Show HN: CLI to share secrets using one-time public keys https://ift.tt/vZFmLJt

Show HN: CLI to share secrets using one-time public keys https://ift.tt/MxSjKdw December 25, 2025 at 11:50PM

Show HN: Buoy – A persistent, status-bar web server for local utilities https://ift.tt/RzsVEyc

Show HN: Buoy – A persistent, status-bar web server for local utilities I’m constantly building small web-based tools for my own use. Usually, my workflow ends with a dilemma: do I keep a terminal tab open forever running `npx http-server -p 8080`, or do I spend time configuring a Caddyfile for a 50-line HTML tool? Nothing felt right. I wanted something that felt like a native, always-on, utility that was easily accessible but invisible. I built Buoy. It’s a minimal server that: Lives in the status bar: I can see that it's running at a glance without hunting through ps aux. Is persistent by default: It starts with macOS and keeps my utilities alive in the background. Zero-config: It points at a XDG‑Standard www folder so I can create a symlink and be done. Small: I wanted to avoid the modern bloat. Buoy is a single, self-contained binary that's under 10MB. It’s a minimal tool that lets me build many small things and move on to the next. https://ift.tt/iKQORMV December 25, 2025 at 09:51PM

Show HN: WebPtoPNG – I built a WebP to PNG tool, everything runs in the browser https://ift.tt/PowjqfD

Show HN: WebPtoPNG – I built a WebP to PNG tool, everything runs in the browser I built WebPtoPNG after getting frustrated with converters that throttle uploads or phone data; everything runs straight in the browser, and never asks for a signup. https://webptopng.cc/ December 25, 2025 at 02:14AM

Show HN: Elfpeek – A tiny interactive ELF binary inspector in C https://ift.tt/6DM4gu5

Show HN: Elfpeek – A tiny interactive ELF binary inspector in C https://ift.tt/c0fRphu December 24, 2025 at 11:08PM

Show HN: An open-source anonymizer tool to replace PII in PostgreSQL databases https://ift.tt/IBl8mhJ

Show HN: An open-source anonymizer tool to replace PII in PostgreSQL databases https://ift.tt/xSW8hHp December 24, 2025 at 09:45PM

Show HN: Openinary – Self-hosted image processing like Cloudinary https://ift.tt/cEFNTDP

Show HN: Openinary – Self-hosted image processing like Cloudinary Hi HN! I built Openinary because Cloudinary and Uploadcare lock your images and charge per request. Openinary lets you self-host a full image pipeline: transform, optimize, and cache images on your infra; S3, Cloudflare R2, or any S3-compatible storage. It’s the only self-hosted Cloudinary-like tool handling both transformations and delivery with a simple URL API (/t/w_800,h_800,f_avif/sample.jpg). Built with Node.js, Docker-ready. GitHub: https://ift.tt/xeMpiK7 Feedback welcome; especially from Cloudinary users wanting the same UX but on their own infra! https://ift.tt/xeMpiK7 December 23, 2025 at 09:31PM

Show HN: A kids book that introduces authorization and permissions concepts https://ift.tt/ZmnUPtj

Show HN: A kids book that introduces authorization and permissions concepts A colleague and I made a kids' picture book that introduces authorization concepts. We work at AuthZed and explain these concepts regularly. We thought it'd be fun to put them together in a format accessible and appealing to kids and grownups alike. It would also be helpful when explaining what we do for work and make a unique gift for our families. The goal was a fun story first and foremost. We aimed to present concepts accessibly but made conscious decisions to simplify, knowing we couldn't be comprehensive in a picture book format. We also wanted visually appealing illustrations, so we built a custom tool to streamline exploring ideas with AI. It does reference-weighted image generation (upload references, weight which ones matter most), git-like branching for asset organization, and feedback loops that improve subsequent generations. It was built with Claude Code. Here's a screenshot: https://ift.tt/glWyLJj... We'd love feedback on where we chose to simplify. Did we get the tradeoffs right or did we oversimplify? And lastly, did you enjoy the story? You can read the book online: https://ift.tt/QXW2hqd https://ift.tt/QXW2hqd December 24, 2025 at 12:06AM

Show HN: It's Like Clay but in Google Sheets https://ift.tt/U2svlLC

Show HN: It's Like Clay but in Google Sheets Hey everyone! After struggling a lot with data enrichment for SMBs, I launched a Google Sheets add-on that gives you direct access to an AI-powered webscraper. Vurge lets you get structured information from any website right inside your Google Sheet, eliminating the need for learning a new tool or adding a new dependency for data enrichment. Let me know what you think! https://ift.tt/52N3ulx December 19, 2025 at 12:44AM

Show HN: Meds — High-performance firewall powered by NFQUEUE and Go https://ift.tt/kOVD6fr

Show HN: Meds — High-performance firewall powered by NFQUEUE and Go Hi HN, I'm the author of Meds ( https://ift.tt/RkFgAZq ). Meds is a user-space firewall for Linux that uses NFQUEUE to inspect and filter traffic. In the latest v0.7.0 release, I’ve added ASN-based filtering using the Spamhaus DROP list (with IP-to-ASN mapping via IPLocate.io). Key highlights: Zero-lock core, ASN Filtering, Optimized Rate Limiting, TLS Inspection, Built-in Prometheus metrics and Swagger API. Any feedback is very welcome! https://ift.tt/RkFgAZq December 22, 2025 at 10:58PM

Show HN: Real-time SF 911 dispatch feed (open source) https://ift.tt/OfJEHdn

Show HN: Real-time SF 911 dispatch feed (open source) I built an open-source alternative to Citizen App's paid 911 feed for San Francisco. It streams live dispatch data from SF's official open data portal, uses an LLM to translate police codes into readable summaries, and auto-redacts sensitive locations (shelters, hospitals, etc.). Built it at a hack night after getting annoyed that Citizen is the only real-time option and they paywall it. Repo: https://ift.tt/9EJslYq Discord: https://ift.tt/xkCTpGi Happy to discuss the technical approach or take feedback. https://ift.tt/U1vFoCq December 22, 2025 at 06:29AM

Show HN: Mactop v2.0.0 https://ift.tt/FspgYRl

Show HN: Mactop v2.0.0 https://ift.tt/v20ujDV December 22, 2025 at 06:14AM

Show HN: Pac-Man with Guns https://ift.tt/0EXi749

Show HN: Pac-Man with Guns Title really says it all on this https://pac-man-with-guns.netlify.app/ December 22, 2025 at 04:47AM

Show HN: I built a 1‑dollar feedback tool as a Sunday side project https://ift.tt/S9gE06M

Show HN: I built a 1‑dollar feedback tool as a Sunday side project I’ve always found it funny how simple feedback widgets end up as $20–$30/month products. The tech is dead simple, infra is cheap, and most of us here could rebuild one in a weekend. So as a “principle experiment” I built my own today as a side project and priced it at 1 dollar. Just because if something is cheap to run and easy to replicate, it should be priced accordingly, and it’s also fun marketing. 1$ feedback tool. Shipped today, got the first users/moneys today, writing this post today. Side Sunday project, then back to the main product tomorrow. https://ift.tt/PqozBb5 December 22, 2025 at 03:22AM

Show HN: HN Wrapped 2025 - an LLM reviews your year on HN https://ift.tt/VtGUdPv

Show HN: HN Wrapped 2025 - an LLM reviews your year on HN I was looking for some fun project to play around with the latest Gemini models and ended up building this :) Enter your username and get: - Generated roasts and stats based on your HN activity 2025 - Your personalized HN front page from 2035 (inspired by a recent Show HN [0]) - An xkcd-style comic of your HN persona It uses the latest gemini-3-flash and gemini-3-pro-image (nano banana pro) models, which deliver pretty impressive and funny results. A few examples: - dang: https://ift.tt/Jx4iywE - myself: https://ift.tt/Us9yT7N Give it a try and share yours :) Happy holidays! [0] https://ift.tt/cLT8YNf https://ift.tt/ilDPodk December 20, 2025 at 07:09PM

Show HN: Misata – synthetic data engine using LLM and Vectorized NumPy https://ift.tt/HU8J5xB

Show HN: Misata – synthetic data engine using LLM and Vectorized NumPy Hey HN, I’m the author. I built Misata because existing tools (Faker, Mimesis) are great for random rows but terrible for relational or temporal integrity. I needed to generate data for a dashboard where "Timesheets" must happen after "Project Start Date," and I wanted to define these rules via natural language. How it works: LLM Layer: Uses Groq/Llama-3.3 to parse a "story" into a JSON schema constraint config. Simulation Layer: Uses Vectorized NumPy (no loops) to generate data. It builds a DAG of tables to ensure parent rows exist before child rows (referential integrity). Performance: Generates ~250k rows/sec on my M1 Air. It’s early alpha. The "Graph Reverse Engineering" (describe a chart -> get data) is experimental but working for simple curves. pip install misata I’d love feedback on the simulator.py architecture—I’m currently keeping data in-memory (Pandas) which hits a ceiling at ~10M rows. Thinking of moving to DuckDB for out-of-core generation next. Thoughts? https://ift.tt/4PEXrgd December 16, 2025 at 08:08PM

Show HN: MCPShark Viewer (VS Code/Cursor extension)- view MCP traffic in-editor https://ift.tt/0FfR5t1

Show HN: MCPShark Viewer (VS Code/Cursor extension)- view MCP traffic in-editor A few days ago I posted MCPShark (a traffic inspector for the Model Context Protocol). I just shipped a VS Code / Cursor extension that lets you view MCP traffic directly in the editor, so you’re not jumping between terminals, logs, and "I think this is what got sent". VS Code Marketplace: https://marketplace.visualstudio.com/items?itemName=MCPShark... Main repo: https://ift.tt/rCDSdwp Feature requests / issues: https://ift.tt/dHQxWsT Site: https://mcpshark.sh/ If you’re building MCP agents/tools: what would make MCP debugging actually easy—timeline view, session grouping, diffing tool args, exporting traces, something else? I’d be thankful if you could open a feature request here: https://ift.tt/dHQxWsT December 17, 2025 at 11:49PM

Show HN: Stickerbox, a kid-safe, AI-powered voice to sticker printer https://ift.tt/eANsQFh

Show HN: Stickerbox, a kid-safe, AI-powered voice to sticker printer Bob and Arun here, creators of Stickerbox. If AI were built for kids, what would it look like? Asking that question led us to creativity, and more specifically, the power of kids’ imaginations. We wanted to let kids combine the power of their ideas with AI tools but we needed to make sure we did it safely and in the right way. Enter Stickerbox, a voice powered sticker printer. By combining AI image generation with thermal sticker printing, we instantly turn kids' wildest ideas into real stickers they can color, stick, and share. What surprised us most is how the “AI” disappears behind the magic of the device. The moment that consistently amazes kids is when the printer finishes and they are holding their own idea as a real sticker. A ghost on a skateboard, a dragon doing its taxes, their dog as a superhero, anything they can dream of, they can hold in their hand. Their reactions are what pushed us to keep building, even though hardware can be really hard. Along the way the scope of the project grew more than we expected: navigating supply chains, sourcing safe BPA/BPS free thermal paper, passing safety testing for a children’s product, and designing an interface simple enough that a five year old can walk up and just talk to it. We also spent a lot of time thinking about kids’ data and privacy so that parents would feel comfortable having this in their home. Stickerbox is our attempt to make modern AI kid-safe, playful, and tangible. We’d love to hear what you think! P.S. If you’re interested in buying one for yourself or as a gift, use code FREE3PACK to get an extra free pack of paper refills. https://stickerbox.com/ December 20, 2025 at 01:14AM

Show HN: Spice Cayenne – SQL acceleration built on Vortex https://ift.tt/qf27DTA

Show HN: Spice Cayenne – SQL acceleration built on Vortex Hi HN, we’re Luke and Phillip, and we’re building Spice.ai OSS - a lightweight, portable data and AI engine and powered by Apache DataFusion & Ballista for SQL query, hybrid-search, and LLM-inference across disaggregated-storage used by enterprises like Barracuda Networks and Twilio. We first introduced Spice [1] on HN in 2021 and re-launched it on HN [2] in 2024 re-built from the ground up in Rust. Spice includes the concept of a Data Accelerator [3], which is a way to materialize data from disparate sources, such as other databases, in embedded databases like SQLite and DuckDB. Today we’re excited to announce a new Ducklake-inspired Data Accelerator built on Vortex [3], a highly performant, extensible columnar data format that claims 100x faster random access, 10-20x faster scans, 5x faster writes with a similar compression ratio vs. Apache Parquet. In our tests with Spice, Vortex performs faster than DuckDB with a third of the memory usage, and is much more scalable (multi-file). For real-world deployments, we see the DuckDB Data Accelerator often capping out around 1TB, but Spice Cayenne can do Petabyte-scale. You can read about it at https://spice.ai/blog and in the Spice OSS release notes [4]. This is just the first version, and we’d love to get your feedback! GitHub: https://ift.tt/9DkasJg [1] https://ift.tt/hU9afrV [2] https://ift.tt/X3LHcF1 [3] https://ift.tt/lgbu6VP [4] https://ift.tt/2wzrjn7 https://ift.tt/9N8YVqC December 19, 2025 at 12:30AM

Show HN: Explore Prometheus /metrics endpoints from your terminal https://ift.tt/NAH9dIQ

Show HN: Explore Prometheus /metrics endpoints from your terminal https://ift.tt/ItVbFGm December 18, 2025 at 11:40PM

Show HN: The feature gap "Chat with PDF" tuts and a regulated enterprise system https://ift.tt/N2v7WaP

Show HN: The feature gap "Chat with PDF" tuts and a regulated enterprise system I've spent the last few months architecting a RAG system for a regulated environment. I am not a developer by trade, but I approached this with a strict "systems engineering" and audit mindset. While most tutorials stop at "LangChain + VectorDB", I found that making this legally defensible and operationally stable required about 40+ additional components. We moved from a simple ingestion script to a "Multi-Lane Consensus Engine" (inspired by Six Sigma) because standard OCR/extraction was too hallucination-prone for our use case. We had to build extensive auditing, RBAC down to the document level, and a hybrid Graph+Vector retrieval to get acceptable accuracy The current architecture includes: Ingestion: 4 parallel extraction lanes (Vision, Layout, Text, Legal) with a Consensus Engine ("Solomon") that only indexes data confirmed by multiple sources Retrieval: Hybrid Neo4j (Graph) + ChromaDB (Vector) with Reciprocal Rank Fusion Performance: Semantic Caching (Redis) specifically for similar-meaning queries (40x speedup) Security: Full RBAC, Audit Logging of every prompt/retrieval, and PII masking. I documented the complete feature list and gap analysis https://gist.github.com/2dogsandanerd/2a3d54085b2daaccbb1125... My question to the community: Looking at this list – where is the line between "robust production engineering" and "over-engineering"? For those working in Fintech/Medtech RAG: what critical failure modes am I still missing in this list? https://gist.github.com/2dogsandanerd/2a3d54085b2daaccbb1125601945ceeb December 17, 2025 at 11:20PM