🛠️ All DevTools

[Other] Ripple – A TypeScript UI framework that takes the best of React, Solid, Svelte

[Other] Catalog of official Microsoft MCP (Model Context Protocol) server implementations for AI-powered data access and tool integration

[Other] Show HN: Docustore – Vectorized Technical Documentations docustore's aim is to provide up-to-date, off-the shelf and plug-and-play context for LLMs from a curated list of frameworks/sdks. It has a 4 step pipeline: scrape the documentation - clean it - vectorize it - package it. My vision is to host it somewhere and develop an API/MCP around it so it will be development-environment agnostic.

[Other] Help AI Truly Understand Your UI Modification Intent Snapmark helps AI precisely understand your UI modification intent through visual selection and accurate DOM information, generating code that truly meets your expectations.

[Other] Coding challenges that feel real, not rehearsed Join our Beta now. Plaicer is a developer-first platform built entirely around real-world coding challenges. Instead of textbook problems, developers prove their skills by solving practical tasks, rising through levels, and unlocking career opportunities.

[Other] Software to supercharge your daily output. Ash List provides a diverse selection of software designed for productivity. Find the tools that align with your needs here.

[Other] Simple pulse surveys, tailored for engineering teams Simple pulse surveys that help engineering managers understand team health. Simple, focused feedback collection via Slack. Built for developers, by developers.

[Other] The ultimate A/B testing app for Webflow Make data-driven decisions for your Webflow site with Optibase. Test everything from copy to design or even entire pages and improve your conversions.

[Monitoring/Observability] The all-in-one monitoring tool for your entire website The all-in-one monitoring tool for your entire website

[Other] Your new software engineering teammate One agent for everywhere you code—included in ChatGPT Plus, Pro, Business, Edu, and Enterprise plans.

[Other] Typing practice for coding TurboType helps you master coding speed with real-world typing practice. It supports 10+ programming languages, gives instant feedback, and tracks your progress. Become a faster, more confident programmer with TurboType.

[Monitoring/Observability] Real-time log analysis terminal UI A powerful, real-time log analysis terminal UI inspired by k9s. Analyze log streams with beautiful charts, AI-powered insights, and advanced filtering.

[Other] Checkpoints for claude code Automatic version control and checkpoint management for Claude Code projects. Track changes, create instant checkpoints, and restore previous states with confidence.

[Other] Clean reading mode — one click, no distractions. Cut the clutter. Focus better. Clean blog pages with 1 click. FocusCutter helps students and productivity users read distraction-free by removing ads, popups, notification bars, and side clutter from any article or blog.

[Other] Expert LSP the official language server implementation for Elixir

[Other] Building your own CLI coding agent with Pydantic-AI

[Other] Chronicle – Idiomatic, type safe event sourcing framework for Go

[Other] Show HN: Grammit – Local-only AI grammar checker (Chrome extension) Hey HN, I wanted a grammar checker that didn’t send my writing to someone&#x27;s servers, so we built Grammit, a Chrome extension that runs grammar checks locally using an LLM. Your text never leaves your computer during checking.<p>Here’s a 2-minute overview: <a href="https:&#x2F;&#x2F;www.loom.com&#x2F;share&#x2F;baf501ee6cf14a919a7384128246ed67" rel="nofollow">https:&#x2F;&#x2F;www.loom.com&#x2F;share&#x2F;baf501ee6cf14a919a7384128246ed67</a><p>Because it uses an LLM, it catches more than spelling and grammar. For example, it can correct some wrong statements like “The first US president was Benjamin Franklin.”<p>Grammit also includes an in-page writing assistant that can rephrase or draft new text. It also uses the local LLM.<p>We used many new web features to build this, such as:<p>- Chrome’s new Prompt API to talk to the local model.<p>- Anchor Positioning API to place the UI with minimal impact on the DOM.<p>- CSS Custom Highlights API for inline error marking.<p>- The new CSS sign() function to create CSS-driven layout with discontinuities.<p>Part of the fun of being early adopters of bleeding edge tech is we’re discovering new Chrome bugs (e.g., <a href="https:&#x2F;&#x2F;issues.chromium.org&#x2F;issues&#x2F;428354426" rel="nofollow">https:&#x2F;&#x2F;issues.chromium.org&#x2F;issues&#x2F;428354426</a>, <a href="https:&#x2F;&#x2F;issues.chromium.org&#x2F;issues&#x2F;428039224" rel="nofollow">https:&#x2F;&#x2F;issues.chromium.org&#x2F;issues&#x2F;428039224</a>).<p>I’d love your feedback on:<p>- Where the UX feels rough<p>- What do you think of the corrections and suggestions<p>Happy to answer questions about the tech or the Prompt API. Thanks for trying it out!<p>Chrome Web Store extension link: <a href="https:&#x2F;&#x2F;chromewebstore.google.com&#x2F;detail&#x2F;grammit-the-ai-grammar-ch&#x2F;pkfmoknmnkbidlniedaloiijibdpjjmm" rel="nofollow">https:&#x2F;&#x2F;chromewebstore.google.com&#x2F;detail&#x2F;grammit-the-ai-gram...</a>

[Monitoring/Observability] Show HN: MCPcat – A free open-source library for MCP server monitoring Hey everyone!<p>We&#x27;ve been working with several MCP server maintainers and we noticed some difficulties getting drop-in logging and identity attribution working out of the box with existing vendors. A couple of challenges we hoped to solve were: - Baseline piping of tool calls to traditional vendors - How to tie tool calls to a “user session” - Understanding the context behind tool calls made by agents<p>So we built something. :) The MCPcat library is completely free to use, MIT licensed, and provides a one-line solution for adding logging and observability to any vendor that supports OpenTelemetry. We added custom support for Datadog and Sentry because we personally use those vendors, but we’re happy to add more if there’s interest.<p>Here’s how it works:<p><pre><code> mcpcat.track(serverObject, {...options…}) </code></pre> This initializes a series of listeners that: 1. Categorize events within the same working session 2. Publish those events directly to your third-party data provider<p>Optionally, you can redact sensitive data. The data never touches our servers (unless you opt in to additional contextual analysis, which I mention below).<p>Some teams might also want a better understanding of “what use cases are people finding with my MCP server.” For that, we provide a separate dashboard that visualizes the user journey in more detail (free for a high baseline of monthly usage and always free for open source projects).<p>We have two SDKs so far: Python SDK: &lt;<a href="https:&#x2F;&#x2F;github.com&#x2F;MCPCat&#x2F;mcpcat-python-sdk" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;MCPCat&#x2F;mcpcat-python-sdk</a>&gt; TypeScript SDK: &lt;<a href="https:&#x2F;&#x2F;github.com&#x2F;MCPCat&#x2F;mcpcat-typescript-sdk" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;MCPCat&#x2F;mcpcat-typescript-sdk</a>&gt;<p>Other SDKs are on the way!

[API/SDK] Show HN: SwiftAI – open-source library to easily build LLM features on iOS/macOS We built SwiftAI, an open-source Swift library that lets you use Apple’s on-device LLMs when available (Apple opened access in June), and fall back to a cloud model when they aren’t available — all without duplicating code.<p>SwiftAI gives you: - A single, model-agnostic API - An agent&#x2F;tool loop - Strongly-typed structured outputs - Optional chat state<p>Backstory: We started experimenting with Apple’s local models because they’re free (no API calls), private, and work offline. The problem: not all devices support them (older iPhones, Apple Intelligence disabled, low battery, etc.). That meant writing two codepaths — one for local, one for cloud — and scattering branching logic across the app. SwiftAI centralizes that decision. Your feature code stays the same whether you’re on-device or cloud.<p>Example<p><pre><code> import SwiftAI let llm: any LLM = SystemLLM.ifAvailable ?? OpenaiLLM(model: &quot;gpt-5-mini&quot;, apiKey: &quot;&lt;key&gt;&quot;) let response = try await llm.reply(to: &quot;Write a haiku about Hacker News&quot;) print(response.content) </code></pre> It&#x27;s open source — we&#x27;d love for you to try it, break it, and help shape the roadmap. Join our discord &#x2F; slack or email us at root@mit12.dev.<p>Links<p>- GitHub (source, docs): <a href="https:&#x2F;&#x2F;github.com&#x2F;mi12labs&#x2F;SwiftAI" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;mi12labs&#x2F;SwiftAI</a><p>- System Design: <a href="https:&#x2F;&#x2F;github.com&#x2F;mi12labs&#x2F;SwiftAI&#x2F;blob&#x2F;main&#x2F;Docs&#x2F;Proposals&#x2F;001-llm-api.md" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;mi12labs&#x2F;SwiftAI&#x2F;blob&#x2F;main&#x2F;Docs&#x2F;Proposals...</a><p>- Swift Package Index (compat&#x2F;builds): <a href="https:&#x2F;&#x2F;swiftpackageindex.com&#x2F;mi12labs&#x2F;SwiftAI" rel="nofollow">https:&#x2F;&#x2F;swiftpackageindex.com&#x2F;mi12labs&#x2F;SwiftAI</a><p>- Discord <a href="https:&#x2F;&#x2F;discord.com&#x2F;invite&#x2F;ckfVGE5r" rel="nofollow">https:&#x2F;&#x2F;discord.com&#x2F;invite&#x2F;ckfVGE5r</a> and slack <a href="https:&#x2F;&#x2F;mi12swiftai.slack.com&#x2F;join&#x2F;shared_invite&#x2F;zt-3c3lr6dat-jJ8BHBsdWc47o4FDu2CgHQ#&#x2F;shared-invite&#x2F;email" rel="nofollow">https:&#x2F;&#x2F;mi12swiftai.slack.com&#x2F;join&#x2F;shared_invite&#x2F;zt-3c3lr6da...</a>