Reddit Research Mcp

io.github.king-of-the-gracklesPublished by GitHub account king-of-the-gracklesv1.0.1Updated Oct 24, 2026

Turn Reddit's chaos into structured insights with full citations - MCP server for Reddit research

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Overview

AI-generated overview

Lets an assistant search Reddit semantically, fetch posts and comment threads, and save subreddit feeds for ongoing research, with citations.

What you can do
Exposes three MCP tools (discover_operations, get_operation_schema, execute_operation) that wrap Reddit research operations: semantic discovery across 20,000+ indexed subreddits, search within a subreddit, fetching posts by listing type, batch fetching from multiple subreddits, and retrieving full comment trees. Feed operations create, list, get, update, and delete saved subreddit collections for recurring monitoring. Results are meant to include citations to real posts and comments.
When to use it
Useful for competitive analysis, customer discovery, market research, and product validation where you want evidence from Reddit discussions rather than assumptions. Also suited to long-running monitoring of chosen communities through saved feeds.
Requirements
Runs as a local stdio process, installed from PyPI as reddit-research-mcp and launched with uvx, so a Python/uv runtime is needed. The README also documents a hosted HTTP endpoint and OAuth2 sign-in on first use; no Reddit API credentials or environment variables are declared in the manifest.
Before you install
The README states the server uses Descope OAuth2 and that tokens are managed by the MCP client, so an account sign-in is involved even though the manifest declares no authentication. Feed operations can create, update, and permanently delete saved feeds. The README also promotes a separate paid hosted platform, Dialog, which is not part of this server.

Installation

In SourceWeft

  1. Open Reddit Research Mcp in the dashboard and add it to a workspace.
  2. Enable the server for the chats that should use its tools.

Desktop only via STDIO. STDIO servers start a local process, so they need the SourceWeft desktop host.

Other MCP clients

Follow the launch instructions in the repository.

README

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

bash
claude mcp add --scope local --transport http dialog-mcp https://mcp.dialog.tools/mcp

Cursor

cursor://anysphere.cursor-deeplink/mcp/install?name=dialog-mcp&config=eyJ1cmwiOiJodHRwczovL21jcC5kaWFsb2cudG9vbHMvbWNwIn0%3D

OpenAI Codex CLI

bash
codex mcp add dialog-mcp \    npx -y mcp-remote \    https://mcp.dialog.tools/mcp \    --auth-timeout 120 \    --allow-http \

Gemini CLI

bash
gemini mcp add dialog-mcp \  npx -y mcp-remote \  https://mcp.dialog.tools/mcp \  --auth-timeout 120 \  --allow-http

Direct MCP Server URL

For other AI assistants: https://mcp.dialog.tools/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

Three-Layer MCP Architecture

The server follows the layered abstraction pattern for scalability and self-documentation:

Layer 1: Discovery

python
discover_operations()

See what operations are available and get workflow recommendations.

Layer 2: Schema Inspection

python
get_operation_schema("discover_subreddits", include_examples=True)

Understand parameter requirements, validation rules, and see examples before executing.

Layer 3: Execution

python
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

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

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

bash
# Clone and install (uses uv)git clone https://github.com/king-of-the-grackles/reddit-research-mcp.gitcd reddit-research-mcpuv sync --extra dev
# Run testsuv run pytest
# Run the server locallyuv run reddit-mcp

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

Stop guessing. Start knowing what your market actually thinks.

Dialog App | GitHub | Report Issues

Source: README.md at commit 36c75dd

Tools

0
SourceWeft has not started this package in its sandbox yet, so its tools are not known.

Version history

1
  1. v1.0.1LatestSep 16, 2026

Score

50% of the applicable checks met

How complete this listing is, computed from the registry entry, the endpoint and public sources. Not a rating of the server and not a statement that it is safe or working today: reachability is a dated check, and no installs or reviews go into the score.

  • Reached in the last 30 days25 pts

    Keep the endpoint answering the MCP handshake; SourceWeft probes it every 30 days.

  • Auth declared10 pts

    Declare the credential headers in the registry entry, or keep the endpoint answering the probe so its auth can be classified.

  • Tools listed15 pts

    Answer tools/list without a credential, or ship a package that starts in a sandbox without one.

  • DescriptionRequired15 pts
  • Logo10 pts
  • Documentation15 pts
  • License10 pts