
Reddit Research Mcp
- 221 repo stars
- Updated July 24, 2026
- king-of-the-grackles/reddit-research-mcp
reddit-research-mcp is an MCP server that converts Reddit discussions into structured research insights with full citations for agent-driven audience and problem discovery.
About
Reddit Research MCP turns Reddit’s unstructured discussions into structured, fully cited insights you can pull from Claude Code, Cursor, or other MCP clients using the PyPI package reddit-research-mcp (uvx runtime hint, version 1.0.1). developers in the Idea phase use it to learn how audiences describe problems, alternatives, and willingness to pay before writing a landing page or roadmap. It also supports competitor subreddit listening and Validate scope checks when threads contradict your assumptions. Beginner-friendly setup via stdio MCP contrasts with the judgment needed to sample threads fairly and avoid anecdote-driven decisions. The server is a research integration, not a moderation or posting bot—expect synthesis and citations, not automated marketing spam. Register uvx/PyPI per your host docs and pair outputs with interviews or analytics before shipping.
- Structures noisy Reddit threads into research-ready insights
- Full citations so claims trace back to posts and comments
- MCP server installable via PyPI reddit-research-mcp with uvx runtime hint
- Version 1.0.1 stdio transport for Claude Code–style workflows
- Purpose-built for research sessions, not generic subreddit scraping dumps
Reddit Research Mcp by the numbers
- Data as of Jul 25, 2026 (Skillselion catalog sync)
claude mcp add reddit-research-mcp -- uvx reddit-research-mcpAdd your badge
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| repo stars | ★ 221 |
|---|---|
| Package | reddit-research-mcp |
| Transport | STDIO |
| Auth | None |
| Last updated | July 24, 2026 |
| Repository | king-of-the-grackles/reddit-research-mcp ↗ |
What it does
Run cited Reddit research from your agent to hear real audience pain, language, and objections before you scope a product.
Who is it for?
Best when you're validating audience pain and messaging and want cited community research inside your coding agent.
Skip if: Skip if you need formal surveys, B2B procurement data, or Reddit automation that posts or votes.
What you get
After you connect the MCP server, your agent returns structured Reddit findings with citations you can paste into validation docs and copy.
- Structured Reddit research summaries with full citations
- Audience language and pain points ready for landing copy
- Competitor and alternative mentions traceable to source threads
By the numbers
- PyPI package reddit-research-mcp version 1.0.1 with uvx runtime hint
- stdio MCP transport per registry metadata
README.md
mcp-name: io.github.king-of-the-grackles/reddit-research-mcp
Dialog MCP Server
AI-Powered Reddit Intelligence for Market Research & Competitive Analysis
Version: 1.0.0
Turn Reddit's chaos into actionable insights. Dialog is your all-in-one Reddit intelligence platform for competitive analysis, market research, and customer discovery across 20,000+ active subreddits.
This is the official MCP server powering Dialog - the AI-powered Reddit research platform built for indie hackers, SaaS founders, product managers, and market researchers.
Why Dialog?
Evidence-based insights with full citations. Every finding links back to real Reddit posts and comments with upvote counts, awards, and direct URLs. When you say "users are complaining about X," you'll have the receipts to prove it.
Zero-friction setup. No Reddit API credentials needed. No terminal commands. No credential management. Just connect and start researching.
Semantic search at scale. Reddit's API caps at 250 search results. Dialog searches conceptually across 20,000+ indexed subreddits using vector embeddings, finding relevant communities you didn't know existed.
Persistent research management. Save subreddit collections into feeds for ongoing monitoring. Perfect for long-term competitive analysis and market research campaigns.
Quick Setup (60 Seconds)
Claude Code
claude mcp add --scope local --transport http dialog-mcp https://reddit-research-mcp.fastmcp.app/mcp
Cursor
cursor://anysphere.cursor-deeplink/mcp/install?name=dialog-mcp&config=eyJ1cmwiOiJodHRwczovL3JlZGRpdC1yZXNlYXJjaC1tY3AuZmFzdG1jcC5hcHAvbWNwIn0%3D
OpenAI Codex CLI
codex mcp add dialog-mcp \
npx -y mcp-remote \
https://reddit-research-mcp.fastmcp.app/mcp \
--auth-timeout 120 \
--allow-http \
Gemini CLI
gemini mcp add dialog-mcp \
npx -y mcp-remote \
https://reddit-research-mcp.fastmcp.app/mcp \
--auth-timeout 120 \
--allow-http
Direct MCP Server URL
For other AI assistants: https://reddit-research-mcp.fastmcp.app/mcp
What You Can Do
Competitive Analysis
"What are developers saying about Next.js vs Remix?"
Get a comprehensive report comparing sentiment, feature requests, pain points, and migration experiences with links to every mentioned discussion.
Customer Discovery
"Find the top complaints about existing CRM tools in small business communities"
Discover unmet needs, feature gaps, and pricing concerns directly from your target market with citations to real user feedback.
Market Research
"Analyze sentiment about AI coding assistants across developer communities"
Track adoption trends, concerns, success stories, and emerging use cases with temporal analysis showing how opinions evolved.
Product Validation
"What problems are SaaS founders having with subscription billing?"
Identify pain points and validate your solution with evidence from actual Reddit discussions, not assumptions.
Server Capabilities
| Category | Count | Description |
|---|---|---|
| MCP Tools | 3 | discover_operations, get_operation_schema, execute_operation |
| Reddit Operations | 5 | discover, search, fetch_posts, fetch_multiple, fetch_comments |
| Feed Operations | 5 | create, list, get, update, delete |
| Indexed Subreddits | 20,000+ | Active communities (2k+ members, updated weekly) |
| MCP Prompts | 1 | reddit_research for automated workflows |
| Resources | 1 | reddit://server-info for documentation |
Use Cases by Role
For Indie Hackers & SaaS Founders
- Validate product ideas before building
- Find communities where your target customers hang out
- Monitor competitor mentions and sentiment
- Discover unmet needs in your niche
For Product Managers
- Gather customer feedback at scale
- Track feature requests across communities
- Understand competitive landscape
- Identify emerging trends before they peak
For Market Researchers
- Conduct sentiment analysis with full citations
- Build audience personas from real discussions
- Track how opinions evolve over time
- Generate evidence-based reports
Technical Details
Three-Layer MCP Architecture
Dialog follows the layered abstraction pattern for scalability and self-documentation:
Layer 1: Discovery
discover_operations()
See what operations are available and get workflow recommendations.
Layer 2: Schema Inspection
get_operation_schema("discover_subreddits", include_examples=True)
Understand parameter requirements, validation rules, and see examples before executing.
Layer 3: Execution
execute_operation("discover_subreddits", {
"query": "machine learning",
"limit": 15,
"min_confidence": 0.6
})
Perform the actual operation with validated parameters.
Reddit Research Operations
discover_subreddits
Find relevant communities using semantic vector search across 20,000+ indexed subreddits.
search_subreddit
Search for posts within a specific subreddit with filters for time range and sort order.
fetch_posts
Get posts from a single subreddit by listing type (hot, new, top, rising).
fetch_multiple
70% more efficient - Batch fetch posts from multiple subreddits concurrently.
fetch_comments
Get complete comment trees for deep analysis of discussions.
Feed Management Operations
Feeds let you save research configurations for ongoing monitoring:
- create_feed - Save discovered subreddits with analysis and metadata
- list_feeds - View all your saved feeds with pagination
- get_feed - Retrieve a specific feed by ID
- update_feed - Modify feed name, subreddits, or analysis
- delete_feed - Remove a feed permanently
Authentication
Dialog uses Descope OAuth2 for secure authentication:
- Setup: No Reddit credentials needed - server handles authentication
- Token: Automatically managed by your MCP client
- Privacy: Only accesses public Reddit data
- First use: Authentication takes ~30 seconds, then you're set
The Dialog Platform
This MCP server is the backend for Dialog, a complete Reddit intelligence platform featuring:
- Chat Interface - Natural language research powered by Claude AI
- Feed Management - Create and manage curated subreddit collections
- Consolidated Views - See hot posts from all your tracked subreddits in one place
- Cross-Device Sync - Chat history and feeds sync across devices
- Visual Analytics - Sentiment gauges, trend charts, and engagement metrics
Contributing
This project uses:
- Python 3.11+ with type hints
- FastMCP for the server framework
- ChromaDB for semantic search
- PRAW for Reddit API interaction
Stop guessing. Start knowing what your market actually thinks.
Recommended MCP Servers
How it compares
Cited community research MCP, not VC GitHub deal-flow analytics or internal RAG over your wiki.
FAQ
Who is reddit-research-mcp for?
Developers and marketers who use coding agents for discovery and need structured, cited Reddit evidence for audience and competitor research.
When should I use reddit-research-mcp?
Use it during Idea audience and competitor work, and early Validate when tightening scope against what real users say on Reddit.
How do I add reddit-research-mcp to my agent?
Add the PyPI package reddit-research-mcp to your MCP config with stdio transport (uvx runtime hint per registry metadata) in Claude Code, Cursor, or compatible clients.