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Hi everyone, I am Kumar, co-founder of Dench (https://denchclaw.com). We were part of YC S24, an agentic workflow company that previously worked with sales floors automating niche enterprise tasks such as outbound calling, legal intake, etc.

Building consumer / power-user software always gave me more joy than FDEing into an enterprise. It did not give me joy to manually add AI tools to a cloud harness for every small new thing, at least not as much as completely local software that is open source and has all the powers of OpenClaw (I can now talk to my CRM on Telegram!).

A week ago, we launched Ironclaw, an Open Source OpenClaw CRM Framework (https://x.com/garrytan/status/2023518514120937672?s=20) but people confused us with NearAI’s Ironclaw, so we changed our name to DenchClaw (https://denchclaw.com).

OpenClaw today feels like early React: the primitive is incredibly powerful, but the patterns are still forming, and everyone is piecing together their own way to actually use it. What made React explode was the emergence of frameworks like Gatsby and Next.js that turned raw capability into something opinionated, repeatable, and easy to adopt.

That is how we think about DenchClaw. We are trying to make it one of the clearest, most practical, and most complete ways to use OpenClaw in the real world.

Demo: https://www.youtube.com/watch?v=pfACTbc3Bh4#t=43

  npx denchclaw

But I use DenchClaw daily for almost everything I do. It also works as a coding agent like Cursor - DenchClaw built DenchClaw. I am addicted now that I can ask it, “hey in the companies table only show me the ones who have more than 5 employees” and it updates it live than me having to manually add a filter.

On Dench, everything sits in a file system, the table filters, views, column toggles, calendar/gantt views, etc, so OpenClaw can directly work with it using Dench’s CRM skill.

The CRM is built on top of DuckDB, the smallest, most performant and at the same time also feature rich database we could find. Thank you DuckDB team!

It creates a new OpenClaw profile called “dench”, and opens a new OpenClaw Gateway… that means you can run all your usual openclaw commands by just prefixing every command with `openclaw --profile dench` . It will start your gateway on port 19001 range. You will be able to access the DenchClaw frontend at localhost:3100. Once you open it on Safari, just add it to your Dock to use it as a PWA.

Think of it as Cursor for your Mac (also works on Linux and Windows) which is based on OpenClaw. DenchClaw has a file tree view for you to use it as an elevated finder tool to do anything on your mac. I use it to create slides, do linkedin outreach using MY browser.

DenchClaw finds your Chrome Profile and copies it fully into its own, so you won’t have to log in into all your websites again. DenchClaw sees what you see, does what you do. It’s an everything app, that sits locally on your mac.

Just ask it “hey import my notion”, “hey import everything from my hubspot”, and it will literally go into your browser, export all objects and documents and put it in its own workspace that you can use.

We would love you all to break it, stress test its CRM capabilities, how it streams subagents for lead enrichment, hook it into your Apollo, Gmail, Notion and everything there is. Looking forward to comments/feedback!

Agent Kanban has 4 main features:

GitOps & team friendly kanban board integration inside VS Code Structured plan / todo / implement via @kanban commands Leverages your existing agent harness rather than trying to bundle a built in one .md task format provides a permanent (editable) source of truth including considerations, decisions and actions, that is resistant to context rot

TinyChart is a free, open-source platform that provides simple and customizable charts for websites and applications. It offers a range of chart types, easy-to-use configuration options, and lightweight performance, making it a versatile choice for data visualization needs.

I'm a multilingual reader (Catalan/Spanish/English/Italian), and I kept hitting the same wall: I'd hear about a book and have no way to know if it existed in my language. Turns out this is a genuinely unsolved problem. There's no single database that tracks which books have been translated into which languages. ISBN registries are fragmented by country. Open Library has great English coverage but gaps elsewhere. Wikidata has surprisingly rich translation data but it's locked behind SPARQL. Google Books is inconsistent across regions.

So I built Zenòdot to cross all four and piece the picture together.

What I found building it:

-The ISBN system is far more broken than I expected. ISBNdb has millions of English records but almost nothing for languages like Basque, Icelandic, or Bengali. Books exist in these languages, they just don't exist in the databases.

-Wikidata was the biggest surprise. It has structured translation data for thousands of works, but extracting it requires SPARQL queries, title resolution across scripts (try matching a book title in Chinese to its English original), and author alias caching. Hard to build, but the results fill gaps that no other source covers.

-The most interesting output isn't what the tool finds; it's what it doesn't find. When someone searches for a book in a language and there's no result, that's a demand signal. "Someone in the world wanted this translation and it doesn't exist." That data could be genuinely useful to publishers.

The tool prioritizes your selected languages, so it shows you editions relevant to you first. The philosophy is "documentary infrastructure”: no recommendations, no social features, no accounts. You search, you find (or don't), you go buy the book wherever you want.

Stack: Next.js 15 (App Router), Supabase, Vercel, TypeScript. Solo project, no funding, about 4 months of work.

If you're multilingual or learning a language, I'd especially love your feedback. Try searching for a book you love and switching between languages, that's where the tool shows its value.

RobotMem is an open-source project that explores the use of artificial memory in robots, allowing them to store and recall information more efficiently. The project aims to advance the field of robot cognition and memory management.

Hey HN, For the past few months, I have been working a lot with Claude code and a huge fan of the tool. When working on some tasks, I noticed Claude spending tokens for simple local tasks like find, grep etc, so I wondered: what if simple local tasks could run on a local LLM and route complex reasoning Claude?

To help answer that question, I started building Locode, a open source CLI that tries this approach.

The idea is: • run simple tasks locally • route complex reasoning to Claude • reduce inference cost and latency • keep the workflow local first

This project is still very early and mostly a fun learning experiment for me. The entire project was built using Claude Code (not vibe coded). I really love the workflow and it inspired a lot of the design. I’m also a huge fan of Ruff, so I took some inspirations from that as well (no rust yet though).

There is a short demo video in the README if you want to see it in action.

Please take it for a spin if you are interested and let me know what you think and/or if you have experience with cli tools and suggestion on improving Locode, I’m happy to learn.

Cheers! Chocks

Instead of giving LLM tools SSH access or installing them on a server, the following:

   promptctl ssh user@server

For example:

  # on remote host
  analyze-config --help
  Usage: analyze-config [OPTIONS] --path <path>

  Prompt inputs:
        --all          
        --path <path>  
        --opt          
        --syntax       
      --sec          

  You are an expert sysadmin and security auditor analyzing   the configuration
  file {{path}}, with contents:
  
  {{cat path}}
  
  Identify:
  
  {{#if (or all syntax) }}- Syntax Problems{{/if}}
  {{#if (or all sec) }}- Misconfigurations and security risks{{/if}}
  {{#if (or all opt) }}- Optimizations{{/if}}
  
  For each finding, state the setting, the impact, a fix, and a severity
  (Critical/Warning/Info).

Github: https://github.com/tgalal/promptcmd/

Documentation: https://docs.promptcmd.sh/

Sup HN,

So I got tired of bouncing between Flightradar, MarineTraffic, and Twitter every time something kicked off globally, so I wrote a dashboard to aggregate it all locally. It’s called Shadowbroker.

I’ll admit I leaned way too hard into the "movie hacker" aesthetic for the UI, but the actual pipeline underneath is real. It pulls commercial/military ADS-B, the AIS WebSocket stream (about 25,000+ ships), N2YO satellite telemetry, and GDELT conflict data into a single MapLibre instance.

Getting this to run without melting my browser was the hardest part. I'm running this on a laptop with an i5 and an RTX 3050, and initially, dumping 30k+ moving GeoJSON features onto the map just crashed everything. I ended up having to write pretty aggressive viewport culling, debounce the state updates, and compress the FastAPI payloads by like 90% just to make it usable.

My favorite part is the signal layer—it actually calculates live GPS jamming zones by aggregating the real-time navigation degradation (NAC-P) of commercial flights overhead.

It’s Next.js and Python. I threw a quick-start script in the releases if you just want to spin it up, but the repo is open if you want to dig into the backend.

Let me know if my MapLibre implementation is terrible, I'm always looking for ways to optimize the rendering.

Why I built Skir: https://medium.com/@gepheum/i-spent-15-years-with-protobuf-t...

Quick start: npx skir init

All the config lives in one YML file.

Website: https://skir.build

GitHub: https://github.com/gepheum/skir

Would love feedback especially from teams running mixed-language stacks.

Every MCP server injects its full tool schemas into context on every turn — 30 tools costs ~3,600 tokens/turn whether the model uses them or not. Over 25 turns with 120 tools, that's 362,000 tokens just for schemas.

mcp2cli turns any MCP server or OpenAPI spec into a CLI at runtime. The LLM discovers tools on demand:

    mcp2cli --mcp https://mcp.example.com/sse --list             # ~16 tokens/tool
    mcp2cli --mcp https://mcp.example.com/sse create-task --help  # ~120 tokens, once
    mcp2cli --mcp https://mcp.example.com/sse create-task --title "Fix bug"

Token savings are real, measured with cl100k_base: 96% for 30 tools over 15 turns, 99% for 120 tools over 25 turns.

It also ships as an installable skill for AI coding agents (Claude Code, Cursor, Codex): `npx skills add knowsuchagency/mcp2cli --skill mcp2cli`

Inspired by Kagan Yilmaz's CLI vs MCP analysis and CLIHub.

https://github.com/knowsuchagency/mcp2cli

Play: https://p.migdal.pl/chromatron-oxide/ Repo: https://github.com/stared/chromatron-oxide/ (educational purpose only) The original: https://www.silverspaceship.com/chromatron/

Full story in the blog post.

Hi HN, I built OpenGraviton, an open-source AI inference engine that pushes the limits of running extremely large LLMs on consumer hardware. By combining 1.58-bit ternary quantization, dynamic sparsity with Top-K pruning and MoE routing, and mmap-based layer streaming, OpenGraviton can run models far larger than your system RAM—even on a Mac Mini. Early benchmarks: TinyLlama-1.1B drops from ~2GB (FP16) to ~0.24GB with ternary quantization. At 140B scale, models that normally require ~280GB fit within ~35GB packed. Optimized for Apple Silicon with Metal + C++ tensor unpacking, plus speculative decoding for faster generation. Check benchmarks, architecture, and details here: https://opengraviton.github.io GitHub: https://github.com/opengraviton This project isn’t just about squeezing massive models onto tiny hardware—it’s about democratizing access to giant LLMs without cloud costs. Feedback, forks, and ideas are very welcome!

Cowleyforniastudios announces the launch of Eyot, a new virtual reality game that allows players to explore a mysterious island and uncover its secrets. The game promises immersive gameplay, stunning visuals, and a compelling narrative.

Engram is an open-source project that aims to provide a secure and decentralized platform for storing and managing personal data. The system leverages blockchain technology to ensure data privacy and integrity, allowing users to control their own information.

Wolfscale.org is a website that provides information about the wolves of North America, including their biology, behavior, and conservation efforts. The site covers topics such as wolf ecology, pack dynamics, and the role of wolves in their ecosystems.

This has been a pet project of mine for the past ~5 months. It consists of six visualizations:

- Spectrogram: Implements the reassignment method for sharper time and frequency resolution. - Spectrum analyzer: A-weighted, frequency guidelines, loudest frequency tooltip. - Waveform: Colored based on frequency, loudness, or static - Oscilloscope: Tracks pitch and autocorrelates against a reference signal, provides stability. Also includes a regular zero-crossing trigger. - Stereometer & Phase meter: Linear and exponential scaling modes, adjustable windows. Multi-band correlation meter. - Loudness (LUFS & RMS): Implements the latest lufs standard. Adjustable timeframes.

Let me know what you think, and give it a star if you think it deserves as much. :] (check out the readme for a more complete enumeration of its features. Currently only available on Linux.)

A DIY Newtonian reflector telescope with dobsonian mount. A fun to do hobby project taking us closer to the moon and beyond. A lot of plans ahead on how to make it much better and portable but this was the first time me and my friend implemented or rather built a telescope.

Have a look at what all we have captured.

I built cursor-tg, a Telegram bot that lets me use Cursor Cloud Agents from my phone.

The idea is simple: sometimes I want to start an agent run, reply to it, or check what changed without opening my laptop. With cursor-tg, I can talk to Cursor agents in Telegram, track their progress, view generated diffs/PRs, and handle simple review actions from chat.

I made this mainly for remote/asynchronous development workflows, where I want quick access to my coding agent while away from my desk.

It is really exciting to be finally be able to (help agent) code anywhere!

Repo: https://github.com/tb5z035i/cursor-tg

Author here. OxiMedia is a clean-room reconstruction of FFmpeg and OpenCV in pure Rust. v0.1.0, 92 crates, ~1.36M lines.

Key decisions: `#![forbid(unsafe_code)]` workspace-wide, patent-free codecs only (AV1/VP9/Opus/FLAC -- no H.264/H.265/AAC ever), async on Tokio, zero C/Fortran deps in default features, native WASM target.

This is v0.1.0 -- APIs are stabilized but not yet battle-tested at scale. Performance benchmarks vs FFmpeg/rav1e/dav1d coming soon.

Feedback on API design welcome, especially the filter graph and transcoding pipeline.

GitHub: https://github.com/cool-japan/oximedia

A competitive multiplayer snake game where AI-controlled snakes written by frontier LLMs (GPT, Claude, Gemini, Grok) go head to head.

AI-powered personal finance analyzer — runs 100% locally, no cloud, no login.

Upload a PDF / CSV / Excel bank or credit card statement → AI extracts and categorizes every transaction → interactive dashboard, spending insights, recurring payment detection & chat with your data.

Hi, I've been working on something I've been thinking for long time but since I had no experience with macOS screen savers I always posponed. Now thanks to Claude I was able to create a screensaver that scroll ANSI files while your computer is idle.

It allow to use local ANS files or packs directly from 16colo.rs.

Repo: https://github.com/lardissone/ansi-saver

Express developers moving to Bun face a full rewrite — every Bun framework (Hono, Elysia) has a completely different API. bunway keeps the exact same app.get(), app.post(), req, res, next pattern but runs on Bun's native HTTP server. Batteries included: routing, CORS, sessions, auth, WebSockets and more in one import. Would love feedback from anyone who's tried migrating Express projects to Bun.

I built µJS because I wanted AJAX navigation without the verbosity of HTMX or the overhead of Turbo.

It intercepts links and form submissions, fetches pages via AJAX, and swaps fragments of the DOM. Single <script> tag, one call to `mu.init()`. No build step, no dependencies.

Key features: patch mode (update multiple fragments in one request), SSE support, DOM morphing via idiomorph, View Transitions, prefetch on hover, polling, and full HTTP verb support on any element.

At ~5KB gzipped, it's smaller than HTMX (16KB) and Turbo (25KB), and works with any backend: PHP, Python, Go, Ruby, whatever.

Playground: https://mujs.org/playground

Comparison with HTMX and Turbo: https://mujs.org/comparison

About the project creation, why and when: https://mujs.org/about

GitHub: https://github.com/Digicreon/muJS

Happy to discuss the project.

I've been building a modern Ultima Online server emulator from scratch. It's not feature-complete (no combat, no skills yet), but the foundation is solid and I wanted to share it early.

What it does today: - Full packet layer for the classic UO client (login, movement, items, mobiles) - Lua scripting for item behaviors (double-click a potion, open a door — all defined in Lua, no C# recompile) - Spatial world partitioned into sectors with delta sync (only sends packets for new sectors when crossing boundaries) - Snapshot-based persistence with MessagePack - Source generators for automatic DI wiring, packet handler registration, and Lua module exposure - NativeAOT support — the server compiles to a single native binary - Embedded HTTP admin API + React management UI - Auto-generated doors from map statics (same algorithm as ModernUO/RunUO)

Tech stack: .NET 10, NativeAOT, NLua, MessagePack, DryIoc, Kestrel

What's missing: Combat, skills, weather integration, NPC AI. This is still early — the focus so far has been on getting the architecture right so adding those systems doesn't require rewiring everything.

Why not just use ModernUO/RunUO? Those are mature and battle-tested. I started this because I wanted to rethink the architecture from scratch: strict network/domain separation, event-driven game loop, no inheritance-heavy item hierarchies, and Lua for rapid iteration on game logic without recompiling.

GitHub: https://github.com/moongate-community/moongatev2

The dotenv-diff library allows developers to easily compare and merge environment variables between different .env files, making it a useful tool for managing configuration settings across different environments.