📱 Reddit Posts Scraper

🚀 Extract Reddit posts at 1,000+ posts per minute. Pull from subreddits, search queries, or direct URLs with score, comment, flair, domain, and author filters. No login, no API keys.

🎁 Paid plan adds

🧵 Full comment tree

👤 Author profiles

🔞 Safety flags

📈 Virality metrics

The Reddit Posts Scraper collects post data from any public subreddit, search query, or direct Reddit URL. Each record includes title, full text, author, score, upvote ratio, comment count, creation date, domain, flair, media flags, and awards. Runs return 1,000+ posts per minute on residential proxy, making it practical for trend analysis, content research, and ongoing monitoring at scale.

The Actor supports three input methods (subreddit names, search queries, and direct URLs), six sort modes (hot, new, top, rising, controversial, relevance), and seven time windows (hour, day, week, month, year, all, default). Filters let you narrow by score range, comment count, flair, domain, and author before results hit the dataset.

🎯 Target Audience	💡 Primary Use Cases
Market researchers, data analysts, social media managers, content creators, brand teams, academic researchers	Trend analysis, sentiment monitoring, competitive research, content discovery, community tracking, public-discourse datasets

📋 What the Reddit Posts Scraper does

Three input methods, combinable in a single run:

• 📋 Subreddit mode. Provide subreddit names (without the r/ prefix) to pull posts from each community.
• 🔍 Search mode. Enter search queries to find posts across all of Reddit, or scoped to a specific subreddit.
• 🔗 URL mode. Paste direct Reddit URLs (subreddit pages, search URLs, or individual post URLs).

Each post record includes title, self-text, author, subreddit, score, upvote ratio, comment count, creation date, permalink, domain, flair, NSFW/spoiler/stickied flags, media flags, gallery status, and award count.

💡 Why it matters: manually browsing Reddit for trends, mentions, or competitor discussions is slow and doesn't scale. This Actor collects structured post data on demand, ready for CSV export, dashboard ingestion, or CRM enrichment.

📊 Data fields

Each record includes: archived, author, authorFlair, authorId, awards, contentCategories, contentType, controversyScore, createdAt, createdUtc, distinguished, domain, engagementRate, estimatedViews, id, isCrosspost, isGallery, isOriginalContent, isSelf, isVideo, linkFlairText, locked, numComments, over18, parsedId, permalink, postAgeHours, postFlair, postedDay, postedHour, previewImages, score, scrapedAt, selfText, selfTextHtml, spoiler, stickied, subreddit, subredditId, thumbnail. All 40 field names come from a real production run, so what you see here is what lands in your dataset.

⚠️ Good to Know: residential proxies are required when running on Apify. Reddit blocks datacenter IPs, so the scraper will fail without proper proxy configuration. The proxy input is already pre-filled with the recommended settings.

🚀 How to use

1. 📝 Sign up. Create a free account with $5 credit (takes 2 minutes).
2. 🌐 Open the Actor. Go to the Reddit Posts Scraper page on the Apify Store.
3. 🎯 Set input. Add subreddits, search queries, or URLs. Pick a sort mode, set filters, and set maxItems.
4. 🚀 Run it. Click Start and let the Actor collect your data.
5. 📥 Download. Grab your results in the Dataset tab as CSV, Excel, JSON, or XML.

⏱️ Total time from signup to downloaded dataset: 3-5 minutes. No coding required.

🔗 MCP Connector integrations

Pipe each scraped Reddit post directly into your tools via the Model Context Protocol. No code, no API keys to manage. Authorize a connector once via OAuth in the Apify Console and the actor sends data to your account automatically.

Officially supported services

Service	URL to paste in the connector wizard	Use case
📝 Notion	https://mcp.notion.com/mcp	Research log — each Reddit post becomes a sub-page in your Notion workspace with full title, body, author and stats
📋 Linear	https://mcp.linear.app/sse	Feedback queue — each post becomes an issue in your Linear team, ready to triage
📊 Airtable	https://mcp.airtable.com/mcp	Mention tracking — each post becomes a row in a base with structured columns you can filter, sort, and analyze
⚙️ Apify	https://mcp.apify.com	Actor chaining — each post triggers another Apify Actor (sentiment analysis, translation, enrichment, screenshot, etc.)

Setting up Notion

1. Create a target page in Notion (e.g. "Reddit Research")
2. Open that page → ••• (top right) → Connections → connect your Apify integration
3. Copy the full page URL
4. In Apify Console → input form → click + on 🔗 MCP Connector → paste https://mcp.notion.com/mcp → click Authorize → login with Notion → allow access
5. Run the actor with:
   • 🔗 MCP Connector: the new "Notion" connector
   • 🔗 Mode: 📄 One entry per post
   • 🔗 Target page: paste the Notion page URL
   • 🔗 Message (optional): leave empty for a rich default template with headings, blockquote, bullets

Setting up Linear

1. In Apify Console → click + on 🔗 MCP Connector → paste https://mcp.linear.app/sse → Authorize → grant access to your workspace
2. In Linear, decide which team should receive the issues and copy that team's URL (looks like https://linear.app/<workspace>/team/<TEAM_KEY>)
3. Run the actor with:
   • 🔗 MCP Connector: the new "Linear" connector
   • 🔗 Mode: 📄 One entry per post
   • 🔗 Target page: paste the Linear team URL (the actor extracts the team key automatically)

Each scraped post becomes a new Linear issue with the post title as the issue title and the Markdown-formatted body as the description.

Setting up Airtable

Airtable requires a one-time setup of the destination table with specific column names.

1. Sign up at airtable.com (free tier works)
2. Create a new base → in the first table, configure these 8 columns exactly (case-sensitive):

Column name	Type
Title	Single line text
Author	Single line text
Subreddit	Single line text
Score	Number (integer)
Comments	Number (integer)
URL	URL
CreatedAt	Single line text or Date
SelfText	Long text

3. Copy the full URL of the table (looks like https://airtable.com/appXXXXXXXX/tblYYYYYYYY/viwZZZZZZZZ) — the actor extracts baseId and tableId from it
4. In Apify Console → click + on 🔗 MCP Connector → paste https://mcp.airtable.com/mcp → Authorize → grant access to your workspace
5. Run the actor with:
   • 🔗 MCP Connector: the new "Airtable" connector
   • 🔗 Mode: 📄 One entry per post
   • 🔗 Target page: paste the table URL

Each scraped post appears as a new row.

Setting up Apify (actor chaining)

Trigger another Apify Actor for every scraped post — useful for enrichment pipelines (e.g. run a sentiment analysis actor on each post's text, or feed each URL into a deep-scraping actor).

1. In Apify Console → click + on 🔗 MCP Connector → paste https://mcp.apify.com → Authorize (uses your existing Apify token, no extra OAuth)
2. Decide which actor you want to call per post. Browse https://apify.com/store and copy its identifier (e.g. apify/rag-web-browser or your-username/sentiment-analyzer)
3. Run the actor with:
   • 🔗 MCP Connector: the new "Apify" connector
   • 🔗 Mode: 📄 One entry per post
   • 🔗 Target page: the target actor ID (e.g. apify/rag-web-browser)
   • 🔗 Tool name override: call-actor (required — Apify MCP exposes many tools, this picks the right one)

Each scraped post fires a run of the target actor with {url, title, query, text, post} as input. The run is fire-and-forget (waitSecs: 0) so the scraper finishes fast even if downstream actors are slow.

Power user: custom format

The actor also accepts any other MCP server URL — fill the advanced fields:

• 🔗 Custom template — write Markdown using {{post.title}}, {{post.url}}, {{post.author}}, {{post.score}}, {{post.numComments}}, {{post.subreddit}}, {{post.permalink}}, {{post.selfText}}, {{post.createdAt}}, {{post.domain}} placeholders
• 🔗 Tool name override — bypass auto-detection and pick a specific MCP tool name
• 🔗 Arguments JSON override — provide the full argument shape literally (e.g. with custom Airtable column names, Linear teamId, Notion's rich_text blocks)

🔗 Recommended Actors

• 📸 Instagram Posts Scraper - Posts, captions, and engagement from public Instagram profiles
• 👤 Instagram Profile Scraper - Bio, follower counts, verification, and profile metadata
• 🐦 X.com Tweets Scraper - Tweet data, engagement metrics, and author details
• 📰 PR Newswire Scraper - Press releases and news articles for media monitoring
• 💼 HubSpot Marketplace Scraper - Business app data for market research

💡 Pro Tip: browse the complete ParseForge collection for more data scrapers.

How to enable MCP enrichment

Inside the input form, scroll to the ✨ Enrichment section and follow these steps:

1. Toggle on the Enrich Output checkbox.
2. Pick a connector in the Enrichment Connector dropdown. If you don't have one yet, click the + button, paste the URL https://api.trendsmcp.ai/mcp, and paste your bearer token from trendsmcp.ai.
3. Run the actor. Every scraped item gets an extra enrichment object with cross-platform momentum curves (Google, YouTube, Amazon), 1-month and 12-month growth rates, and a trend state classification (rising / stable / declining).

The enrichment is cached per unique key (subreddit or hashtag), so a 100-item run from the same source costs only one batch of API calls. Get a free API key (100 requests per month, no credit card) at trendsmcp.ai.

⚠️ Disclaimer: this Actor is an independent tool and is not affiliated with, endorsed by, or sponsored by Reddit, Inc. or any of its subsidiaries. All trademarks mentioned are the property of their respective owners. Only publicly available post data is collected.

🆘 Need Help?

If you hit a bug, have questions about setup, or need a scraper we haven't built yet, open our contact form or write to parseforge@protonmail.com. We also take on paid custom data projects.

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