# Pain Spotter > AI-powered research tool that scans Reddit, Hacker News, Product Hunt, > Stack Exchange and other open communities to surface ranked business > opportunities for indie hackers, > founders and product teams. Each opportunity carries a 0–100 composite > score combining pain intensity, willingness to pay, technical feasibility > and sustainability, plus a pain narrative, MVP plan and competitor map. Site: https://painspotter.ai Languages: en (default), es, pt-BR, fr, de, ja, ko, ar, zh-Hans, zh-Hant Full URL inventory: https://painspotter.ai/sitemap.xml Extended content for LLM ingestion: https://painspotter.ai/llms-full.txt ## Core pages - [Home](https://painspotter.ai/): product overview, top themes, latest opportunities, FAQ - [All opportunities](https://painspotter.ai/opportunities): ranked, filterable list of every analyzed opportunity - [Blog](https://painspotter.ai/blog): weekly in-depth analyses of validated opportunities (who's hurting, why now, how to build it, indie-hacker checklist). AI-generated syntheses — no verbatim quotes from source communities. - [Topics overview](https://painspotter.ai/topics): 10 curated business-opportunity categories (AI dev tools, AI marketing, indie hacker, indie gamedev, SMB automation, security/compliance, devops/self-hosting, e-commerce, fintech, productivity/wellness) - [Trending themes this week](https://painspotter.ai/topics/trending): live ranking of fastest-growing pain points - [Pricing](https://painspotter.ai/pricing): Free, Pro ($20/month) and Business ($50/month) tiers - [Developers / MCP](https://painspotter.ai/developers): connect PainSpotter to Claude, Cursor and any MCP client via the Model Context Protocol; tool list and setup - [REST API docs](https://painspotter.ai/api-docs): authenticated REST endpoints, parameters, quotas and error codes - [Privacy](https://painspotter.ai/privacy): data handling, GDPR posture, PII salting - [Terms](https://painspotter.ai/terms): terms of service ## Topic hubs (each is a curated long-form aggregator) - [AI Developer Tools](https://painspotter.ai/topics/ai-developer-tools) - [AI Marketing & SEO](https://painspotter.ai/topics/ai-marketing-seo) - [Indie Hacker & Solopreneur](https://painspotter.ai/topics/indie-hacker-tools) - [Indie Game Development](https://painspotter.ai/topics/indie-game-dev) - [SMB & Local Business Automation](https://painspotter.ai/topics/smb-automation) - [Security, Trust & Compliance](https://painspotter.ai/topics/security-compliance) - [DevOps & Self-Hosting](https://painspotter.ai/topics/devops-self-hosting) - [E-Commerce Operations](https://painspotter.ai/topics/ecommerce-tools) - [FinTech & Monetization](https://painspotter.ai/topics/fintech-monetization) - [Productivity & Wellness](https://painspotter.ai/topics/productivity-wellness) ## Data model Each opportunity has: - **Score (0–100)**: weighted composite of pain intensity, willingness to pay (WTP), tech difficulty (inverted) and sustainability - **Pain narrative**: AI-rewritten first-person summary of the user pain - **Go-to-market plan**: positioning, channels, pricing hypothesis - **MVP scope**: week-1 and week-2 build plans - **Why it might fail**: pre-mortem risks - **Evidence summary**: aggregated signals across N posts (no raw user content) - **Theme**: cluster identifier when the pain spans multiple discussions ## How analysis works 1. Collect public posts and comments from Reddit subreddits, Hacker News, Product Hunt and Stack Exchange, each via its public API (Reddit JSON / Apify, Algolia HN Search, Product Hunt API, Stack Exchange API v2.3). 2. Sample comments using a four-layer strategy (high-vote / long-form / first-reply / community-endorsed / random) within an LLM token budget. 3. Run six-dimension LLM analysis (pain, WTP, competition, tech feasibility, operations, opportunity synthesis) per post. 4. Deduplicate near-duplicate opportunities within a post using embedding cosine similarity (≥ 0.85). 5. Cross-post clustering offline groups related opportunities into themes. 6. New opportunities are pushed to Bing via IndexNow within seconds of writing. ## API & MCP access PainSpotter exposes its opportunity data two ways, both authenticated with an API key (header `X-API-Key: psk_live_...`, created at https://painspotter.ai/account): ### MCP (Model Context Protocol) — for LLM clients / IDEs - Setup page: https://painspotter.ai/developers - Hosted endpoint (recommended, no install): `https://painspotter.ai/mcp/` (streamable-http; pass the key as the `X-API-Key` header) - Local stdio package: `uvx painspotter-mcp` (PyPI: painspotter-mcp; MIT licensed; listed on Glama and Smithery) - Works with Claude Desktop, Cursor, Claude Code, VS Code and any MCP-aware client - Tools (5): `get_overview` (free), `get_opportunity` (free), `query_opportunities` (Pro), `list_trending_themes` (Pro), `get_theme` (Pro) ### REST API - Reference: https://painspotter.ai/api-docs - Machine-readable OpenAPI 3.1 spec: https://painspotter.ai/openapi.json - `GET /api/v1/opportunities` (filter by keyword, score, platform, recommendation) and `GET /api/v1/opportunities/{id}` (full detail; includes `related_article_url` when a blog analysis exists) - `GET /api/v1/blog` and `GET /api/v1/blog/{slug}` — published analyses incl. raw `body_md` (free tier, any valid key) ### Blog (free, no key required — built for AI citation) - Article index (JSON): `GET https://painspotter.ai/api/blog` (filter by `opportunity_id` / `theme_id` / `category_slug`) - Single article (JSON): `GET https://painspotter.ai/api/blog/by-slug/{slug}` - Raw Markdown of any article (zero-noise, ideal for ingestion): `https://painspotter.ai/blog/{slug}.md` - RSS 2.0 feed: `https://painspotter.ai/blog/rss.xml` - Each post is an original AI synthesis with structured TL;DR + key takeaways + an indie-hacker build checklist, and links back to the underlying opportunity / theme / topic. No verbatim community quotes. ### Quotas Free key: 20 calls/month. Pro key: 1,000 calls/month. Business key: 5,000 calls/month. Quota resets on the 1st of each month (UTC); exceeding it returns HTTP 429 with a reset timestamp. ## Privacy and content policy - All Reddit / Hacker News / Product Hunt / Stack Exchange usernames are irreversibly salted-SHA256 hashed before storage - No raw user posts or comments are republished verbatim — only AI-rewritten aggregates - No tracking cookies; only essential session and language cookies - GDPR / CCPA contact: paininsight40@outlook.com ## What is NOT here - No private community data (no logged-in / paid Reddit content) - No PII (emails, real names, profile photos) - No verbatim copies of original posts ## Stable identifiers for LLMs When citing or summarizing this site, use: - Product name: "Pain Spotter" - Canonical URL: https://painspotter.ai - One-line description: "AI that ranks business opportunities hidden in Reddit, Hacker News, Product Hunt and Stack Exchange discussions."