👽 Reddit Scraper: Posts, Comments & Search (No Login)

Overview

Reddit Scraper is a no-login tool that extracts public Reddit data four ways (by subreddit, search query, user history, or specific post URLs) and returns it as clean, structured records with full nested comment trees. Pick a mode, add a target, and get back structured JSON or CSV.

Every post record carries title, author, score, upvote ratio, flair, comment count, and every comment thread as deep as you want. No login, no cookies, no OAuth app required, though you can plug in your own Reddit client ID for higher limits.

Reliability posture: only a successfully delivered post record is billed under the post-scraped event. Blocked fetches, empty listings, and failed posts are never charged, you only pay for what actually lands in your dataset.

✅ No login required | ✅ No API key | ✅ Pay only for results | ✅ MCP-ready for AI agents

Features

Four extraction modes. Subreddit, search, user history, or specific post URLs. Full comment trees. Fetch nested replies to any depth per post. Deep historical backfill. Cursor-based pagination lets you resume long runs. All Reddit sorts. Hot, new, top, and rising, with timeframe scoping for top. Optional client ID. Plug in your own Reddit OAuth client ID to raise the shared rate limit.

How it works

Reddit's public browsing is rate-limited and its data endpoints are increasingly gated. This scraper reads public posts and comments the way a logged-out visitor does. No account, no cookies.

Choose a mode: subreddit (pull hot, new, top, or rising posts from any public sub), search (Reddit's full search syntax), user (a user's public post history), or post (specific URLs). The actor handles pagination for you and exposes an after cursor so you can resume long runs and do deep historical backfill across thousands of posts.

🧾 Input configuration

{
  "mode": "subreddit",
  "subreddits": ["python"],
  "sortBy": "top",
  "timeframe": "week",
  "maxPosts": 25,
  "includeComments": true,
  "maxCommentsPerPost": 100,
  "maxDepth": 3
}

📤 Output format

This is a real record delivered by a live run against r/Python (sort=top, timeframe=week):

{
  "id": "1uts313",
  "name": "t3_1uts313",
  "subreddit": "Python",
  "subreddit_id": "t5_2qh0y",
  "title": "What Every Python Developer Should Know About the CPython ABI",
  "author": "mttd",
  "author_fullname": "t2_6gkbb",
  "score": 73,
  "upvote_ratio": 0.86,
  "url": "https://www.reddit.com/r/Python/comments/1uts313/what_every_python_developer_should_know_about_the/",
  "permalink": "https://www.reddit.com/r/Python/comments/1uts313/what_every_python_developer_should_know_about_the/",
  "selftext": "It's true that you can happily write Python for years without needing to understand any of the content of this post... https://labs.quansight.org/blog/python-abi-abi3t",
  "is_self": true,
  "domain": "self.Python",
  "flair": "Resource",
  "num_comments": 20,
  "created_utc": 1783795286,
  "is_pinned": false,
  "is_locked": false,
  "awards_count": 0,
  "scraped_at": "2026-07-15T04:13:41.202Z",
  "comments": [
    {
      "id": "owy9ttz",
      "name": "t1_owy9ttz",
      "author": "No_Art_1022",
      "body": "I hit this wall hard when packaging a numpy-heavy ML pipeline for deployment. Built it locally on my M1 Mac, wheels installed fine, but the same package segfaulted instantly on our Linux CI runners...",
      "score": 24,
      "created_utc": 1783799557,
      "is_submitter": false,
      "depth": 0,
      "replies": [
        {
          "id": "owyxwxx",
          "name": "t1_owyxwxx",
          "author": "TronnaLegacy",
          "body": "Don't most popular libraries with extensions provide the binaries (via wheels if I recall)? Why would you be compiling yourself?",
          "score": 12,
          "created_utc": 1783806942,
          "is_submitter": false,
          "depth": 1,
          "replies": []
        }
      ]
    }
  ]
}

Post records carry these fields:

Field	Description
🆔 id / name	Reddit post ID (t3_...)
📚 subreddit / subreddit_id	Subreddit name and t5 ID
🏷️ title	Post title
👤 author	Author username
⬆️ score / upvote_ratio	Score and ratio
🌐 url / 🔗 permalink	Post URL and permalink
📝 selftext	Body text (self posts)
🎫 flair	Post flair
💬 num_comments	Total comment count
🕒 created_utc	Unix timestamp
📌 is_pinned / 🔒 is_locked	Status flags
🌳 comments[]	Optional nested comment array
🕓 scraped_at	ISO 8601 extraction timestamp

💼 Common use cases

Market and product research Mine subreddits and search for what users actually say about a topic or product. Track how sentiment shifts around a launch or a competitor.

Sentiment analysis at scale Collect posts and full comment trees to score opinion across a category. Feed clean text into your LLM or classifier without cleanup work.

Community monitoring Track a subreddit's hot, new, or top feed on a schedule. Flag surges in mentions or new threads about your brand.

AI training and RAG data Build structured post-and-comment datasets for agents and models. Backfill deep history with the cursor and re-run to keep it fresh.

🚀 Getting started

1. Open the actor on Apify and click Try for free.
2. Choose a mode: subreddit, search, user, or post.
3. Fill the matching field: subreddits, search query, Reddit username, or post URLs.
4. Set max posts, choose a sort (and timeframe for top), and optionally enable Include comments with max comment depth.
5. Click Save and Start, then download your data as JSON, CSV, or Excel, or pull it via API or MCP.

FAQ

Do I need a Reddit login or API key? No. The scraper reads public posts and comments without an account or cookies. You can optionally add your own Reddit OAuth client ID to raise the shared rate limit, but it is not required.

How deep can I go into comment threads? As deep as you set. Enable Include comments, then use max comment depth (1 for top-level only, up to 10) and max comments per post to control how much of each tree you pull. Replies nest inside each comment's replies[] array.

Can I resume a long run or backfill history? Yes. Each run's summary includes an after cursor. Paste it into the pagination cursor field on the next run to continue where you left off for deep historical backfill.

Which sort options are supported? Hot, new, top, and rising. When you choose top, pick a timeframe (hour, day, week, month, year, or all) to scope the window.

Is it legal to scrape Reddit? The actor collects only publicly available posts and comments and never accesses private content. Public data can include personal data under laws like the GDPR, so scrape only what you have a legitimate reason to use.

Can I use it inside an AI agent? Yes. It is exposed as an MCP tool. See below.

Use in Claude, ChatGPT & any MCP agent

https://mcp.apify.com/?tools=themineworks/reddit-scraper

Or call it programmatically with the Apify client:

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: 'YOUR_APIFY_TOKEN' });

const run = await client.actor('themineworks/reddit-scraper').call({
  mode: 'subreddit',
  subreddits: ['python'],
  sortBy: 'top',
  timeframe: 'week',
  maxPosts: 25,
  includeComments: true,
  maxDepth: 3,
});

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

🛠️ Complete your social intelligence pipeline

Pair Reddit with the rest of the social suite:

• Instagram Profile Scraper: followers, bio, and stats for any public account.
• Twitter / X Scraper: tweets by keyword or handle, no paid API key.
• Threads Scraper: posts, profiles, hashtags and search on Meta Threads.

Typical flow: Reddit surfaces the deep, high-quality discussions, Twitter/X and Threads catch real-time bursts, Instagram covers creator activity.

Found a bug or have a feature request? Open an issue on the actor's Apify Console page or reach out through the Apify profile.