Substack Scraper — Publication Posts & Metadata | $1.50/1K | No Auth, Official API

For newsletter researchers, content agencies, competitive intelligence teams, and AI pipelines that need Substack content at scale.

Pricing: $1.50 per 1,000 post records · $2.50 per 1,000 podcast posts (posts where type=podcast and podcast_url is present — audio file URL included). No monthly fees. No authentication required.

Scrape any Substack publication's post listing via the official public REST API — no authentication, no proxy, no browser required. Returns structured metadata for every post: title, subtitle, publish date, audience (free vs paid), post type, reactions, comments, restacks, cover image, wordcount, and canonical URL.

Pay per post returned (PPE pricing).

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What you get

Field	Description
title	Post title
subtitle	Deck / tagline
canonical_url	Full URL to the post
slug	URL slug
post_date	Published timestamp (ISO 8601 UTC)
audience	everyone (free) or only_paid (paywalled)
type	newsletter, podcast, video, etc.
podcast_url	Audio file URL (podcast posts only)
reactions_count	Total hearts
comment_count	Number of comments
restacks	Number of Substack reposts
cover_image	Cover image URL
wordcount	Approximate word count
publication_slug	Short publication identifier
parse_confidence	Data quality score 0–1
warnings	List of missing-field codes

Note: Post bodies (full text / HTML) are not returned by the listing API. Paywalled posts return metadata only — body content requires a paid subscription and is not scraped.

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Pricing example

$1.50 per 1,000 newsletter posts · $2.50 per 1,000 podcast posts (posts where type=podcast and podcast_url is present). A 500-post archive = $0.75. Scraping 5 newsletters × 200 posts = $1.50. No per-run fee.

Sample output

{
  "title": "The Collapse of Web Scraping",
  "subtitle": "Why every major site now requires a browser — and what to do about it",
  "canonical_url": "https://on.substack.com/p/the-collapse-of-web-scraping",
  "post_date": "2026-05-18T14:00:00Z",
  "audience": "everyone",
  "type": "newsletter",
  "podcast_url": null,
  "reactions_count": 312,
  "comment_count": 47,
  "restacks": 89,
  "wordcount": 2100,
  "publication_slug": "on",
  "parse_confidence": 1.0,
  "scraped_at": "2026-06-05T09:00:00Z"
}

Frequently asked questions

Do I need a Substack account or API key? No. The actor uses the official Substack public listing API — no authentication required for public publications.

Do I need a proxy? No. The Substack API is open. Zero proxy cost to you.

What formats does the output come in? JSON, CSV, and Excel via the Apify dataset. Native integration with n8n, Make, Zapier.

What if the publication returns a 403 or empty results? Some publications restrict their API access (e.g. bankless.substack.com). The actor logs the error and exits cleanly — it pushes nothing and charges nothing. Switch to a different slug and try again.

Input

Parameter	Type	Default	Description
publication	string	on	Slug (e.g. on), full URL (e.g. https://on.substack.com), or custom domain
maxPosts	integer	100	Max posts to return. 0 = no limit (fetch entire archive)

Publication examples

on                          →  on.substack.com
bankless                    →  bankless.substack.com
https://on.substack.com     →  on.substack.com (same)
https://platformer.news     →  custom domain (supported)

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How it works

Uses the Substack per-publication public REST endpoint:

GET https://<publication>.substack.com/api/v1/posts?offset=0&limit=50

Paginates via offset until all posts are retrieved or maxPosts is reached. No auth headers needed. No proxy required for public publications.

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Our edge over incumbents

• Reliable pagination — offset-based, not page-based; survives large archives.
• Reactions normalized — raw reactions dict summed to reactions_count (compatible with publications adding new reaction types).
• parse_confidence score — every record includes a data-quality score and warnings list so you can detect schema drift without re-running.
• restacks field — Substack's repost count, absent from most competitor actors.
• Custom domain support — not just *.substack.com slugs.

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Limitations

• Post bodies not included — listing API returns metadata only. Full HTML/Markdown bodies require the individual post endpoint (not in this actor's scope).
• Paywalled posts — metadata is returned for all posts, but body content is not accessible without a paid subscription.
• Publications blocking API access — some publications (e.g. bankless.substack.com) return 403; this is a publication-level restriction, not a Substack platform restriction.

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Competitor comparison

	This scraper	Other Substack actors
Official Substack API	✓	partial
restacks field	✓	✗
Custom domain support	✓	✗
podcast_url field	✓	✗
parse_confidence on every record	✓	✗
No auth required	✓	✓

Podcast use case

The podcast_url field makes this actor useful for extracting Substack podcast episode lists without an RSS parser. Filter records where type == "podcast" and podcast_url is non-null.

Podcast posts are billed at the podcast-post premium event ($2.50/1K, set in the Apify console) because they include a direct audio file URL — useful for media monitoring tools, podcast discovery platforms, and content aggregators that need the actual audio stream. Regular newsletter posts are billed at the standard post-item rate ($1.50/1K).

Monitoring use case

Track a competitor's newsletter for new posts — run daily and filter by post_date to see only new content. Set maxPosts=20 for fast incremental runs.

Use with AI Agents (MCP)

This Substack scraper is callable as a tool by AI agents (Claude Desktop, Cursor, VS Code, n8n, or any MCP-compatible client) via Apify's hosted Model Context Protocol server.

{
  "mcpServers": {
    "apify": {
      "command": "npx",
      "args": [
        "mcp-remote",
        "https://mcp.apify.com/?tools=bovi/substack-publication",
        "--header",
        "Authorization: Bearer <YOUR_APIFY_TOKEN>"
      ]
    }
  }
}

Integrations

Built for newsletter researchers, content agencies, and AI-pipeline teams ingesting Substack post metadata at scale — the JSON/dataset output drops into the tools you already run, no glue code:

• n8n / Make / Zapier — trigger a run or pipe every new dataset item into 500+ apps (Google Sheets, Airtable, Slack, HubSpot, your database) with no code: n8n, Make, Zapier.
• Webhooks — fire your own endpoint the moment a run finishes, to push results straight into your pipeline (docs).
• MCP server — expose this actor as a tool to Claude, Cursor, or any MCP client so an AI agent can pull this data mid-conversation (guide).
• API & SDKs — fetch the dataset as JSON, CSV, or Excel through the Apify REST API or the Python / JS SDKs.

See all Apify integrations.

Usage statistics

This Actor creates a small, content-free summary at the end of each run. It is used only to monitor reliability and improve this Actor. A copy is saved as USAGE_STATS in your own Apify key-value store, so you can see the exact record created for your run.

Set disableUsageStats to true in the input to opt out. Nothing is sent then; your USAGE_STATS record only says that statistics were disabled.

Only these fields are recorded:

• schema version, Actor name and build number;
• UTC start and finish hour (not a precise timestamp);
• run duration, number of results and time to the first result, each as a coarse range;
• whether the result was empty, the end status, and an error type from a fixed list;
• memory setting and counts of charged events;
• names of the input fields you set, never their values;
• the selected option for input fields that offer a fixed list of choices (for example a sort order).

We do not collect input text, search terms, URLs, domains, usernames, email addresses, names, proxy credentials, tokens, scraped records, output items, raw error messages, stack traces, or hashes of any of those values. Records are kept for no longer than 13 months, used only as aggregated operational statistics, and never sold or shared.

Additional fields (Phase 2)

This Actor also records your Apify user ID, whether Apify marks the account as paying, the size range of list inputs, the selected country when the input offers a fixed list of countries, and one category from a fixed Actor taxonomy. We use these fields only for aggregate reliability, repeat-use and cross-Actor analysis; reports suppress any cell with fewer than five distinct users.

The same disableUsageStats: true input flag turns these fields off too. The user ID is removed after 13 months; we do not export, sell, share, or attempt to re-identify this data.

Run-outcome signals (v2)

To learn whether a run did what it was asked to do, the record also holds a few more coarse ranges and yes/no flags. None of them contains content:

• the result limit you asked for (a range, when the input has one) and what share of it was delivered;
• results delivered per input item you listed (a range);
• output quality as ranges: how fully the result fields were filled, the share of rows that look like errors, the share of duplicate rows, and how many different fields appeared. These are counted in memory while results are saved; no result content is kept;
• how the run was started (console, API, schedule, webhook, another Actor);
• how it ended: stopped by you, timed out, reached the requested limit, stopped by the charge limit, and how many times the platform moved the run;
• if this Actor reports it: how many items to process worked or failed (ranges) and one failure reason from a fixed list;
• a short code made from the names of the input fields you set, never their values.

Repeat-run fingerprint (v2)

When your Apify user ID is recorded (see above), the record also holds an 8-character one-way code made from your input (proxy settings left out) and this Actor's name. It only lets us see that the same account ran the same input again soon after an unsatisfying run; we never see the input itself. It is stored only in the database, never published, and reports use it in aggregate with the same five-user minimum. It is the one exception to the statement above that no hashes are collected, and disableUsageStats: true turns it off.