# Substack Scraper: Posts, Comments, Reactions + Sentiment (`dltik/substack-scraper`) Actor Scrape any Substack publication: full post text, comments, replies, reactions, restacks. Built-in sentiment scoring on every item. Multi-publication batch, date filter, audience filter (free/paid/founding). For creator economy research, brand monitoring, PR. $3/1K posts + $5/1K comments. - **URL**: https://apify.com/dltik/substack-scraper.md - **Developed by:** [dltik](https://apify.com/dltik) (community) - **Categories:** AI, Marketing, Social media - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 1 bookmarks - **User rating**: No ratings yet ## Pricing Pay per event 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 Scraper — Posts, Comments, Reactions + AFINN-165 Sentiment > Scrape any **Substack publication**: full post text, comments, nested replies, reactions, restacks. **Built-in AFINN-165 sentiment analysis** on every post and comment — no external API. Multi-publication batch, date filter, audience filter (free/paid/founding). HTTP-only, **$0.003 per post / $0.005 per comment** — the cheapest, cleanest way to monitor newsletters at scale. ⭐ **Bookmark this Substack Scraper** — Apify ranks actors by bookmarks, so it directly helps the visibility of this scraper on the Apify Store. ### What is the Substack Scraper? The **Substack Scraper** is an Apify actor that pulls structured data from any [Substack](https://substack.com/) publication. Drop in a publication URL and get back the full post archive — body text, comments (with full nested reply tree), reactions count, restacks count, paywall status, audience tier (free/paid/founding-only). Every post and every comment is sentiment-scored on the fly using the AFINN-165 lexicon with negation handling. The cheapest, cleanest way to monitor the creator economy at scale: track newsletters in your space, surface high-engagement posts, run brand-mention monitoring across hundreds of Substacks at once. ### Use cases - **Creator-economy research** — track top Substacks in your sector, their post velocity, engagement. - **Brand monitoring** — alert on every Substack post mentioning your brand + sentiment. - **Competitive intelligence** — analyze a competitor's full post archive for content strategy. - **PR / journalism** — find which Substacks cover your industry; monitor for new mentions. - **AI training data** — Substack is high-quality long-form content, labeled with reactions and comments — perfect for RLHF. - **Newsletter benchmarking** — compare engagement (reactions/comments) across Substacks of similar size. - **Content research** — find which post topics drove the most subscriber growth (by audience-tier mix). ### Input ```json { "publications": [ "https://example1.substack.com/", "https://example2.substack.com/" ], "since": "2026-01-01", "includeComments": true, "audienceTiers": ["free", "paid"] } ```` ### Output ```json { "publication": "example1.substack.com", "post_id": "12345678", "url": "https://example1.substack.com/p/example-post", "title": "Why MCP servers are the future of AI agents", "author": "Example Author", "published_at": "2026-04-25", "audience_tier": "free", "body_text": "Full post body text...", "reactions": 423, "restacks": 87, "comments_count": 34, "sentiment": "positive", "sentiment_score": 0.38 } ``` ### Pricing **PAY\_PER\_EVENT — $0.003 per post + $0.005 per comment**. Sentiment analysis included free. ### FAQ — Substack API alternatives **Substack official API?** No public API. This scraper is the way to get structured data at scale. **Paywall content — does it scrape paid posts?** Public preview only (the same content non-subscribers see). Full paid post text requires a logged-in cookie. **Why AFINN-165 sentiment?** Fast, deterministic, runs in microseconds per item, no GPU. For deeper semantic sentiment, run downstream on the dataset. **How fast for bulk?** ~5-10 posts/sec, ~20 comments/sec per actor instance. For 100 publications × 1K posts each, run 4 concurrent actor runs. *** ⭐ **Found this useful? Bookmark this Substack Scraper** — it's the strongest signal for Apify Store ranking. #### Related actors - [Reddit Scraper — Posts + Sentiment](https://apify.com/dltik/reddit-scraper) — same sentiment engine for Reddit - [Trustpilot Scraper — Reviews + Sentiment](https://apify.com/dltik/trustpilot-scraper) — same sentiment engine for reviews - [Amazon Reviews Scraper](https://apify.com/dltik/amazon-reviews-scraper) — same sentiment engine for Amazon License: MIT · Author: [dltik](https://apify.com/dltik) # Actor input Schema ## `publications` (type: `array`): Substack publications to scrape. Subdomain ('lennysnewsletter') or custom domain ('www.astralcodexten.com') or full URL. ## `maxPostsPerPublication` (type: `integer`): Maximum number of posts to scrape per publication. ## `fetchFullBodies` (type: `boolean`): Fetch the full body\_html for each post. Costs +1 request per post but unlocks full text + sentiment analysis. ## `includeComments` (type: `boolean`): Fetch comments for each post. Free posts only — paid posts return no comments. Costs +1 request per post. ## `maxCommentsPerPost` (type: `integer`): Cap comments returned per post (incl. nested replies). ## `sortBy` (type: `string`): new = chronological (newest first), top = most popular. ## `searchKeyword` (type: `string`): Filter posts by keyword (Substack-side search). ## `sinceDate` (type: `string`): Only posts published after this ISO date (e.g. '2026-01-01'). Skipped posts stop the scrape. ## `audienceFilter` (type: `string`): Restrict to free / paid / founding posts. ## `computeSentiment` (type: `boolean`): Run AFINN-165 sentiment analysis on each post and comment. No external API. ## `proxyConfig` (type: `object`): Optional Apify proxy. Substack rarely blocks — only useful if you hit rate limits on heavy runs. ## Actor input object example ```json { "publications": [ "lennysnewsletter" ], "maxPostsPerPublication": 30, "fetchFullBodies": true, "includeComments": false, "maxCommentsPerPost": 100, "sortBy": "new", "computeSentiment": true, "proxyConfig": { "useApifyProxy": false } } ``` # Actor output Schema ## `results` (type: `string`): Substack records. # 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 = { "publications": [ "lennysnewsletter" ] }; // Run the Actor and wait for it to finish const run = await client.actor("dltik/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 '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "publications": ["lennysnewsletter"] } # Run the Actor and wait for it to finish run = client.actor("dltik/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 '{ "publications": [ "lennysnewsletter" ] }' | apify call dltik/substack-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=dltik/substack-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Substack Scraper: Posts, Comments, Reactions + Sentiment", "description": "Scrape any Substack publication: full post text, comments, replies, reactions, restacks. Built-in sentiment scoring on every item. Multi-publication batch, date filter, audience filter (free/paid/founding). For creator economy research, brand monitoring, PR. $3/1K posts + $5/1K comments.", "version": "1.0", "x-build-id": "H2l6dC0q0mBlNsgFk" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/dltik~substack-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-dltik-substack-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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/dltik~substack-scraper/runs": { "post": { "operationId": "runs-sync-dltik-substack-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/dltik~substack-scraper/run-sync": { "post": { "operationId": "run-sync-dltik-substack-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", "required": [ "publications" ], "properties": { "publications": { "title": "Publications", "type": "array", "description": "Substack publications to scrape. Subdomain ('lennysnewsletter') or custom domain ('www.astralcodexten.com') or full URL.", "items": { "type": "string" }, "default": [] }, "maxPostsPerPublication": { "title": "Max posts per publication", "minimum": 1, "maximum": 1000, "type": "integer", "description": "Maximum number of posts to scrape per publication.", "default": 30 }, "fetchFullBodies": { "title": "Fetch full post bodies", "type": "boolean", "description": "Fetch the full body_html for each post. Costs +1 request per post but unlocks full text + sentiment analysis.", "default": true }, "includeComments": { "title": "Include comments", "type": "boolean", "description": "Fetch comments for each post. Free posts only — paid posts return no comments. Costs +1 request per post.", "default": false }, "maxCommentsPerPost": { "title": "Max comments per post", "minimum": 1, "maximum": 5000, "type": "integer", "description": "Cap comments returned per post (incl. nested replies).", "default": 100 }, "sortBy": { "title": "Sort posts by", "enum": [ "new", "top" ], "type": "string", "description": "new = chronological (newest first), top = most popular.", "default": "new" }, "searchKeyword": { "title": "Search keyword", "type": "string", "description": "Filter posts by keyword (Substack-side search)." }, "sinceDate": { "title": "Since date", "type": "string", "description": "Only posts published after this ISO date (e.g. '2026-01-01'). Skipped posts stop the scrape." }, "audienceFilter": { "title": "Audience filter", "enum": [ "everyone", "only_paid", "founding" ], "type": "string", "description": "Restrict to free / paid / founding posts." }, "computeSentiment": { "title": "Compute sentiment", "type": "boolean", "description": "Run AFINN-165 sentiment analysis on each post and comment. No external API.", "default": true }, "proxyConfig": { "title": "Proxy (rarely needed)", "type": "object", "description": "Optional Apify proxy. Substack rarely blocks — only useful if you hit rate limits on heavy runs.", "default": { "useApifyProxy": false } } } }, "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 } } } } } } } } } } ```