Reddit Insights MCP

Semantic search across millions of Reddit posts. Unlike keyword search, this understands intent and meaning.

Setup

1. Get API Key (free tier available)

•Sign up at https://reddit-insights.com
•Go to Settings → API
•Copy your API key

2. Install MCP Server

For Claude Desktop - add to claude_desktop_config.json:

json

{
  "mcpServers": {
    "reddit-insights": {
      "command": "npx",
      "args": ["-y", "reddit-insights-mcp"],
      "env": {
        "REDDIT_INSIGHTS_API_KEY": "your_api_key_here"
      }
    }
  }
}

For Clawdbot - add to config/mcporter.json:

json

{
  "mcpServers": {
    "reddit-insights": {
      "command": "npx reddit-insights-mcp",
      "env": {
        "REDDIT_INSIGHTS_API_KEY": "your_api_key_here"
      }
    }
  }
}

Verify installation:

bash

mcporter list reddit-insights

Available Tools

Tool	Purpose	Key Params
`reddit_search`	Semantic search across posts	`query` (natural language), `limit` (1-100)
`reddit_list_subreddits`	Browse available subreddits	`page`, `limit`, `search`
`reddit_get_subreddit`	Get subreddit details + recent posts	`subreddit` (without r/)
`reddit_get_trends`	Get trending topics	`filter` (latest/today/week/month), `category`

Performance Notes

•
Response time: 12-25 seconds (varies by query complexity)
- •Simple queries: ~12-15s
- •Complex semantic queries: ~17-20s
- •Heavy load periods: up to 25s
•Best results: Specific products, emotional language, comparison questions
•Weaker results: Abstract concepts, non-English queries, generic business terms
•Sweet spot: Questions a real person would ask on Reddit

Best Use Cases (Tested)

Use Case	Effectiveness	Why
Product comparisons (A vs B)	⭐⭐⭐⭐⭐	Reddit loves debates
Tool/app recommendations	⭐⭐⭐⭐⭐	High-intent discussions
Side hustle/money topics	⭐⭐⭐⭐⭐	Engaged communities
Pain point discovery	⭐⭐⭐⭐	Emotional posts rank well
Health questions	⭐⭐⭐⭐	Active health subreddits
Technical how-to	⭐⭐⭐	Better to search specific subreddits
Abstract market research	⭐⭐	Too vague for semantic search
Non-English queries	⭐	Reddit is English-dominant

Query Strategies (Tested with Real Data)

✅ Excellent Queries (relevance 0.70+)

Product Comparisons (best results!):

code

"Notion vs Obsidian for note taking which one should I use"
→ Relevance: 0.72-0.81 | Found: Detailed comparison discussions, user experiences

"why I switched from Salesforce to HubSpot honest experience"  
→ Relevance: 0.70-0.73 | Found: Migration stories, feature comparisons

Side Hustle/Money Topics:

code

"side hustle ideas that actually make money not scams"
→ Relevance: 0.70-0.77 | Found: Real experiences, specific suggestions

Niche App Research:

code

"daily horoscope apps which one is accurate and why"
→ Relevance: 0.67-0.72 | Found: App recommendations, feature requests

✅ Good Queries (relevance 0.60-0.69)

Pain Point Discovery:

code

"I hate my current CRM it is so frustrating"
→ Relevance: 0.60-0.64 | Found: Specific CRM complaints, feature wishlists

"cant sleep at night tried everything what actually works"
→ Relevance: 0.60-0.63 | Found: Sleep remedies discussions, medical advice seeking

Tool Evaluation:

code

"AI tools that actually save time not just hype"
→ Relevance: 0.64-0.65 | Found: Real productivity gains, tool recommendations

❌ Weak Queries (avoid these patterns)

Too Abstract:

code

"business opportunity growth potential"
→ Relevance: 0.52-0.58 | Returns unrelated generic posts

Non-English:

code

"学习编程最好的方法" (Chinese)
→ Relevance: 0.45-0.51 | Reddit is English-dominant, poor cross-lingual results

Query Formula Cheat Sheet

Goal	Pattern	Relevance
Compare products	"[Product A] vs [Product B] which should I use"	0.70-0.81
Find switchers	"why I switched from [A] to [B]"	0.70-0.73
Money/hustle topics	"[topic] that actually [works/makes money] not [scam/hype]"	0.70-0.77
App recommendations	"[category] apps which one is [accurate/best] and why"	0.67-0.72
Pain points	"I hate my current [tool] it is so [frustrating/slow]"	0.60-0.64
Solutions seeking	"[problem] tried everything what actually works"	0.60-0.63

Response Fields

Each result includes:

•title, content - Post text
•subreddit - Source community
•upvotes, comments - Engagement metrics
•relevance (0-1) - Semantic match score (0.5+ is good, 0.6+ is strong)
•sentiment - Discussion/Q&A/Story Sharing/Original Content/News
•url - Direct Reddit link

Example response:

json

{
  "id": "1oecf5e",
  "title": "Trying to solve the productivity stack problem",
  "content": "The perfect productivity app doesn't exist. No single app can do everything well, so we use a stack of apps. But this creates another problem: multi app fragmentation...",
  "subreddit": "productivityapps",
  "upvotes": 1,
  "comments": 0,
  "relevance": 0.631,
  "sentiment": "Discussion",
  "url": "https://reddit.com/r/productivityapps/comments/1oecf5e"
}

Tips

•Natural language works best - Ask questions like a human would
•Include context - "for small business" or "as a developer" improves results
•Combine emotion words - "frustrated", "love", "hate", "wish" find stronger opinions
•Filter by engagement - High upvotes/comments = validated pain points
•Check multiple subreddits - Same topic discussed differently in r/startups vs r/smallbusiness

Example Workflows

Find SaaS opportunity:

•reddit_search: "frustrated with project management tools for remote teams"
•Filter results with high engagement
•Identify recurring complaints → product opportunity

Validate idea:

•reddit_search: "[your product category] recommendations"
•See what alternatives people mention
•Note gaps in existing solutions

Content research:

•reddit_get_subreddit: Get posts from target community
•reddit_search: Find specific questions/discussions
•Create content answering real user questions