mcpField
R
reddit

reddit

github.com/hyperfx-aiMarketing & growth107142 installsUpdated 4d ago
Repository

About reddit

A Reddit research skill that guides focused scraping before broader searches. It emphasizes relevant evidence and structured findings, including source URLs, recurring themes, subreddit distribution, and follow-up keywords.

Key features

  1. 01Start with focused lead scraping
  2. 02Expand post searches when needed
  3. 03Filter by subreddit, keyword, and time
  4. 04Summarize findings, sources, and themes

Use cases

  1. 01Monitor new discussions in selected subreddits
  2. 02Research user pain points and discussion themes
  3. 03Reduce noise and adjust search scope
  4. 04Organize findings and follow-up keywords

MCP support

Requires Hyper MCP to be installed and connected, with the Reddit scraper toolkit enabled. Scraping tools can be discovered and called through an MCP client.

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/hyperfx-ai/marketing-skills --skill reddit

After installing, type/redditin Claude Code to confirm it loaded.

Details

From the project README

Reddit Research

Use these tools in this order for research quality:

Requirements

  1. reddit_leads_scrape (precision first)
  2. reddit_scrape (expand recall second)
How to run the tools in this skill

Every tool in this skill is named by its canonical tool name. Run it with the call your surface gives you:

SurfaceFind a toolRun it
MCP client (Claude, Cursor, Codex, ChatGPT)search("<what you want to do>"), then describe("<name>")call("<name>", {...})
Hyper CLIhyperai search "<what you want to do>", then hyperai describe <name>hyperai call <name> --json '{...}'

If a tool is not found, its integration is not connected or not enabled for the workspace: stop and tell the user which integration to connect.

Default Workflow

Step 1: Precision pass with reddit_leads_scrape

Start with focused keyword + subreddit pairs:

  • searches: list of { "keyword": "...", "subreddit": "..." }
  • hours_back: set a clear recency window
  • search_posts=true
  • search_comments=true only when comment evidence is needed
  • sort="new" for monitoring or sort="top" for stable discussions
  • negative_keywords to suppress spam/noise

Use 1-3 specific keywords first. Avoid broad single words.

Step 2: Expand with reddit_scrape

If precision results are too narrow:

  • run reddit_scrape with subreddit start_urls
  • add adjacent keyword variants in searches
  • tune sort and time for recency vs quality
  • keep skip_comments=true when only post-level signal is needed

Query Quality Rules

  • Prefer scoped subreddits before global search.
  • Include negative filters (e.g. onlyfans, porn, nsfw, promo, buy now) when results are noisy.
  • Increase specificity before increasing max_items.
  • If results are sparse, widen subreddits and add semantically related keywords.

Output Requirements

Return:

  • top findings with short rationale
  • source URLs
  • subreddit distribution
  • repeated themes/pain points
  • recommended follow-up keywords

Do not return unfiltered dumps. Prioritize relevance and evidence.

Comments

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