Reddit Research Mcp

io.github.king-of-the-grackles由 GitHub 帳號 king-of-the-grackles 發布v1.0.1更新於 Oct 24, 2026

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

概覽

AI 產生的概覽

讓助理對 Reddit 進行語意搜尋、抓取貼文與留言串,並儲存 subreddit 摘要來源以供持續研究,且附上引用。

可以做什麼
提供三個 MCP 工具(discover_operations、get_operation_schema、execute_operation),包裝 Reddit 研究操作:在 20,000 多個已索引的 subreddit 中進行語意探索、在單一 subreddit 內搜尋、依列表類型抓取貼文、批次抓取多個 subreddit,以及取得完整留言樹。摘要來源操作可建立、列出、取得、更新與刪除已儲存的 subreddit 集合,用於持續監控。結果旨在附上真實貼文與留言的引用。
適用情境
適合競爭分析、客戶需求挖掘、市場調查與產品驗證,希望以 Reddit 討論中的證據而非假設為依據的情境。也適合透過已儲存的摘要來源長期監控特定社群。
執行需求
以本機 stdio 程序執行,從 PyPI 安裝 reddit-research-mcp 並以 uvx 啟動,因此需要 Python/uv 執行環境。README 另記錄了託管 HTTP 端點與首次使用時的 OAuth2 登入;清單中未宣告任何 Reddit API 憑證或環境變數。
安裝前請注意
README 說明此伺服器使用 Descope OAuth2,權杖由 MCP 用戶端管理,因此儘管清單未宣告驗證,仍涉及帳號登入。摘要來源操作可建立、更新並永久刪除已儲存的摘要來源。README 另推廣了另一個付費託管平台 Dialog,它不屬於此伺服器。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 Reddit Research Mcp,將其新增到工作區。
  2. 為需要使用其工具的對話啟用該服務。

Desktop only,透過 STDIO。 STDIO 服務會啟動本機處理程序,因此需要 SourceWeft 桌面主機。

其他 MCP 客戶端

參照 儲存庫 中的啟動說明。

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

來源:README.md,提交 36c75dd

工具

0
SourceWeft 尚未在沙箱中啟動過該軟體包,因此其工具未知。

版本歷史

1
  1. v1.0.1最新Sep 16, 2026

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