Reddit Research MCP

🚀 Dialog MCP Server

AI-Powered Reddit Intelligence for Market Research & Competitive Analysis

Version: 1.0.0

Dialog transforms the chaos of Reddit into actionable insights. It serves as an all - in - one Reddit intelligence platform, enabling competitive analysis, market research, and customer discovery across over 20,000 active subreddits. This is the official MCP server that powers Dialog, an AI - powered Reddit research platform designed for indie hackers, SaaS founders, product managers, and market researchers.

✨ Features

Evidence - based insights with full citations

Every finding is linked back to real Reddit posts and comments, including upvote counts, awards, and direct URLs. When stating "users are complaining about X," you can provide evidence to support it.

Zero - friction setup

There's no need for Reddit API credentials, terminal commands, or credential management. Simply connect and start your research.

Semantic search at scale

Reddit's API has a limit of 250 search results. Dialog uses vector embeddings to conduct conceptual searches across over 20,000 indexed subreddits, uncovering relevant communities you might not have known existed.

Persistent research management

Save subreddit collections into feeds for continuous monitoring, which is ideal for long - term competitive analysis and market research campaigns.

🚀 Quick Start

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

💻 Usage Examples

Competitive Analysis

"What are developers saying about Next.js vs Remix?"

Obtain 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 through temporal analysis, showing how opinions have evolved.

Product Validation

"What problems are SaaS founders having with subscription billing?"

Identify pain points and validate your solution based on evidence from actual Reddit discussions, rather than assumptions.

📚 Documentation

Server Capabilities

Use Cases by Role

For Indie Hackers & SaaS Founders

• Validate product ideas before development.
• Locate communities where your target customers are active.
• Monitor competitor mentions and sentiment.
• Discover unmet needs in your niche.

For Product Managers

• Gather large - scale customer feedback.
• Track feature requests across communities.
• Understand the competitive landscape.
• Identify emerging trends before they peak.

For Market Researchers

• Conduct sentiment analysis with full citations.
• Build audience personas from real discussions.
• Track the evolution of opinions over time.
• Generate evidence - based reports.

🔧 Technical Details

Three - Layer MCP Architecture

Dialog adheres to the layered abstraction pattern for scalability and self - documentation:

Layer 1: Discovery

discover_operations()

View available operations and get workflow recommendations.

Layer 2: Schema Inspection

get_operation_schema("discover_subreddits", include_examples=True)

Understand parameter requirements, validation rules, and view examples before execution.

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 over 20,000 indexed subreddits.

search_subreddit

Search for posts within a specific subreddit, with filters for time range and sort order.

fetch_posts

Retrieve 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

Obtain complete comment trees for in - depth analysis of discussions.

Feed Management Operations

Feeds allow you to save research configurations for continuous 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 - Permanently remove a feed.

Authentication

Dialog uses Descope OAuth2 for secure authentication:

• Setup: No Reddit credentials are required; the server handles authentication.
• Token: Automatically managed by your MCP client.
• Privacy: Only accesses public Reddit data.
• First use: Authentication takes approximately 30 seconds, after which you're set.

📄 License

This project is licensed under the MIT License. View License

The Dialog Platform

This MCP server serves as the backend for Dialog, a comprehensive Reddit intelligence platform with the following features:

• Chat Interface - Natural language research powered by Claude AI.
• Feed Management - Create and manage curated subreddit collections.
• Consolidated Views - View hot posts from all your tracked subreddits in one location.
• Cross - Device Sync - Chat history and feeds sync across devices.
• Visual Analytics - Sentiment gauges, trend charts, and engagement metrics.

Try Dialog Free

Contributing

This project utilizes:

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