Scraping Substack Newsletters in 2026: Posts, Authors & Recommendations

Substack newsletters are goldmines of curated content. Investor theses, niche industry analysis, tech deep-dives — some of the best writing on the internet lives behind Substack URLs. But when you need data from dozens of publications at scale, manually copying posts is not an option. I have been scraping Substack data for a few months. Here is what works in 2026, what the limits are, and how to do it programmatically. Substack's Hidden API Substack does not have an official public API, but every publication exposes structured JSON endpoints. The pattern is simple: https://{publication}.substack.com/api/v1/posts?limit=12&offset=0 This returns a JSON array of post objects with titles, subtitles, post dates, slugs, authors, and more. No authentication required for public posts. import httpx def get_substack_posts ( publication , limit = 12 , offset = 0 ): url = f " https:// { publication } .substack.com/api/v1/posts " params = { " limit " : limit , " offset " : offset } resp = httpx . ge