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[Other] Show HN: Open-source implementation of Stanford's self-learning agent framework We implemented Stanford&#x27;s Agentic Context Engineering paper which shows agents can improve their performance just by evolving their own context.<p>How it works: Agents execute tasks, reflect on what worked&#x2F;failed, and curate a &quot;playbook&quot; of strategies. All from execution feedback - no training data needed.<p>Happy to answer questions about the implementation or the research!

[IDE/Editor] Flowistry: An IDE plugin for Rust that focuses on relevant code

[Other] Lux: A luxurious package manager for Lua

[Monitoring/Observability] Show HN: ServiceRadar – open-source Network Observability Platform ServiceRadar is an open-source platform for distributed, secure network management and observability, scaling to 100k+ devices. Born from frustration with complex traditional NMS tools like Zabbix, it bridges legacy (SNMP&#x2F;syslog) and modern (gNMI, OTLP) protocols for cloud-native environments.<p>We built ServiceRadar to simplify monitoring hybrid telecom networks, evolving it into a Kubernetes-native solution with Helm and Docker support. It uses mTLS with SPIFFE&#x2F;SPIRE, NATS JetStream for event streaming (90M+ EPS), and SRQL for intuitive queries. Integrated with OpenTelemetry, Prometheus, and CloudEvents, it fills the network visibility gap in CNCF’s application-focused observability stack.<p>We’re seeking early adopters to try our demo or deploy locally—no sign-up needed. Feedback on usability or contributions for new protocols would be awesome.<p>Quick Start: helm install serviceradar carverauto&#x2F;serviceradar or docker compose up -d<p>GitHub: <a href="https:&#x2F;&#x2F;github.com&#x2F;carverauto&#x2F;serviceradar" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;carverauto&#x2F;serviceradar</a> (please star!)<p>Docs: <a href="https:&#x2F;&#x2F;docs.serviceradar.cloud" rel="nofollow">https:&#x2F;&#x2F;docs.serviceradar.cloud</a><p>Join our Discord or use GitHub Issues to share thoughts.

[Other] Show HN: ASCII Automata ASCII AUTOMATA is a tool to analyze the visual connectivity of characters in textmode fonts. It works by scoring edge connectivity of each piece and finding the best matching neighbour piece. Every time it places a piece, it &quot;grows&quot; towards the edges it touches by placing a matching piece. The red heatmap shows how frequently each character is used, useful for analyzing the fonts.<p>I initially made it as a tool for myself. When I design textmode art fonts it is sometimes difficult to figure out if a specific character would actually be useful for drawing or not. I wanted a tool which would show how useful and versatile some character is, and how well it connects to all other pieces.<p>But, as it turned out, this tool produces unexpectedly beautiful emergent patterns, so I made it into a proper little toy-tool for anyone to play around with.<p>Sidenote: it was also a good opportunity to test a new method for constructing a responsive semi-complex UI.<p>I made a web component which renders text as SVG paths using hershey vector fonts. The SVG fills the parent element, and applies stroke after the stretching happens: so strings &quot;a&quot; and &quot;aaa&quot; take the same amount of space, while remaining legible because the stroke is independent of the text&#x27;s transformations. Thus, I never have problems with overflowing text in the UI!<p>The layout is made with a CSS grid. For example the sidebar is simply &lt;div style=&quot;--cols:8;--rows:41;&quot; class=&quot;sidebar grid&quot;&gt; and then each UI element gets a position and size &lt;vec-text style=&quot;--x:1;--y:19;--w:2;--h:1;&quot;&gt;Cell Width&lt;&#x2F;vec-text&gt; . As a result, the layout is easy to make, the sidebar itself can be any size or shape,all the UI elements stay exactly where I put them, and all text remains legible due to the stretchy, monolined vector font web component. It&#x27;s great!<p>The WHOLE UI layout is just 120 lines of HTML, and 40 lines of CSS (for around 90 UI elements)!<p>(it did take a while to fiddle with the coordinate numbers, but I&#x27;m working on a wysiwyg tool to make that easier too...)<p>[crossposted this comment from mastodon: <a href="https:&#x2F;&#x2F;typo.social&#x2F;@gdc&#x2F;115405978249292146" rel="nofollow">https:&#x2F;&#x2F;typo.social&#x2F;@gdc&#x2F;115405978249292146</a>]

[Other] Code from MIT's 1986 SICP video lectures

[Other] Show HN: We packaged an MCP server inside Chromium Hey HN, we just shipped a browser with an inbuilt MCP server!<p>We&#x27;re a YC startup (S24) building BrowserOS — an open‑source Chromium fork. We&#x27;re a privacy‑first alternative to the new wave of AI browsers like Dia, Perplexity Comet. Since launching ~3 months ago, the #1 request has been to expose our browser as an MCP server.<p>-- Google beat us to launch with chrome-devtools-mcp (solid product btw), which lets you build&#x2F;debug web apps by connecting Chrome to coding assistants. But we wanted to take this a step further: we packaged the MCP server directly into our browser binary. That gives three advantages:<p>1. MCP server setup is super simple — no npx install, no starting Chrome with CDP flags, you just download the BrowserOS binary.<p>2. with our browser&#x27;s inbuilt MCP server, AI agents can interact using your logged‑in sessions (unlike chrome-devtools-mcp which starts a fresh headless instance each time)<p>3. our MCP server also exposes new APIs from Chromium&#x27;s C++ core to click, type, and draw bounding boxes on a webpage. Our APIs are also not CDP-based (Chrome Debug Protocol) and have robust anti-bot detection.<p>-- Few example use cases for BrowserOS-mcp are:<p>a) *Frontend development with Claude Code*: instead of screenshot‑pasting, claude-code gets WYSIWYG access. It can write code, take a screenshot, check console logs, and fix issues in one agentic sweep. Since it has your sessions, it can do QA stuff like &quot;test the auth flow with my Google Sign‑In.&quot; Here&#x27;s a video of claude-code using browserOS to improve the css styling with back-and-forth checking: <a href="https:&#x2F;&#x2F;youtu.be&#x2F;vcSxzIIkg_0" rel="nofollow">https:&#x2F;&#x2F;youtu.be&#x2F;vcSxzIIkg_0</a><p>b) *Use as an agentic browser:* You can install BrowserOS-mcp in claude-code or Claude Desktop and do things like form-filling, extraction, multi-step agentic tasks, etc. It honestly works better than Perplexity Comet! Here&#x27;s a video of claude-code opening top 5 hacker news posts and summarizing: <a href="https:&#x2F;&#x2F;youtu.be&#x2F;rPFx_Btajj0" rel="nofollow">https:&#x2F;&#x2F;youtu.be&#x2F;rPFx_Btajj0</a><p>-- *How we packaged MCP server inside Chromium binary*: We package the server as a Bun binary and expose MCP tools over HTTP instead of stdio (to support multiple sessions). And we have a BrowserOS controller installed as an extension at the application layer which the MCP server connects to over WebSocket to control the browser. Here&#x27;s a rough architecture diagram: <a href="https:&#x2F;&#x2F;dub.sh&#x2F;browseros-mcp-diag" rel="nofollow">https:&#x2F;&#x2F;dub.sh&#x2F;browseros-mcp-diag</a><p>-- *How to install and use it:* We put together a short guide here: <a href="https:&#x2F;&#x2F;git.new&#x2F;browseros-mcp" rel="nofollow">https:&#x2F;&#x2F;git.new&#x2F;browseros-mcp</a><p>Our vision is to reimagine the browser as an operating system for AI agents, and packaging an MCP server directly into it is a big unlock for that!<p>I&#x27;ll be hanging around all day, would love to get your feedback and answer any questions!

[Other] I built an F5 QKview scanner for CISA ED 26-01

[Other] Show HN: OnlyJPG – Client-Side PNG/HEIC/AVIF/PDF/etc to JPG TL;DR: private, in-browser converter that turns pretty much any image file format into standard JPEGs. Everything runs locally. No uploads.<p>This started as a five-minute job and forty hours later...<p>I wanted to convert a HEIC without uploading it anywhere, so I wrestled Emscripten&#x2F;WebAssembly to run Google&#x27;s Jpegli inside a Web Worker. Now there&#x27;s a small UI and it handles a bunch of formats.<p>Just about the only thing it can&#x27;t decode is JXL - but there&#x27;s still some JPEG XL magic in there: XYB perceptual color quantization is enabled by default via Jpegli.<p>The upside of all this over-engineering is privacy and compatibility: images are processed entirely on your machine and never touch a server; the output is a regular JPEG that works everywhere.<p>I could have used a CLI, sure — but where&#x27;s the fun in that?<p>Would love feedback on edge cases and defaults.<p>Tested on Firefox, Chrome, and Safari.<p>Cheers!

[Other] Show HN: Code First CDC from Postgres to ClickHouse with MooseStack

[API/SDK] Cloudflare Sandbox SDK

[Other] Show HN: Kite – A modern, lightweight Kubernetes dashboard An early version was shown before, and now it works even better.<p>Enjoy！

[CLI Tool] Run interactive commands in Gemini CLI

[CLI Tool] Launch HN: Inkeep (YC W23) – Open Source Agent Builder Hi HN! I&#x27;m Nick from Inkeep. We built an agent builder with true 2-way sync between code and a drag-and-drop visual editor, so devs and non-devs can collaborate on the same agents. Here’s a demo video: <a href="https:&#x2F;&#x2F;go.inkeep.com&#x2F;video">https:&#x2F;&#x2F;go.inkeep.com&#x2F;video</a>.<p>As a developer, the flow is: 1) Build AI Chat Assistants or AI Workflows with the TypeScript SDK 2) Run `inkeep push` from your CLI to publish 3)Edit agents in the visual builder (or hand off to non-technical teams) 4) Run `inkeep pull to edit in code again.<p>We built this because we wanted the accessibility of no-code workflow builders (n8n, Zapier), but the flexibility and devex of code-based agent frameworks (LangGraph, Mastra). We also wanted first-class support for chat assistants with interactive UIs, not just workflows. OpenAI got close, but you can only do a one-time export from visual builder to code and there’s vendor lock-in.<p>How I&#x27;ve used it: I bootstrapped a few agents for our marketing and sales teams, then was able to hand off so they can maintain and create their own agents. This has enabled us to adopt agents across technical and non-technical roles in our company on a single platform.<p>To try it, here’s the quickstart: <a href="https:&#x2F;&#x2F;go.inkeep.com&#x2F;quickstart">https:&#x2F;&#x2F;go.inkeep.com&#x2F;quickstart</a>.<p>We leaned on open protocols to make it easy to use agents anywhere: An MCP endpoint, so agents can be used from Cursor&#x2F;Claude&#x2F;ChatGPT A Chat UI library with interactive elements you can customize in React An API endpoint compatible with the Vercel AI SDK `useChat` hook Support for Agent2Agent (A2A) so they work with other agent ecosystems<p>We made some practical templates like a customer_support, deep_research, and docs_assistant. Deployment is easy with Vercel&#x2F;Docker with a fair-code license and there&#x27;s a traces UI and OTEL logs for observability.<p>Under the hood, we went all-in on a multi-agent architecture. Agents are made up of LLMs, MCPs, and agent-to-agent relationships. We’ve found this approach to be easier to maintain and more flexible than traditional “if&#x2F;else” approaches for complex workflows.<p>The interoperability works because the SDK and visual builder share a common underlying representation, and the Inkeep CLI bridges it with a mix of LLMs and TypeScript syntactic sugar. Details in our docs: <a href="https:&#x2F;&#x2F;docs.inkeep.com">https:&#x2F;&#x2F;docs.inkeep.com</a>.<p>We’re open to ideas and contributions! And would love to hear about your experience building agents - what works, hasn’t worked, what’s promising?

[Other] Hyperflask – Full stack Flask and Htmx framework

[Other] Show HN: Modshim – a new alternative to monkey-patching in Python I&#x27;ve invented a new alternative to forking &#x2F; vendoring &#x2F; monkey-patching packages in Python.<p>It&#x27;s a bit like OverlayFS for Python modules - it allows you write modifications for a target module (lower) in a new module (upper), and have these combined in a new virtual module (mount).<p>It works by rewriting imports using AST transformations, then running both the lower and upper module&#x27;s code in the new Python module.<p>This prevents polluting the global namespace when monkey-patching, and means if you want to make changes to a third-party package, you don&#x27;t have to take on the maintenance burden of forking, you can package and distribute just your changes.

[Build/Deploy] Show HN: Pxxl App – A Nigerian Alternative to Vercel, Render, and Netlify Hi HN,<p>I built Pxxl App — a free web hosting and deployment platform for developers in Nigeria and beyond. It’s a Nigerian alternative to Vercel, Render, and Netlify, designed for those who want a simple, fast, and barrier-free way to host both frontend and backend apps.<p>With Pxxl App, you can connect your Git repo and deploy in seconds — no credit card, no limits. You’ll get a live subdomain like yourapp.pxxl.pro, automatic builds, and continuous deployment.<p>It supports: • Frontend frameworks: React, Next.js, Vue, Svelte, and more • Backend projects: Node.js, PHP, and Python • Features like environment variables, CI&#x2F;CD, and instant rollback<p>The goal is to make cloud deployment accessible to African and global developers without the typical payment or region restrictions.<p>It’s completely free to start, and I’d love to hear feedback from the HN community on how to improve it or what features you’d want next.<p>Check it out: <a href="https:&#x2F;&#x2F;pxxl.app" rel="nofollow">https:&#x2F;&#x2F;pxxl.app</a>

[Other] Show HN: Cmux – Coding Agent Multiplexer HN,<p>I&#x27;m stoked to share this product I&#x27;ve been working on non-stop for the past few weeks. It&#x27;s an immersive GUI experience for working with many coding agents in parallel. The UX should be familiar to Claude Code users, but we took advantage of the GUI nature to add in a bunch more.<p>cmux is early but certainly usable—almost all of our internal cmux development rolls through cmux itself. Please let me know your thoughts and feedback!

[DevOps] Show HN: Specific (YC F25) – Build backends with specifications instead of code Hi folks! Iman and I (Fabian) have been building Specific for a while now and are finally opening up our public beta.<p>Specific is a platform for building backend APIs and services entirely through natural-language specifications and tests, without writing code. We then automatically turn your specs into a working system and deploy it for you, along with any infrastructure needed.<p>We know a lot of developers who have already adopted spec-driven development to focus on high-level design and let coding agents take care of implementation. We are attempting to take this even further by making the specs themselves the source of truth. Of course, we can’t blindly trust coding agents to follow the spec, so we also support adding tests that will run to ensure the system behaves as expected and to avoid regressions.<p>There is so much ground to cover, so we are focusing on a smaller set of initial features that in our experience should cover a large portion of backends:<p>- An HTTP server for each project. Authentication can be added by simply stating in the spec how you want to protect your endpoint.<p>- A database automatically spun up and schema configured if the spec indicates persistence is needed.<p>- External APIs can be called. You can even link out to API docs in your specs.<p>You currently can’t see the generated code, but we are working on enabling it. Of course, we don’t claim any ownership of the generated code and will gladly let you export it and continue building elsewhere.<p>Specific is free to try and we are really eager to hear your feedback on it!<p>Try it here: <a href="https:&#x2F;&#x2F;app.specific.dev">https:&#x2F;&#x2F;app.specific.dev</a>

[Other] Show HN: Osaurus – Ollama-Compatible Runtime for Apple Foundation Models Osaurus is an open-source local inference runtime for macOS, written in Swift and optimized for Apple Silicon.<p>It lets you run Apple Foundation Models locally — fully accelerated by the Neural Engine — while also exposing OpenAI- and Ollama-compatible endpoints, so you can connect your favorite apps, tools, or clients without any code changes.<p>Key points:<p>* Supports Apple Foundation Models natively<p>* Compatible with OpenAI &amp; Ollama APIs<p>* ~7 MB binary, runs locally (no cloud, no telemetry)<p>* MIT Licensed, open source<p>Project: <a href="https:&#x2F;&#x2F;osaurus.ai" rel="nofollow">https:&#x2F;&#x2F;osaurus.ai</a><p>Source: <a href="https:&#x2F;&#x2F;github.com&#x2F;dinoki-ai&#x2F;osaurus" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;dinoki-ai&#x2F;osaurus</a><p>We’re exploring what a local-first AI ecosystem could look like — where inference, privacy, and creativity all happen on your own hardware. Feedback and testing welcome!