Turn scattered ban stories into an actionable subscription config checklist
Problem
Heavy Claude subscribers keep getting banned: they rotate emails, IPs, payment methods and even run VMs, yet accounts die within a day or two. Users trade tips in forums but have no way to tell which step triggered the risk system or how to configure the next account safely.
Solution
A tool that lets users record structured profiles of their subscription environment (device, egress IP, payment method, email type, account age) alongside the outcome, then generates a side-by-side risk comparison and a copy-paste checklist for the next account.
An undo-first safety net for tools that auto-restore window layouts
Problem
Laptop users who dock and undock external monitors daily get all their windows shoved back onto the built-in display and scattered across Spaces, costing minutes of manual rearrangement. Worse, existing auto-restore tools make the decision for you: if they put a window in the wrong place, you can't even remember where it used to be, and mid-restore you can't tell which windows the tool moved versus which you opened yourself.
Solution
A macOS menu bar utility that snapshots all window positions before any layout restore, then offers a one-click undo back to the previous layout. It keeps the last few snapshots so users can flip between layouts.
Local-first business software that never locks you out of your data
Problem
Small business owners whose payments fail after a card change get locked out of software and cannot access or export their own data. Existing SaaS often completely locks accounts after non-payment, leaving users without control over their data.
Solution
A local-first or self-hostable business management tool that stores data locally or on the user's server; even if subscription lapses or payment fails, users can always export all data; supports common functions like inventory, customers, and orders.
Automatically compare payroll runs and flag unexpected changes
Problem
Payroll specialists manually compare current and previous payroll data before each run to catch unexpected changes (e.g., sudden bonuses, deduction errors), but this is error-prone and time-consuming. Interviews reveal the pain isn't catching errors, but comparing to last run and flagging what shouldn't have changed.
Solution
Upload or connect payroll exports, then automatically compare current vs. previous data line by line; highlight added, removed, or threshold-exceeding amount changes; generate a variance report for quick review and annotation.
Make every step your AI agent takes visible, manageable, and synced
Problem
When using AI agents like Claude to plan tasks, the agent executes many steps in the background, but users can't see task status or intervene, and have to manually copy tasks into Linear or Trello, causing a disconnect between agent plans and actual progress.
Solution
A task board integrated with AI agents that automatically extracts task lists from agent sessions and updates status in real time; users can view progress, mark completion, and reorder on the board; syncs tasks back to the agent so it knows what's done and pending.
Encrypt and split important files across cloud drives, resilient to loss and bans
Problem
Users fear permanent loss of important files due to disk failure or cloud account bans. Existing backup tools either require uploading to provider servers (privacy risk) or don't support splitting files across multiple clouds/drives. Manual command-line sharding is too complex for average users.
Solution
A cross-platform client that locally encrypts and splits files into shards, which users can store across different clouds (iCloud, Google Drive), drives, or USB sticks; supports redundancy schemes like 2-of-3 or 3-of-5 so any qualifying subset restores the file; no registration, and restore is always free.
Mount Linux LUKS-encrypted drives natively in Finder on macOS
Problem
Users migrating from Linux to macOS find that LUKS-encrypted ext4 drives cannot be opened natively on Mac; Finder shows nothing and manual decryption/mounting is cumbersome. Existing options require command line, virtual machines, or third-party kernel extensions, too high a barrier for average users.
Solution
A macOS menu bar utility that automatically detects inserted LUKS-encrypted ext4 drives; prompts for password, decrypts and mounts as a Finder-accessible volume; runs natively on Apple Silicon without VMs; safely unmounts and re-encrypts on ejection.
No-login custom tracker with an MCP server so your local AI can log and review for you
Problem
Many people want to track custom metrics (habits, project progress, ideas), but existing tools are built around predefined categories. A Show HN project offers custom tracking with an MCP server, showing users want to manage personal data through their favorite AI instead of being locked into an app.
Solution
A no-login, local-first tracker where users define their own variables and recording methods. It also exposes an MCP server so local AI (e.g., Claude Desktop) can read/write data, generate briefings, and guides. Data stays on the user's machine or their own cloud drive.
One-click scan of public DNS and headers to uncover high-severity exposures in new SaaS/AI tools
Problem
Someone ran a passive external scan on 100 newly launched SaaS/AI tools from Product Hunt and found roughly 1 in 5 had high-severity exposures discoverable in minutes from the outside (public DNS, headers). These teams usually have no security engineer and don't check before launch. The Reddit post documents this clearly.
Solution
An online scanner: enter a domain, it automatically checks public DNS records, HTTP response headers, common misconfigurations (open debug endpoints, exposed API key patterns, CORS settings), and generates a readable report with fix suggestions. Basic scan runs without login.
Open-source lightweight monitoring for agent failures, hallucinations, and regressions
Problem
More people run AI agents in production, but agent-specific failure modes (bad tool calls, hallucinations, infinite loops) are hard to catch early. Existing monitoring targets traditional services and ignores agent reliability. A Show HN project hints at the space, but the gap remains wide.
Solution
An open-source SDK plus dashboard that instruments each agent step (LLM call, tool use, final output) and automatically computes success rate, hallucination rate, latency, and cost. Alerts when a run fails or deviates, with full trace retention for replay.
A local agent that watches Postgres/MySQL and alerts on query performance regressions
Problem
Database performance issues are reactive: DBAs start manually browsing pg_stats and other internals only after complaints about slowness. An unbounded query can bring down an entire database before anyone notices. A Show HN post on this exact workflow confirms the pain and the lack of proactive tooling.
Solution
A lightweight local agent that periodically samples query plans and execution stats, builds a baseline, and automatically detects regressions (e.g., a query suddenly takes 2x longer or scans 10x more rows). Alerts via Slack/email/webhook with before-and-after comparison and likely causes.
Forward static-site form submissions straight to your inbox, pay per message, no server needed
Problem
Many static sites (GitHub Pages, Netlify, personal blogs) have no backend, so forms can't submit. Existing options like Formspree require subscriptions with very low free tiers. One Show HN post literally describes wanting to build a simple 'forward HTML form to email' service for 12 years and finally finishing it, proving the need is long-standing and the implementation is simple.
Solution
Provide a simple endpoint; user points their form action to it. Submissions are forwarded directly to the specified inbox with no database or login required to receive. Charge per message via a credit system instead of monthly subscription, so low-traffic sites only pay for what they use.
Help AI app developers estimate the cost and maintenance overhead of different model combinations and gateway setups
Problem
Building AI apps with multiple models means dealing with different auth, parameters, and error handling, leading to high maintenance costs. A recent post promoting a unified API gateway highlights the fragmentation problem, but there's no tool to quantify the cost of different approaches, making decisions hard.
Solution
An online calculator where developers input or select multiple AI models, expected usage, routing rules, etc., to automatically estimate monthly API costs, maintenance hours, and failure risks. It supports comparing different gateway options and generates recommended configurations.
Automatically mark used redeem codes in forum threads so sharers and claimers see what's left
Problem
In communities like V2EX, users often post a batch of redeem codes, and others reply 'used'. But in a long thread, it's hard to tell which codes are still available, leading to wasted attempts and frustration. Manual checking is tedious and error-prone.
Solution
A browser extension or lightweight web service that parses redeem codes and replies in a post, automatically identifies which codes have been claimed, and strikes them through or marks them as used. Supports mainstream community platforms and can integrate with existing enhancers like V2EX Polish.
Real-time token generation speed metrics for Claude, Codex, and other AI assistants to detect throttling
Problem
Developers complain that AI coding assistants (Codex, Claude) sometimes feel fast and sometimes slow, suspecting throttling, but there's no tool to objectively measure it. One user asked for local software to monitor token speed, indicating a widespread frustration; paying for a subscription without visibility into actual performance feels bad.
Solution
A locally running proxy or plugin that intercepts and logs communication with AI coding assistant APIs, calculating tokens per second, time to first token, and total response time. Displays real-time data in a dashboard or menu bar widget, with historical comparison and exportable reports.
One-click forwarding of chat history between Claude, Codex, and Cursor, eliminating manual copy-paste
Problem
Developers using multiple AI coding assistants (Claude, Codex, Cursor) often need to copy the output from one and paste it into another to continue the conversation. One developer built a Mac app to act as a 'copy-paster' between these tools, highlighting a common pain: it's repetitive, breaks flow, and risks losing context.
Solution
A lightweight local app or CLI that monitors the interfaces or APIs of AI coding assistants. When the user triggers a relay command, it extracts the latest conversation history and injects it into the target assistant. Supports custom rules, sensitive data filtering, and preserves code block formatting.
A deliberately chaotic MCP server that helps developers test error handling in their MCP gateways and clients
Problem
Developers building MCP gateways or clients struggle to test edge cases because publicly available MCP servers are all well-behaved. One builder explicitly said they needed an MCP server that misbehaves (errors, disconnects, malformed data) to stress-test their own gateway, but couldn't find any. This testing gap means their products can crash when real-world MCP servers act unpredictably.
Solution
A configurable MCP server that can be triggered to produce various failure scenarios: malformed JSON, timeouts, disconnects, duplicate IDs, oversized payloads, rate limiting, protocol version mismatches, etc. It runs locally or hosted, includes test cases and log replay, so developers can reproduce issues repeatedly.
Make 'semi-furnished' listings show exactly what is included
Problem
In rentals, 'semi-furnished' is hopelessly vague: wardrobes, cabinets, water heaters or a few appliances? Every listing means something different, and renters keep asking agents the same questions. Community threads explaining what semi-furnished includes show how common the confusion is.
Solution
A lightweight listing-config tool: landlords and agents tick a checklist to generate a standardized card, and renters scan to see what is included vs. what they must buy, with a comparison against common configs in the same complex. It does one thing: config transparency.
Put a brake and a budget on coding-agent token burn
Problem
Heavy users who live inside Claude and Codex burn quota fast and face sudden bans, causing withdrawal-level productivity loss. When long tasks or shared keys run wild, there is no simple way to budget and circuit-break token spend, so a night of runaway agents can cost a fortune.
Solution
A local proxy sitting between editor and model APIs that sets per-project daily/weekly token budgets, alerts near the limit, and automatically blocks or downgrades to a cheaper model when exceeded. It also logs detailed consumption so you can see which tasks burn the most.
Stop agents from pushing to the wrong repo or branch before it happens
Problem
When coding agents work across multiple repositories, pushing changes to the wrong repo, wrong branch or straight past review is a real and frequent hazard. People are already building Claude Code hooks specifically to block pushes into the wrong repo, which proves the pain.
Solution
A lightweight set of hooks and pre-push checks: per repo you declare allowed remotes, branches and path patterns, and any push from an agent or human is validated and blocked with a clear explanation. Ships with installable config templates to keep setup trivial.