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Reddit Research

AI-powered Reddit intelligence for market research and competitive analysis. Discover subreddits via semantic search across 20k+ indexed communities, fetch posts/comments with full citations, and manage research feeds. No Reddit API credentials needed.

social-mediaapiai
By king-of-the-grackles
22427Updated 1 week agoPythonMIT

Installation

npx -y reddit-research-mcp

Configuration

{
  "mcpServers": {
    "reddit-research-mcp": {
      "command": "npx",
      "args": ["-y", "reddit-research-mcp"]
    }
  }
}

How to use

  1. Run the installation command above (if needed)
  2. Open your Claude Code settings file (~/.claude/settings.json)
  3. Add the configuration to the mcpServers section
  4. Restart Claude Code to apply changes

README

View on GitHub

mcp-name: io.github.king-of-the-grackles/reddit-research-mcp

Dialog MCP Server

Open source Reddit intelligence, part of the research engine that powers Dialog

Python 3.11+ FastMCP License: MIT

Version: 1.0.1

Turn Reddit's chaos into evidence-backed insights. This MCP server gives any AI assistant semantic search across 20,000+ active subreddits, deep-dive access to posts and comment threads, and saved feeds for ongoing monitoring. Every finding comes with citations to real posts and comments.

It's fully usable on its own, for free, in Claude Code, Cursor, Codex, Gemini CLI, or any MCP-compatible client. It's also part of the research engine that powers Dialog, the AI agent platform for continuous market intelligence, where it ships connected to every agent.

Why This Server?

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. This server 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.

Ongoing Monitoring

"Save these communities as a feed so we can track competitor sentiment over time"

Build curated feeds of the communities that matter to you, then come back to them in any session. Want this to run on a schedule and land in Slack? That's what Dialog adds on top.

Server Capabilities

CategoryCountDescription
MCP Tools3discover_operations, get_operation_schema, execute_operation
Reddit Operations5discover, search, fetch_posts, fetch_multiple, fetch_comments
Feed Operations5create, list, get, update, delete
Indexed Subreddits20,000+Active communities (2k+ members, updated weekly)
MCP Prompts1reddit_research for automated workflows
Resources1reddit://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

<details> <summary><strong>Three-Layer MCP Architecture</strong></summary>

The server 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.

</details> <details> <summary><strong>Reddit Research Operations</strong></summary>

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.

</details> <details> <summary><strong>Feed Management Operations</strong></summary>

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
</details> <details> <summary><strong>Authentication</strong></summary>

The server 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
</details>

Want This Running on Autopilot? Meet Dialog

This server is free and fully usable standalone. Dialog is the hosted platform where it plugs into a larger research engine: AI agents that combine this Reddit server with 45+ other integrations to run your research continuously and deliver the results where you work.

This MCP server (free, open source)Dialog platform
Reddit researchFull access: semantic discovery, search, posts, comments, feedsThis same server, connected by default to every agent
How it runsOn demand, inside your AI assistantAutonomous agents powered by Claude that plan and execute multi-step research
SchedulingManual, session by sessionAutomations that run on a schedule and land in a persistent inbox
DeliveryYour chat windowFormatted reports with inline charts in Slack, Telegram, or the web app
Data sourcesRedditReddit plus 45+ integrations: Gmail, Slack, Linear, HubSpot, Apollo, PostHog, Google Drive, and more
MemoryPer sessionPersistent agent workspaces that build context over time

A typical Dialog workflow: an agent monitors your competitors' communities every Monday morning, cross-references mentions against your CRM, and posts a formatted report with charts to your team's Slack channel before standup.

Try Dialog Free

Contributing

Contributions are welcome. The stack:

  • Python 3.11+ with type hints
  • FastMCP for the server framework
  • ChromaDB for semantic search
  • PRAW for Reddit API interaction

Local Development

# Clone and install (uses uv)
git clone https://github.com/king-of-the-grackles/reddit-research-mcp.git
cd reddit-research-mcp
uv sync --extra dev

# Run tests
uv run pytest

# Run the server locally
uv run reddit-mcp

Found a bug or have a feature idea? Open an issue.

<div align="center">

Stop guessing. Start knowing what your market actually thinks.

Dialog App | GitHub | Report Issues

</div>
View source on GitHub

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