Reddit Insights MCP

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

Ecommerce Seller Research Workflow (Deliverable)

Goal: produce a market research / pain-point opportunity report for ecommerce sellers.

1) Define scope

• Category seed(s): category / niche / use case (e.g., "under desk treadmill", "portable blender", "pet grooming")
• Target persona: who is buying/using (e.g., new parents, renters, office workers)
• Price band: low/mid/high (optional)
• Geography / constraints: US/EU, small apartment, travel, etc. (optional)

2) Tool decision flow

• If you already know what to search:
  • Use reddit_search
• If you need communities first:
  • Use reddit_list_subreddits → pick 3-10 relevant subs
  • Then reddit_get_subreddit on 2-3 key subs to understand what’s being discussed
• If you need what’s hot right now:
  • Use reddit_get_trends → convert trends into reddit_search queries

3) Execute searches (batch)

• Run 6-15 reddit_search queries covering:
  • complaints / failures / returns
  • comparisons / alternatives
  • “best” / recommendations
  • “worth it” / regret / buyer’s remorse
  • gifts / seasonal intent

4) Filter + cluster

• Keep results where relevance >= 0.60 (0.55-0.59 only as supporting context)
• Prioritize evidence with engagement signals:
  • Upvotes and/or comments are non-trivial (relative to the subreddit)
• Cluster posts into themes:
  • complaints about quality/durability
  • usability/friction
  • missing features/accessories
  • sizing/fit/compatibility
  • shipping/packaging/returns
  • safety/health concerns

5) Produce the output document

• Use the formats below.
• Requirement:
  • “原句” uses English with Chinese in parentheses.
  • All other fields are Chinese.

Output Document Formats

机会点（Pain-point Opportunities）

Rules:

• “场景+抱怨” should be concrete (who/where/when + what went wrong).
• “设计机会点” should translate the complaint into a solution direction (not a full product spec).
• “原句” should be verbatim from the post/comment when possible.

趋势产品（Trending Products）

Rules:

• “产品名称” should be the common name used by users (include brand if repeatedly mentioned).
• “说明（卖点）” should be based on what users praise (time-saving, compact, durable, etc.).
• “证据原句” should be verbatim from the post/comment when possible, and should support the stated selling point.
• If a product has multiple evidence posts, put multiple links in the same “帖子链接” cell using line breaks (e.g., link1<br>link2<br>link3).

Ecommerce Query Playbook

Use natural-language queries a real shopper would write.

Category opportunity (complaints / gaps)

• "I hate my [product] because it keeps breaking"
• "[product] is so frustrating to use"
• "what do you wish [product] had"
• "returned my [product] because"
• "[product] alternatives that actually work"
• "problems with [product] for small apartment"

Buyer intent (recommendations / comparisons)

• "best [product] under $[X]"
• "[brand A] vs [brand B] which should I buy"
• "is [product] worth it"
• "buy it for my [persona]" (e.g., baby, dog, elderly parent)

Trend discovery (what’s being adopted)

• "what did you buy recently that you love"
• "products that actually improved my [routine]"
• "gift ideas for [persona] that people actually use"

Notes for Ecommerce Sellers

• Reddit evidence is strongest for:
  • comparisons, switching stories, and candid complaints
• Be careful with:
  • regulated categories (health claims, safety)
  • one-off viral posts (validate across multiple posts/subreddits)

Setup

1. Get API Key (free tier available)

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

2. Install MCP Server

For Claude Desktop - add to claude_desktop_config.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:

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

Verify installation:

mcporter list reddit-insights

Available Tools

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)

Query Strategies (Tested with Real Data)

✅ Excellent Queries (relevance 0.70+)

Product Comparisons (best results!):

"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:

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

Niche App Research:

"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:

"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:

"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:

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

Non-English:

"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

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:

{
  "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

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

Example Workflows

Find SaaS opportunity:

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

Validate idea:

1. reddit_search: "[your product category] recommendations"
2. See what alternatives people mention
3. Note gaps in existing solutions

Content research:

1. reddit_get_subreddit: Get posts from target community
2. reddit_search: Find specific questions/discussions
3. Create content answering real user questions