Reddit Scraper - Neatrat ⚡

🚀 High-speed Reddit scraping. No API limits. No proxy needed. Pay only for results.

Get fresh Reddit posts, comments, subreddits, user pages, popular feeds, leaderboards, and search results as clean structured JSON, without touching the Reddit API, without managing proxies, and without paying for compute time you didn't use.

Built for developers, marketers, researchers, data teams, and AI agents who just want Reddit data to show up, correct and on time.

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Why Neatrat's Reddit Scraper?

• ⚡ High-speed. Runs finish in seconds, not minutes. Tuned to be the fastest Reddit scraper on Apify.
• 🔓 No API limits. Skip Reddit's rate limits, quotas, and app-registration paperwork.
• 🌐 No proxy needed. Residential proxies are included. Nothing to buy, configure, or rotate.
• 💸 Pay only for results. Flat $3 per 1,000 stored items. No per-hour compute surprises. Blocked responses are never billed.
• 🧼 Clean input. Paste a Reddit link or a keyword. Done. No twenty toggles to learn.
• 🔎 Auto URL detection. Posts, comments, subreddits, users, searches, r/popular, and leaderboards all handled from one list.
• 🤖 AI-agent friendly. The same engine is exposed as an MCP (Model Context Protocol) server, so agents in Claude Desktop, Cursor, and VS Code can call Reddit scraping as a native tool.
• 🪶 Lean runtime. 512 MB is all it needs, which keeps Apify compute charges minimal on every plan.

What you can scrape

You give us	You get
A post URL	Full post with title, body, metadata, and expandable comment threads
A comment permalink	The comment with its ancestor context and replies
A subreddit URL	Post listings, with pagination and sort control
A user URL	Profile, submitted posts, or comment history
A search URL	Search results across Reddit or scoped to one subreddit
r/popular or subreddits/leaderboard	Trending posts or trending communities
Keywords	Keyword search across posts, communities, and users

Everything comes back as structured JSON, one item at a time, straight to the Apify dataset. Stream it into Make, Zapier, n8n, Google Sheets, a webhook, or your own pipeline.

Pricing

$3 per 1,000 stored items. That's the whole price.

• Residential proxies included.
• Live Reddit fetches included.
• Dataset delivery included.
• No hidden compute upcharge.
• Blocked responses are never billed - they're skipped and counted in the run summary.

Free trial for Apify users

Not on a paid plan yet? Kick the tires for free:

• 5 lifetime runs
• 500 lifetime stored results

When you hit the limit the actor exits cleanly and points you to a paid plan. No credit-card surprises, no partial charges.

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How to use it

You can combine direct URLs and keyword searches in the same run.

Option 1 - Drop in Reddit URLs

Just paste the URLs. The actor figures out the rest.

{
  "startUrls": [
    { "url": "https://www.reddit.com/r/programming/" },
    { "url": "https://www.reddit.com/r/programming/comments/173viwj/" },
    { "url": "https://www.reddit.com/user/spez" },
    { "url": "https://www.reddit.com/r/popular/" }
  ]
}

Option 2 - Search by keyword

{
  "searchTerms": ["typescript", "bun runtime"],
  "searchTypes": ["posts", "communities"],
  "withinSubreddit": "programming",
  "searchSort": "new",
  "timeFilter": "week"
}

searchTypes accepts any combination of "posts", "communities", "users".

Option 3 - Full-depth post crawl

Turn any post listing into a deep scrape that follows every post into its full comment thread:

{
  "startUrls": [{ "url": "https://www.reddit.com/r/generativeAI/" }],
  "crawlComments": true,
  "maxPosts": 10,
  "maxCommentsPerPost": 50
}

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Input reference

Field	Type	Default	What it does
startUrls	{ url }[]	-	Reddit URLs to scrape. Posts, comments, subreddits, users, searches, popular, leaderboard.
searchTerms	string[]	-	Keywords to search for.
searchTypes	("posts" | "communities" | "users")[]	["posts"]	Which surfaces each keyword hits.
withinSubreddit	string	null	Restrict keyword post search to one subreddit (e.g. programming).
searchSort	"relevance" | "new" | "comments" | "top"	"new"	Sort order for keyword post search.
timeFilter	"all" | "hour" | "day" | "week" | "month" | "year"	"all"	Time window for searches and top/controversial sorts.
postSort	"hot" | "new" | "top" | "rising" | "controversial"	"hot"	Sort for subreddit listings when the URL doesn't specify one.
crawlComments	boolean	false	Treat post listings as discovery and fetch full comments for every post.
pages	integer	1	Listing pages to follow. For posts, this is how many extra comment expansion rounds to run.
includeNsfw	boolean	true	When false, NSFW items are filtered out before billing.
maxItems	integer	100	Total dataset cap for the whole run.
maxPosts	integer	25	Cap per post-style listing.
maxComments	integer	100	Global cap on nested comments stored across all full-post fetches.
maxCommentsPerPost	integer	20	Per-post cap on nested comments.
maxCommunities	integer	10	Cap for community search and leaderboard.
maxUsers	integer	25	Cap for user search.
requestTimeoutSecs	integer	45	Per-request timeout.

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Example inputs

Single subreddit feed

{
  "startUrls": [{ "url": "https://www.reddit.com/r/programming/" }],
  "maxPosts": 25,
  "maxItems": 25
}

One post with deep comment expansion

{
  "startUrls": [
    { "url": "https://www.reddit.com/r/programming/comments/173viwj/" }
  ],
  "pages": 3,
  "maxCommentsPerPost": 200,
  "maxItems": 1
}

Keyword search scoped to one subreddit

{
  "searchTerms": ["typescript"],
  "searchTypes": ["posts"],
  "withinSubreddit": "programming",
  "searchSort": "new",
  "timeFilter": "week",
  "maxPosts": 50,
  "maxItems": 50
}

Discovery plus full-post crawl

{
  "startUrls": [{ "url": "https://www.reddit.com/r/generativeAI/" }],
  "crawlComments": true,
  "maxPosts": 10,
  "maxCommentsPerPost": 50,
  "maxItems": 10
}

Mixed run

{
  "startUrls": [
    { "url": "https://www.reddit.com/r/popular/" },
    { "url": "https://www.reddit.com/user/spez" }
  ],
  "searchTerms": ["apify", "neatrat"],
  "searchTypes": ["posts", "communities"],
  "maxPosts": 15,
  "maxCommunities": 5,
  "maxItems": 120
}

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Output shape

Every dataset item carries a dataType and a sourceType so downstream pipelines can filter cleanly even when one run mixes post results, community previews, and user search hits.

Typical dataType values:

• post: full post with comments
• comment-permalink: a comment with ancestor context
• communityDetails: subreddit about-box
• userProfile: user about-box
• postPreview: one item from a post listing
• commentPreview: one item from a user comment listing
• communityPreview: one item from community search or leaderboard
• userPreview: one item from user search

Listing routes are flattened (one dataset item per preview). Single-resource routes store one item. When crawlComments is on, raw previews are dropped so you only pay for the full-comment post objects.

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Good use cases

• Marketing: track brand mentions, watch competitors, monitor product subreddits, find influencers.
• Research: pull public discussions about a topic, sample comment sentiment, build datasets.
• Analytics: snapshot subreddit activity over time, feed BI dashboards.
• AI / LLM teams: build RAG corpora from niche subreddits, keep LLM context fresh, ground agents with live Reddit signal.
• Community & growth: spot trending threads in your niche, catch support questions fast.

For AI agents and MCP users

This scraper also ships as an MCP (Model Context Protocol) server, so AI agents in Claude Desktop, Cursor, VS Code, and other MCP-capable clients can call Reddit scraping as a native tool.

If you're building an agent and want it wired in as an MCP tool, reach out through the contact channel on the Apify store page and we'll share the MCP endpoint.

For everyone else, this Apify actor is the simplest way to turn Reddit into clean structured data without thinking about APIs, proxies, or rate limits.

Support

Questions, feature requests, or custom use cases? Reach out through the Apify store page and we'll get back fast.