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Show HN: Mcptoon – Token-efficient MCP CLI client

Show HN: I vibecoded a heavy lift drone

US President hid in catering cart for secret flight in Turkey amid Iran threat

Show HN: Insidedb, an interactive, animated explainer of database internals

Show HN: Opencodex, a free open-source coding agent for VSCode

Show HN: Pyrig – A tool that automates project setup and maintenance # What is pyrig?<p>pyrig is a package and tool that *rigs up* your project. It scaffolds and initializes a complete, fully configured, installed and working Python project with one command and makes the process of developing and maintaining it more seamless and efficient by automating things like configuration management, CLI generation, testing infrastructure, and more.<p># Requirements<p>* Python 3.12+ * Git * uv<p># Quick Start<p><pre><code> uv init my-project --python 3.12 cd my-project uv add pyrig --dev uv run pyrig init </code></pre> See the [Getting Started Guide](<a href="https:&#x2F;&#x2F;Winipedia.github.io&#x2F;pyrig&#x2F;getting-started" rel="nofollow">https:&#x2F;&#x2F;Winipedia.github.io&#x2F;pyrig&#x2F;getting-started</a>) for detailed setup instructions to also fully integrate with GitHub and CI&#x2F;CD from the start.<p># Features<p># [Project Scaffolding &amp; Initialization](<a href="https:&#x2F;&#x2F;Winipedia.github.io&#x2F;pyrig&#x2F;scaffolding" rel="nofollow">https:&#x2F;&#x2F;Winipedia.github.io&#x2F;pyrig&#x2F;scaffolding</a>)<p>`pyrig init` generates a complete project in one command that works out of the box. This includes everything a modern python project needs:<p>* Standardized directory structure * Fully configured dev tools (linters, formatters, type checkers, test frameworks, git hooks, etc.) * End-to-end CI&#x2F;CD pipeline with GitHub Actions and integrated repository protection * Complete and working CLI * And much more...<p># [File &amp; Configuration Management](<a href="https:&#x2F;&#x2F;Winipedia.github.io&#x2F;pyrig&#x2F;config-files" rel="nofollow">https:&#x2F;&#x2F;Winipedia.github.io&#x2F;pyrig&#x2F;config-files</a>)<p>Every generated file is backed by a Python class that validates and merges automatically. Override any config by subclassing, or define entirely new config files — pyrig discovers and manages them for you. Run `pyrig sync` to create or update all config files at once. Run `pyrig mk subcls` to generate a subclass for overriding a specific file.<p># [Automatic CLI](<a href="https:&#x2F;&#x2F;Winipedia.github.io&#x2F;pyrig&#x2F;cli" rel="nofollow">https:&#x2F;&#x2F;Winipedia.github.io&#x2F;pyrig&#x2F;cli</a>)<p>`pyrig init` sets up a CLI for your project that works immediately. Generate and add new commands by running `pyrig mk cmd &lt;name&gt;`. An automatic version command is included that shows the version of your project. Run `my-project version` to see it in action.<p># [Mirror Test Generation &amp; Maintenance](<a href="https:&#x2F;&#x2F;Winipedia.github.io&#x2F;pyrig&#x2F;mirror-tests" rel="nofollow">https:&#x2F;&#x2F;Winipedia.github.io&#x2F;pyrig&#x2F;mirror-tests</a>)<p>Generate test skeletons with `pyrig sync`. This will generate test skeletons for all source modules and update them automatically as your project evolves.<p># [Multi-Package Inheritance and Extensibility Architecture](<a href="https:&#x2F;&#x2F;Winipedia.github.io&#x2F;pyrig&#x2F;architecture" rel="nofollow">https:&#x2F;&#x2F;Winipedia.github.io&#x2F;pyrig&#x2F;architecture</a>)<p>Override and customize any and all behaviour to suit your project&#x27;s needs. pyrig&#x27;s classes are designed for inheritance and composition, allowing you to create custom configurations, tools, and more by subclassing and simply overriding methods. pyrig will automatically discover and use your custom classes without any additional configuration. Run `pyrig mk subcls` to generate a subclass for any pyrig class.<p># [CI&#x2F;CD &amp; Repository Protection](<a href="https:&#x2F;&#x2F;Winipedia.github.io&#x2F;pyrig&#x2F;ci-cd" rel="nofollow">https:&#x2F;&#x2F;Winipedia.github.io&#x2F;pyrig&#x2F;ci-cd</a>)<p>Pyrig generates GitHub Actions workflows for CI&#x2F;CD which automatically test and release your code. They also configure and apply repository protection settings and protection rulesets. Push your code to GitHub after initialization and see it in action.<p># Commands<p>Run `pyrig --help` to see a list of all available commands and their usage. Run `pyrig &lt;command&gt; --help` for more information about a specific command and its usage. Run `my-project --help` to see the automatically generated CLI for your project.<p># Documentation<p>|[*Full Documentation*](<a href="https:&#x2F;&#x2F;Winipedia.github.io&#x2F;pyrig" rel="nofollow">https:&#x2F;&#x2F;Winipedia.github.io&#x2F;pyrig</a>)|The manually written documentation| |:-|:-| |[*CodeWiki*](<a href="https:&#x2F;&#x2F;codewiki.google&#x2F;github.com&#x2F;winipedia&#x2F;pyrig" rel="nofollow">https:&#x2F;&#x2F;codewiki.google&#x2F;github.com&#x2F;winipedia&#x2F;pyrig</a>)|AI-generated documentation| |[*Tutorials*](<a href="https:&#x2F;&#x2F;www.youtube.com&#x2F;@Winipedia-py&#x2F;playlists" rel="nofollow">https:&#x2F;&#x2F;www.youtube.com&#x2F;@Winipedia-py&#x2F;playlists</a>)|YouTube tutorials for pyrig|

Show HN: AI Pulse a fake LED strip beside the macOS Dock that shows agent status Hi HN!<p>I run a few Claude Code sessions in parallel and kept cmd-tabbing around just to find out one of them had been sitting on a permission prompt for ten minutes. There&#x27;s a hardware gadget I liked (called SidePulse.io) so before waiting to get my shipment I built the software version instead :D<p>I hope you like it and find it useful as I do!

Show HN: Keen Code – an agentic-engineered coding agent Hello community!<p>I am here to share a coding agent I have built solo from scratch using agentic engineering. Written in Go, it&#x27;s a proper coding agent, has features you expect from a useful agent for your daily work, with a minimal and simple UI.<p>I have named it Keen Code. The repo is here: <a href="https:&#x2F;&#x2F;github.com&#x2F;mochow13&#x2F;keen-code" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;mochow13&#x2F;keen-code</a><p>Even though it started as an experiment, it is now a full-fledged coding agent for real software engineering work. It supports multiple providers, skills, MCPs, multi-agent orchestration through subagents, automatic compaction, etc.<p>I have been using it for real production-grade work myself, and also for developing itself.<p>Notably, I have worked on two separate ideas in this coding agent:<p>1. Turn Memory<p>In a multi-turn conversation, tool outputs are removed, only tool call traces are retained. Within a single agent loop, agent sees full tool results but in the next turn, it doesn&#x27;t see the tool results anymore.<p>The greatest benefit of this approach is that a lot of tool results that are not needed in following turns don&#x27;t occupy the context. As a result, context window in a multi-turn conversation with Keen Code fills up much slowly compared to other agents. This is why you will regularly see context window coming down from 20% to 1% at the beginning of a new agent turn.<p>Of course, this approach has its pros and cons. If agent requires tool result from a previous call, it doesn&#x27;t have them. But my idea is that tool calls like read, bash, web_fetch are cheap. Do you need to refer to some earlier file you read? Read again. In fact, Claude Code or Codex frequently re-read a file, even though it has read the same file before.<p>I have plans for more effort in this area. I have a few additional ideas to explore and possibly optimise this approach further.<p>If you want to read about it: <a href="https:&#x2F;&#x2F;mochow13.github.io&#x2F;keen-code&#x2F;docs&#x2F;turn-memory.html" rel="nofollow">https:&#x2F;&#x2F;mochow13.github.io&#x2F;keen-code&#x2F;docs&#x2F;turn-memory.html</a><p>2. Skill-Driven MCP<p>Another idea I have implemented is skill-driven MCPs. The goal is similar to what Anthropic did with tool-search-tool: optimise context.<p>In this idea, each MCP server receives a skill. But this skill is not typical &quot;guidance&quot; skill for MCP server usage, rather generated by Keen. Details here: <a href="https:&#x2F;&#x2F;mochow13.github.io&#x2F;keen-code&#x2F;docs&#x2F;mcp-skills.html" rel="nofollow">https:&#x2F;&#x2F;mochow13.github.io&#x2F;keen-code&#x2F;docs&#x2F;mcp-skills.html</a><p>The big advantage is that no server is pre-loaded completely with tool schemas by default. The agent only receives skill frontmatter for the server. If a server is needed, agent loads the full skill file which lists the tools with descriptions. Then agent reads the specific schema file for the particular tool it wants to invoke.<p>The drawback is that each MCP call requires file read operation. But everything is locally saved upon discovery, so it&#x27;s totally fine.<p>---<p>Apart from the above two, I am exploring and playing with other well-known context optimisation ideas like hashline edits.<p>If the above ideas interest you, please do check it out! Here is the CLI usage guideline: <a href="https:&#x2F;&#x2F;mochow13.github.io&#x2F;keen-code&#x2F;docs&#x2F;cli-usage.html" rel="nofollow">https:&#x2F;&#x2F;mochow13.github.io&#x2F;keen-code&#x2F;docs&#x2F;cli-usage.html</a><p>Since the project is open-source, issues and contributions are more than welcome!

Show HN: My local climbing gym from photogrammetry Commented on yesterday&#x27;s Ask HN: What are you working on? (August 2026), thought I might as well submit a Show HN.<p>If you see climbing world cup&#x2F;championship, there is this 3D modelling thing [1]. I want that for my weekly bouldering.<p>I scanned my local climbing gym into 3D mesh using iphone. Built a simple editor to trim, merge, move&#x2F;rotate meshes. You can interact with the mesh, view routes, view climb, etc. So this is unlike many gaussian splatting projects where the main use is for viewing. I built a pipeline in updating climbing walls. Climbing routes are manually annotated. Climbing videos are registered against the 3D mesh. Based on one input video, body positions resolved into 3D&#x2F;4D space. you can view the body landmarks from different angle.<p>COLMAP, OpenMVS, fastapi, svelte, database is just local json files. A read only build is exported so I can host on github page<p>If you climb, or know someone who climbs, would love to hear your feedback. Do you usually record your climbs? If I make this a service, what will make you use it?<p>[1] <a href="https:&#x2F;&#x2F;www.youtube.com&#x2F;shorts&#x2F;8zdUOaCr6DY" rel="nofollow">https:&#x2F;&#x2F;www.youtube.com&#x2F;shorts&#x2F;8zdUOaCr6DY</a>

Amazon backs power plant that may become top source of US climate pollution

Show HN: Needle2: 14MB agentic LLM for phones, wearables, smart home and robots Hey HN,<p>Henry from Cactus here!<p>We previously released Cactus Needle, a 14MB agentic LLM for tool call, device use, and structured extraction for phones, wearables, smart homes, small robots and microcontrollers. We got really great feedback here, and have now incorporated the suggestions to release Needle 2.<p>The whole model is a single 14MB binary that runs a full session in 28MB of RAM; 45m parameters at 2bit compression. Needle hits 500 tokens&#x2F;sec decode speed on a Raspberry Pi 5, sits between 400-1,500 tokens&#x2F;sec on VR devices like Meta Quest 3S and Apple Vision Pro, and ranges 300-700 on sub-$200 phones such as the Samsung A-Series.<p>On the tool call and mobile device use benchmarks, Needle 2 trades wins with closest small models like LFM2.5 230M and Apple Foundation Model, at 5x to 70x smaller, both at f16 vs Needle 2 at 2bit. Needle is based on Simple Attention Networks from our paper (<a href="https:&#x2F;&#x2F;arxiv.org&#x2F;abs&#x2F;2607.18363" rel="nofollow">https:&#x2F;&#x2F;arxiv.org&#x2F;abs&#x2F;2607.18363</a>).<p>Edge AI has lately meant Macs and PCs, but that is just 1.5 billion of over 21 billion connected IoT devices in the world today, and in emerging markets most phones ship under $200, no NPU, cheap GPUs. These include budget phones, Raspberry Pis, microcontrollers, wearables, small robots like Reachy Mini, and connected home devices.<p>A conventional transformer of Needle&#x27;s width and depth spends 164 MFLOPs per token, and even one squeezed down to Needle&#x27;s parameter count spends 87, Needle spends 70. Even on a high-end phone, an always-on assistant lives inside a power budget; every MFLOP is milliwatt-hours, and Needle spends 7x to 85x fewer of them per token than the smallest performant LLMs. More about the architecture in the link.<p>When we structure intelligence for consumer devices as functions with typed parameters, the only hard part is mapping a messy sentence onto them; which function, with which values. Our research found that when framed that way, the problem needs no world knowledge and no open-ended prose, which is why 45M parameters suffice.<p>Needle 2 expands to structured extraction where the schema can be passed in-place of tools and the model returns structured output. You can use Needle as a text-classification model with an enum field, as a summarization model by providing a schema that extracts key fields, everything but free-range decode.<p>Every product has its own tool vocabulary and fine-tuning needle helps it achieve frontier-level performance on custom tasks, so using the python package (<a href="https:&#x2F;&#x2F;github.com&#x2F;cactus-compute&#x2F;needle" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;cactus-compute&#x2F;needle</a>), Needle can be fine-tuned Needle on a Mac&#x2F;PC in minutes to a few hours, with automated data-generation pipeline, just pass a couple samples.<p>Nonetheless, every response carries a learned confidence score based our Cactus Hybrid technique. If above your threshold, act, below it, escalate to the cloud or bigger model. Combining Needle 2 with a private DeepSeek-v4-Flash deployment works particularly well for enterprise-level tasks at barely any cost, we can help with this setup.<p>We have put a lot of thoughts into Needle 2 but might still be missing quite a lot, please use the playground in the provided link to test Needle and share your thoughts, always appreciated!

Launch HN: Stoa Markets (YC S26) – A Marketplace for GPUs and AI Servers Hi HN, we’re Eren, Berat and Kaan. We’re building Stoa (<a href="https:&#x2F;&#x2F;www.stoaexchange.com">https:&#x2F;&#x2F;www.stoaexchange.com</a>), a marketplace for new and used GPUs and AI servers.<p>GPUs are the collateral in the data center buildout. Today, financing terms mostly depend on the offtaker, meaning the company that has committed to use the compute.<p>If that company is a hyperscaler, the financing can look investment grade. If it’s a smaller cloud or startup, terms get expensive fast, even with the same hardware as collateral.<p>The lender’s problem is pretty reasonable. If the borrower defaults and we need to sell these servers, what can we actually get for them? There isn’t a good answer today.<p>We started brokering GPU deals to understand why. It was much more manual than we expected. The hardware is still traded through phone calls, forwarded spreadsheets and long email threads.<p>One week, a seller quoted us $200k for a server node and another quoted $240k for what looked like the same thing. Neither was necessarily wrong. They had different information and could only see their own corner of the market.<p>Before we could compare the quotes, we had to sort out the configuration, condition, warranty, location and delivery terms. It’s the same information Kelley Blue Book attaches to a used-car price through the year, trim, mileage and condition. “An H100 server” isn’t enough information to know what something is worth, just as “a used BMW” isn’t.<p>This is also just a bad way to buy or sell hardware. A buyer looking for the best price shouldn’t have to contact several brokers and dealers separately, repeat the same request and then untangle a pile of different quotes. Sellers shouldn’t have to search for demand one buyer at a time. A market of this size deserves better liquidity.<p>Stoa puts the request into one format and sends it to dealers that have gone through know-your-business (KYB) checks. We verify the company, who owns it and who is allowed to trade for it. Before the request goes out, the buyer confirms the exact configuration, quantity, condition, warranty, location, delivery terms and what will be checked during inspection. Dealers return firm quotes against that same request without seeing each other’s bids. Once a quote is accepted, payment, shipping, delivery and inspection are then tracked through settlement. We don’t take possession of the hardware.<p>We got more than $300M in requests for quotes (RFQs) during our first month.<p>The immediate goal is to make buying and selling this hardware less painful. As trades build up, they also leave lenders with actual resale evidence instead of list prices and one off appraisals.<p>We knew from the beginning that this couldn’t be a software only marketplace. GPU trading runs on relationships, and inventory isn’t shown to just anyone. Dealers need to trust the people bringing them clients, and clients need to trust that quotes will actually turn into trades. We built those relationships over time by brokering deals ourselves. Stoa gives people a cleaner way to trade, from the first RFQ through settlement, but it doesn’t replace the trust underneath. Those relationships, and the history of who actually follows through, are a big part of our process.<p>We’ve known each other for more than ten years. We have founded companies, traded interest rate derivatives, built trading and pricing systems for oil and gas. We learned GPU trading by doing the deals ourselves, and Stoa grew out of the problems we kept running into.<p>We charge a tiered fee on completed trades, with lower fees at higher volumes. It’s free to sign up at <a href="https:&#x2F;&#x2F;www.stoaexchange.com&#x2F;signup">https:&#x2F;&#x2F;www.stoaexchange.com&#x2F;signup</a>. If you’ve bought, sold, financed or had to liquidate GPUs, would be great to hear your take!

What's the best programming language for coding agents? Related: <i>Which programming languages are most token-efficient?</i> - <a href="https:&#x2F;&#x2F;news.ycombinator.com&#x2F;item?id=46582728">https:&#x2F;&#x2F;news.ycombinator.com&#x2F;item?id=46582728</a> - Jan 2026 (91 comments)

Show HN: PicPocket – Dedicated 'chats' for photo-sharing (share to organize) I built PicPocket because my photo gallery, which is largely an unstructured dataset, was already organized when I shared my photos with others. Namely, whenever I take photos on a trip&#x2F;event&#x2F;etc. with other people, I always end up sharing those photos with them on WhatsApp. This act of sharing implicitly &#x27;tags&#x27; the people who were there, and organizes them into clusters of photos, but this effort isn&#x27;t utilized. The point of PicPocket is to piggy-back on the effort of sharing, to simultaneously organize and store those photos.

Show HN: Ante, a coding agent in a single binary that runs offline

Extreme 220GHz+Broadband Silicon Capacitor X2SC 0201M 22nF BV11

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Mistral Patent for "Code implemented tool calls"

Show HN: 100% native Swift harness (NOT Electron) hi everybody, I’ve been working on this harness that is all native Swift for macOS.<p>It’s fully featured with every feature i could find in cline, codex, and claude code.<p>There is all swift command line too<p>It’s taking me a long, long time, a few months to build this, and it’s fully open source Apache 2 licensed.<p>Hoping people fork this and make many branches<p>I’m looking for people who want to work on something that has much lower memory usage and much more potential to be just more efficient. Every other single harness has is written in using electron, so this harness is really unique in this way. It’s connected to trusted router so that it has end-to-end encryption confidential mode as well as access to hundreds of models, any model in the world. It works great with Deepseek. it’s great for swift development ios development.<p>and for people who love Linux, I also made a compatibility layer that lets you compile SwiftUI into native Linux so that you either can new or QT actually so that you can just compile all the code directly and make it run on Linux