

Proxy settings. Substack is reachable without a proxy, so proxies are disabled by default to keep runs cheap.

## Actor input object example

```json
{
  "startUrls": [
    {
      "url": "https://substack.com/search/bitcoin?searching=all_posts"
    }
  ],
  "maxItems": 5,
  "includePaywalled": true,
  "scrapeComments": false,
  "maxCommentsPerPost": 5,
  "aiEnabled": false,
  "aiFeatures": [
    "summarize",
    "keywords",
    "sentiment"
  ],
  "aiModels": [
    "openai/gpt-4o-mini"
  ],
  "proxyConfiguration": {
    "useApifyProxy": true
  }
}
```

# Actor output Schema

## `overview` (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 = {
    "startUrls": [
        {
            "url": "https://substack.com/search/bitcoin?searching=all_posts"
        }
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("confidential_gnat/substack-newsletter-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 = { "startUrls": [{ "url": "https://substack.com/search/bitcoin?searching=all_posts" }] }

# Run the Actor and wait for it to finish
run = client.actor("confidential_gnat/substack-newsletter-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 '{
  "startUrls": [
    {
      "url": "https://substack.com/search/bitcoin?searching=all_posts"
    }
  ]
}' |
apify call confidential_gnat/substack-newsletter-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,confidential_gnat/substack-newsletter-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/rcf7LtUXGaoGpYwDL/builds/Emb6i3qBGMjOrqdOH/openapi.json