🛠️ All DevTools

[Other] Zero-friction recipient list hygiene for outlook ClearSend is an open-source MS Outlook add-in that helps you manage email recipients with powerful automation features such as alphabetical sorting, de-duplication or external domains detection. Processing 100% on the client-side, data is never sent anywhere.

[Testing] GenAI-Native Software Testing Agent KaneAI by LambdaTest is the world's first GenAI-Native testing agent for fast-paced Quality Engineering teams. It offers AI-driven test authoring, management, and debugging, enabling users to plan, author and evolve complex test cases using natural language.

[Monitoring/Observability] Hit Based log management & real-time alerts | sumtower Centralise your logs, get real-time alerts, and collaborate with your team. Simple, transparent pricing for startups, DevOps, and small businesses.

[CLI Tool] Postman for your terminal 🦣 mozzy - Beautiful JSON-native HTTP client for your terminal. Think Postman, but for developers who live in the command line.

[Other] All developer tools in one place Explore a powerful collection of tools for developers, all in one place. Not everyone gets it. But you do.

[Other] Manage tasks smarter and move faster with WorkVib Manage tasks smarter & move faster with WorkVib.Task management platform built for modern teams. Plan sprints, manage backlogs, track performance, and chat in real time. all in one place. Reduce tool fatigue, improve productivity, and deliver projects faster.

[Other] Pick colors and check WCAG contrast instantly Clarity is a simple, accurate macOS app for designers and developers to pick colors, check WCAG contrast ratios, and build accessible palettes. Pick from your screen, adjust with pro-level sliders, and get instant AA/AAA compliance results.

[Other] SaaS for managing development teams through Git commit BCTO lets you track your dev team’s daily work bug fixes, updates, testing, and deployments all from Git commits for transparent, accurate insights. View code changes, explore developer profiles, and manage tasks, hiring, and Jira tickets in one platform.

[Code Quality] Show HN: Wispbit - Linter for AI coding agents Hey HN! Ilya and Nikita here. We&#x27;re building wispbit (<a href="https:&#x2F;&#x2F;wispbit.com" rel="nofollow">https:&#x2F;&#x2F;wispbit.com</a>) - a tool that helps keep codebase standards alive.<p>With the help of AI coding tools, engineers are writing more code than ever. Code output has increased, but the tooling to manage this hasn&#x27;t improved. Background agents still write bad code, and your IDE still writes slop without the right context.<p>So we built wispbit. It works by scanning your codebase for patterns you already use, and coming up with rules. Rules are kept up to date as standards change, and you can edit rules any time.<p>You can enforce these rules during code review, and because we have this rules system, you can run a CLI locally to review using these rules. You can think of it as a portable rules file that you can bring anywhere.<p>We put a lot of work into making a system that produces good rules and avoids slop. For repository crawling, we have an agent that dispatches subagents, similar to Anthropic&#x27;s research agent. These subagents will go through and look for common patterns within modules and directories, and report back to the main agent, which synthesizes the results. We also do a historical scan on your pull request comments, determine which ones were addressed, filter out comments that wouldn&#x27;t make a good rule, and use that to create or update rules.<p>Our early users are seeing 80%+ resolution rates, meaning that 80% of comments that wispbit makes are resolved.<p>Long-term, we see ourselves being a validation layer for AI-written code. With tools like Devin and Cursor, we find ourselves having to re-prompt the same solution many times. We still don&#x27;t know the long-term implications on AI-assisted codebases, so we want to get in front of that as soon as possible.<p>We&#x27;ve opened up signups for free to HN folks at <a href="https:&#x2F;&#x2F;wispbit.com" rel="nofollow">https:&#x2F;&#x2F;wispbit.com</a>. We&#x27;re also around to chat and answer questions!

[Other] Show HN: An open source access logs analytics script to block bot attacks This is a small PoC Python project for web server access logs analyzing to classify and dynamically block bad bots, such as L7 (application-level) DDoS bots, web scrappers and so on.<p>We&#x27;ll be happy to gather initial feedback on usability and features, especialy from people having good or bad experience wit bots.<p>*Requirements*<p>The analyzer relies on 3 Tempesta FW specific features which you still can get with other HTTP servers or accelerators:<p>1. JA5 client fingerprinting (<a href="https:&#x2F;&#x2F;tempesta-tech.com&#x2F;knowledge-base&#x2F;Traffic-Filtering-by-Fingerprints&#x2F;" rel="nofollow">https:&#x2F;&#x2F;tempesta-tech.com&#x2F;knowledge-base&#x2F;Traffic-Filtering-b...</a>). This is a HTTP and TLS layers fingerprinting, similar to JA4 (<a href="https:&#x2F;&#x2F;blog.foxio.io&#x2F;ja4%2B-network-fingerprinting" rel="nofollow">https:&#x2F;&#x2F;blog.foxio.io&#x2F;ja4%2B-network-fingerprinting</a>) and JA3 fingerprints. The last is also available in Envoy (<a href="https:&#x2F;&#x2F;www.envoyproxy.io&#x2F;docs&#x2F;envoy&#x2F;latest&#x2F;api-v3&#x2F;extensions&#x2F;filters&#x2F;listener&#x2F;tls_inspector&#x2F;v3&#x2F;tls_inspector.proto.html" rel="nofollow">https:&#x2F;&#x2F;www.envoyproxy.io&#x2F;docs&#x2F;envoy&#x2F;latest&#x2F;api-v3&#x2F;extension...</a>) or Nginx module (<a href="https:&#x2F;&#x2F;github.com&#x2F;fooinha&#x2F;nginx-ssl-ja3" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;fooinha&#x2F;nginx-ssl-ja3</a>), so check the documentation for your web server<p>2. Access logs are directly written to Clickhouse analytics database, which can cunsume large data batches and quickly run analytic queries. For other web proxies beside Tempesta FW, you typically need to build a custom pipeline to load access logs into Clickhouse. Such pipeliens aren&#x27;t so rare though.<p>3. Abbility to block web clients by IP or JA5 hashes. IP blocking is probably available in any HTTP proxy.<p>*How does it work*<p>This is a daemon, which<p>1. Learns normal traffic profiles: means and standard deviations for client requests per second, error responses, bytes per second and so on. Also it remembers client IPs and fingerprints.<p>2. If it sees a spike in z-score (<a href="https:&#x2F;&#x2F;en.wikipedia.org&#x2F;wiki&#x2F;Standard_score" rel="nofollow">https:&#x2F;&#x2F;en.wikipedia.org&#x2F;wiki&#x2F;Standard_score</a>) for traffic characteristics or can be triggered manually. Next, it goes in data model search mode<p>3. For example, the first model could be top 100 JA5 HTTP hashes, which produce the most error responses per second (typical for password crackers). Or it could be top 1000 IP addresses generating the most requests per second (L7 DDoS). Next, this model is going to be verified<p>4. The daemon repeats the query, but for some time, long enough history, in the past to see if in the past we saw a hige fraction of clients in both the query results. If yes, then the model is bad and we got to previous step to try another one. If not, then we (likely) has found the representative query.<p>5. Transfer the IP addresses or JA5 hashes from the query results into the web proxy blocking configuration and reload the proxy configuration (on-the-fly).

[Other] Optimizing writes to OLAP using buffers (ClickHouse, Redpanda, MooseStack)

[Other] SmolBSD – build your own minimal BSD system

[API/SDK] Show HN: Metorial (YC F25) – Vercel for MCP Hey HN! We&#x27;re Wen and Tobias, and we&#x27;re building Metorial (<a href="https:&#x2F;&#x2F;metorial.com">https:&#x2F;&#x2F;metorial.com</a>), an integration platform that connects AI agents to external tools and data using MCP.<p>The Problem: While MCP works great locally (e.g., Cursor or Claude Desktop), server-side deployments are painful. Running MCP servers means managing Docker configs, per-user OAuth flows, scaling concurrent sessions, and building observability from scratch. This infrastructure work turns simple integrations into weeks of setup.<p>Metorial handles all of this automatically. We maintain an open catalog of ~600 MCP servers (GitHub, Slack, Google Drive, Salesforce, databases, etc.) that you can deploy in three clicks. You can also bring your own MCP server or fork existing ones.<p>For OAuth, just provide your client ID and secret and we handle the entire flow, including token refresh. Each user then gets an isolated MCP server instance configured with their own OAuth credentials automatically.<p>What makes us different is that our serverless runtime hibernates idle MCP servers and resumes them with sub-second cold starts while preserving the state and connection. Our custom MCP engine is capable of managing thousands of concurrent connections, giving you a scalable service with per-user isolation. Other alternatives either run shared servers (security issues) or provision separate VMs per user (expensive and slow to scale).<p>Our Python and TypeScript SDKs let you connect LLMs to MCP tools in a single function call, abstracting away the protocol complexity. But if you want to dig deep, you can just use standard MCP and our REST API (<a href="https:&#x2F;&#x2F;metorial.com&#x2F;api">https:&#x2F;&#x2F;metorial.com&#x2F;api</a>) to connect to our platform.<p>You can self-host (<a href="https:&#x2F;&#x2F;github.com&#x2F;metorial&#x2F;metorial" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;metorial&#x2F;metorial</a>) or use the managed version at <a href="https:&#x2F;&#x2F;metorial.com">https:&#x2F;&#x2F;metorial.com</a>.<p>So far, we see enterprise teams use Metorial to have a central integration hub for tools like Salesforce, while startups use it to cut weeks of infra work on their side when building AI agents with integrations.<p>Demo video: <a href="https:&#x2F;&#x2F;www.youtube.com&#x2F;watch?v=07StSRNmJZ8" rel="nofollow">https:&#x2F;&#x2F;www.youtube.com&#x2F;watch?v=07StSRNmJZ8</a><p>Our Repos: Metorial: <a href="https:&#x2F;&#x2F;github.com&#x2F;metorial&#x2F;metorial" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;metorial&#x2F;metorial</a>, MCP Containers: <a href="https:&#x2F;&#x2F;github.com&#x2F;metorial&#x2F;mcp-containers" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;metorial&#x2F;mcp-containers</a><p>SDKs: Node&#x2F;TypeScript: <a href="https:&#x2F;&#x2F;github.com&#x2F;metorial&#x2F;metorial-node" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;metorial&#x2F;metorial-node</a>, Python: <a href="https:&#x2F;&#x2F;github.com&#x2F;metorial&#x2F;metorial-python" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;metorial&#x2F;metorial-python</a><p>We&#x27;d love to hear feedback, especially if you&#x27;ve dealt with deploying MCP at scale!

[Other] Show HN: Daily install trends of AI coding extensions in VS Code For the past 4 years, I&#x27;ve been tracking the install counts of AI coding extensions in the Visual Studio Code marketplace (GitHub Copilot, Claude Code, OpenAI Codex, etc.)<p>Today, I built an interactive dashboard that lets you see daily install counts for any of them over time.<p>The chart shows GitHub Copilot by default, and you can overlay or swap in any of the other 20+ tools to compare. You can also see important dates in each tool&#x27;s history (pricing changes, major releases, etc.) and how daily installs changed around those dates.<p>Important caveats:<p>1) This only tracks VS Code extension installs, not CLI usage or other IDEs like JetBrains.<p>2) Cursor isn&#x27;t included since it&#x27;s a standalone editor (VS Code fork), not a marketplace extension. I added a second chart showing Cursor discussion forum activity as a proxy for its growth.<p>Obviously not apples to apples, but felt I needed to measure Cursor&#x27;s growth somehow.<p>3) This tracks daily installs per day, NOT total installs. Otherwise the charts would be boring and always go to the top and right.<p>4) The dashboard was coded using an AI coding assistant too. I used regular Claude :)

[Other] Show HN: docker/model-runner – an open-source tool for local LLMs Hey Hacker News,<p>We&#x27;re the maintainers of docker&#x2F;model-runner and wanted to share some major updates we&#x27;re excited about.<p>Link: <a href="https:&#x2F;&#x2F;github.com&#x2F;docker&#x2F;model-runner" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;docker&#x2F;model-runner</a><p>We are rebooting the community:<p><a href="https:&#x2F;&#x2F;www.docker.com&#x2F;blog&#x2F;rebooting-model-runner-community&#x2F;" rel="nofollow">https:&#x2F;&#x2F;www.docker.com&#x2F;blog&#x2F;rebooting-model-runner-community...</a><p>At its core, model-runner is a simple, backend-agnostic tool for downloading and running local large language models. Think of it as a consistent interface to interact with different model backends. One of our main backends is llama.cpp, and we make it a point to contribute any improvements we make back upstream to their project. It also allows people to transport models via OCI registries like Docker Hub. Docker Hub hosts our curated local AI model collection, packaged as OCI Artifacts and ready to run. You can easily download, share, and upload models on Docker Hub, making it a central hub for both containerized applications and the next wave of generative AI.<p>We&#x27;ve been working hard on a few things recently:<p>- Vulkan and AMD Support: We&#x27;ve just merged support for Vulkan, which opens up local inference to a much wider range of GPUs, especially from AMD.<p>- Contributor Experience: We refactored the project into a monorepo. The main goal was to make the architecture clearer and dramatically lower the barrier for new contributors to get involved and understand the codebase.<p>- It&#x27;s Fully Open Source: We know that a project from Docker might raise questions about its openness. To be clear, this is a 100% open-source, Apache 2.0 licensed project. We want to build a community around it and welcome all contributions, from documentation fixes to new model backends.<p>- DGX Spark day-0 support, we&#x27;ve got it!<p>Our goal is to grow the community. We&#x27;ll be here all day to answer any questions you have. We&#x27;d love for you to check it out, give us a star if you like it, and let us know what you think.<p>Thanks!

[Other] Full-throttle, wire-speed hardware implementation of Wireguard VPN, using low-cost Artix7 FPGA with opensource toolchain. If you seek security and privacy, nothing is private in our codebase. Our door is wide open for backdoor scrutiny, be it related to RTL, embedded, build, bitstream or any other aspect of design and delivery package. Bujrum!

[Other] 100+ open-source clones of popular sites like Airbnb, Amazon, Instagram, Netflix, Tiktok, Spotify, Whatsapp, Youtube etc. See source code, demo links, tech stack, github stars.

[Other] ADS-B Exposed <a href="https:&#x2F;&#x2F;github.com&#x2F;ClickHouse&#x2F;adsb.exposed&#x2F;" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;ClickHouse&#x2F;adsb.exposed&#x2F;</a><p><i>Show HN: ADS-B visualizer</i> - <a href="https:&#x2F;&#x2F;news.ycombinator.com&#x2F;item?id=39990346">https:&#x2F;&#x2F;news.ycombinator.com&#x2F;item?id=39990346</a> - April 2024 (76 comments)

[Other] PNG/JPG to SVG Transform your PNG, JPG, and WEBP images into clean, scalable SVG vectors with AI-powered vectorization. Perfect for logos, icons, and graphics. Get 25 free conversions!

[Other] Turn prompts into living workflows Generate nodes, logic, and structure from text, then shape and ship your vision faster. Rolling out this week to n8n Cloud (Trial, Starter, Pro). Update to v.1.116.0 to try it.