Reddit MCP Server

A unified Apify MCP (Model Context Protocol) server for comprehensive Reddit scraping. This actor provides a single interface to scrape subreddits, comments, and user profiles using browser automation with Playwright.

🚀 Features

Multi-Mode Scraping

This MCP server supports three scraping modes:

1. Subreddit Mode - Scrape posts from Reddit subreddits
2. Comments Mode - Scrape comments from Reddit posts
3. Profile Mode - Scrape user profiles and their posts

Key Capabilities

✅ Unified Interface - Single actor for all Reddit scraping needs
✅ Browser Automation - Bypasses API restrictions using Playwright
✅ No Authentication Required - Scrape public content without login
✅ Comprehensive Data - Extract all relevant fields and metadata
✅ Automatic Pagination - Load multiple pages automatically
✅ NSFW Support - Automatically handles NSFW confirmation dialogs
✅ Structured Output - Clean JSON data ready for AI consumption

📋 Input Parameters

Common Parameters

Parameter	Type	Required	Description
mode	string	Yes	Scraping mode: subreddit, comments, or profile

Subreddit Mode Parameters

Parameter	Type	Default	Description
subreddits	array	-	List of subreddit names (without 'r/' prefix)
maxPosts	integer	25	Maximum posts per subreddit (1-1000)
sort	string	"hot"	Sort method: hot, new, top, controversial
timeFilter	string	"day"	Time filter for top/controversial (hour/day/week/month/year/all)

Comments Mode Parameters

Parameter	Type	Default	Description
postUrls	array	-	List of Reddit post URLs to scrape
maxComments	integer	100	Maximum comments per post (1-10000)
expandThreads	boolean	true	Automatically expand collapsed threads

Profile Mode Parameters

Parameter	Type	Default	Description
usernames	array	-	List of Reddit usernames (without 'u/' prefix)
maxPosts	integer	100	Maximum posts per user (1-1000)
section	string	"submitted"	Profile section: submitted, overview, gilded
sort	string	"new"	Sort method: hot, new, top, controversial

📝 Input Examples

Example 1: Scrape Subreddits

{
  "mode": "subreddit",
  "subreddits": ["python", "programming", "webdev"],
  "maxPosts": 50,
  "sort": "hot",
  "timeFilter": "day"
}

Example 2: Scrape Comments

{
  "mode": "comments",
  "postUrls": [
    "https://www.reddit.com/r/programming/comments/1abc123/interesting_discussion/",
    "https://old.reddit.com/r/python/comments/1def456/another_post/"
  ],
  "maxComments": 200,
  "expandThreads": true
}

Example 3: Scrape User Profiles

{
  "mode": "profile",
  "usernames": ["spez", "example_user"],
  "maxPosts": 100,
  "section": "submitted",
  "sort": "top"
}

📊 Output Format

Subreddit Mode Output

Each post includes:

{
  "subreddit": "python",
  "subreddit_prefixed": "r/python",
  "post_id": "1abc123",
  "post_name": "t3_1abc123",
  "title": "Interesting Python discussion",
  "author": "example_user",
  "selftext": "Post content preview...",
  "score": 456,
  "num_comments": 89,
  "url": "https://old.reddit.com/r/python/comments/...",
  "permalink": "https://old.reddit.com/r/python/comments/...",
  "domain": "self.python",
  "is_self_post": true,
  "link_flair": "Discussion",
  "thumbnail_url": null,
  "created_utc": 1747683628,
  "created_at": "2025-10-31T12:30:00",
  "is_stickied": false,
  "is_locked": false,
  "is_nsfw": false
}

Comments Mode Output

Each comment includes:

{
  "comment_id": "abc123xyz",
  "comment_name": "t1_abc123xyz",
  "author": "example_user",
  "text": "This is a great discussion!",
  "score": 42,
  "awards_count": 2,
  "permalink": "https://old.reddit.com/r/...",
  "post_url": "https://old.reddit.com/r/...",
  "depth": 0,
  "parent_comment_id": null,
  "is_op": false,
  "is_edited": true,
  "is_stickied": false,
  "created_utc": 1728912645,
  "created_at": "2025-10-31T12:30:45"
}

Profile Mode Output

Profile data with posts:

{
  "username": "spez",
  "post_karma": 0,
  "comment_karma": 0,
  "total_karma": 1047690,
  "account_created": "2005-06-06T04:00:00+00:00",
  "posts": [
    {
      "post_id": "abc123",
      "title": "Announcing new features",
      "author": "spez",
      "subreddit": "announcements",
      "score": 15234,
      "num_comments": 1250,
      "url": "https://old.reddit.com/...",
      "created_at": "2025-10-31T12:30:45",
      "is_stickied": true,
      "is_nsfw": false
    }
  ]
}

🎯 Use Cases

Research & Analysis

• Sentiment Analysis - Analyze community opinions across subreddits
• Trend Detection - Track emerging topics and discussions
• User Behavior - Study posting patterns and engagement
• Content Analysis - Build datasets for machine learning

Business Intelligence

• Market Research - Gather user feedback and discussions
• Brand Monitoring - Track mentions and sentiment
• Competitive Analysis - Monitor competitor discussions
• Customer Insights - Understand customer needs and pain points

AI & ML Applications

• Training Data - Build high-quality datasets for AI models
• RAG Systems - Feed Reddit content to retrieval systems
• Chatbot Training - Use conversations for dialogue models
• Content Generation - Analyze successful content patterns

🛠️ Local Development

Prerequisites

pip install -r requirements.txt
playwright install chromium

Create Input File

Create storage/key_value_stores/default/INPUT.json:

{
  "mode": "subreddit",
  "subreddits": ["python"],
  "maxPosts": 10
}

Run Locally

cd Reddit/mcp
apify run

Check Results

Results are saved in storage/datasets/default/

🚀 Deployment

Using Apify CLI

# Login to Apify
apify login

# Push to Apify platform
apify push

Manual Upload

1. Create a new actor on Apify Console
2. Upload all files including Dockerfile, requirements.txt, and .actor/ directory
3. Configure input parameters
4. Run the actor

📚 API Integration

JavaScript/Node.js

const { ApifyClient } = require("apify-client");

const client = new ApifyClient({ token: "YOUR_API_TOKEN" });

const input = {
  mode: "subreddit",
  subreddits: ["python", "programming"],
  maxPosts: 50,
  sort: "hot",
};

const run = await client.actor("YOUR_ACTOR_ID").call(input);
const { items } = await client.dataset(run.defaultDatasetId).listItems();

console.log(`Scraped ${items.length} posts`);

Python

from apify_client import ApifyClient

client = ApifyClient('YOUR_API_TOKEN')

input_data = {
    'mode': 'subreddit',
    'subreddits': ['python', 'programming'],
    'maxPosts': 50,
    'sort': 'hot'
}

run = client.actor('YOUR_ACTOR_ID').call(run_input=input_data)

for item in client.dataset(run['defaultDatasetId']).iterate_items():
    print(f"Post: {item['title']}")
    print(f"Score: {item['score']}")

⚡ Performance Tips

Optimize Speed

• Start with lower maxPosts values for testing
• Use specific subreddits instead of scraping all posts
• Disable expandThreads in comments mode if not needed
• Process fewer URLs/usernames per run

Avoid Rate Limiting

• Add delays between requests (built-in)
• Don't scrape the same content repeatedly
• Respect Reddit's servers - use reasonable limits
• Consider batching requests across multiple runs

⚠️ Limitations

• Public Content Only - Cannot scrape private subreddits or profiles
• No Authentication - Requires public access to content
• Rate Limits - Reddit may throttle excessive requests
• Browser-Based - Slower than direct API but more reliable
• Dynamic Content - Some features may change if Reddit updates layout

🐛 Troubleshooting

No Results Returned

• Verify subreddit/username/URL is correct
• Check if content is public (not private/restricted)
• Try with smaller maxPosts values first
• Review logs for specific error messages

Timeout Errors

• Content may be loading slowly
• Try with fewer items or smaller limits
• Check if Reddit is accessible from your location

Missing Data Fields

• Some fields may be null if not available
• Deleted content shows "[deleted]" for authors
• Hidden scores may show as 0

📄 License

This actor is provided as-is for scraping public Reddit data in accordance with Reddit's terms of service.

🔗 Related Actors

• ../reddit/ - Dedicated subreddit scraper
• ../reddit-comment/ - Dedicated comment scraper
• ../reddit-profile/ - Dedicated profile scraper

💡 Notes

• This MCP server uses browser automation to access Reddit's public interface
• Always respect Reddit's robots.txt and terms of service
• Use responsibly and avoid overwhelming Reddit's servers
• Consider implementing additional rate limiting for large-scale scraping
• The actor works best with the Apify platform's infrastructure

🆘 Support

For issues, questions, or feature requests, please open an issue in the repository or contact support.

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