Open-source tool for AI-curated Reddit feeds using Cloudflare, Supabase, and Vercel

A developer has open-sourced a self-hosted tool that creates AI-curated Reddit feeds, specifically designed to filter out low-quality content about AI-assisted development and vibecoding. The tool removes posts like "I made $1M with AI in 2 hours," low-effort screenshots, and repeated beginner questions.

How it works

Every 15 minutes, a Cloudflare Worker triggers the pipeline. It fetches Reddit JSON through a Cloudflare proxy because Reddit often blocks Vercel/AWS IPs. A pre-filter removes low-signal posts before any AI processing. Remaining posts receive engagement scoring with community-size normalization, comment boosts, and controversy penalties. Top posts can optionally go through an LLM for quality rating, categorization, and one-line summaries. A diversity pass prevents one subreddit from dominating the feed.

Technical stack

• Supabase for storage
• Cloudflare Workers for cron jobs and Reddit proxy
• Vercel for the frontend
• AI scoring is optional and costs about $1-2/month with Claude Haiku

Features

The tool provides a dark-themed feed with AI summaries and category badges, daily archives, RSS, weekly digest via Resend, anonymous upvotes, and a feedback form.

Setup process

Setup involves cloning the repository, editing one config file, running one SQL migration, deploying two Workers, then deploying to Vercel.

Configuration example

const config = {
  name: "My ML Feed",
  subreddits: {
    core: [
      { name: "MachineLearning", minScore: 20, communitySize: 300_000 },
      { name: "LocalLLaMA", minScore: 15, communitySize: 300_000 },
    ],
  },
  keywords: ["LLM", "transformer model"],
  communityContext: `Value: papers with code, benchmarks, novel architectures.
  Penalize: hype, speculation, product launches without technical depth.`,
};

The tool was built with Claude Code and is available on GitHub at github.com/solzange/reddit-signal.