Show HN: Mark 1.0, a notation that unifies JSON, HTML, JSX, XML, YAML, and more

Show HN: MCP Jetpack – The easiest way to get started with MCP in Cursor

Show HN: MCP Jetpack – The easiest way to get started with MCP in Cursor My friends and I built MCP Jetpack which makes it really easy to start using MCP. It’s an MCP server that automatically finds and executes the right tools needed to accomplish your task without having to manage MCP servers for each service (GitHub, Linear, Atlassian, Notion etc.). Once you add it to Cursor (or any other AI app with MCP support), Cursor instantly gets access to a growing library of remote MCP servers without any extra setup. For services that require authentication, you will be asked to login the first time you ask your AI to interact with that service.Two problems we are trying to solve:Friction - Normally if you want to give Cursor access to GitHub, you have to install the right MCP server and login before you can use GitHub with Cursor’s chat. With MCP Jetpack, you can ask Cursor to list your GitHub issues, and it will automatically execute the right tool behind the scenes to accomplish your task. For services that require authentication, you will be asked to login the first time you interact with the service. However, it all happens within the Cursor chat so you never have to context switch and fiddle with Cursor’s settings.Tool Limits - Cursor warns you if you have more than 50 MCP tools installed as it says having more will degrade performance. However, just installing the GitHub MCP server itself adds 74 MCP tools. With MCP Jetpack, you get access to GitHub, Atlassian and 15 other services with just two tools: “FindTool” and “ExecTool”.Here are the 17 services we support today: GitHub, Atlassian, Canva, Linear, Notion, Intercom, Monday.com, Neon, PayPal, Hugging Face, Sentry, Square, Webflow, Wix, Cloudflare Docs, Cloudflare AI Gateway, Cloudflare Workers Bindings.We’ll continue to add more services as companies launch remote MCP servers. If yours isn’t listed and you’d like it to be added, please email us at team@mcpjetpack.com.MCP Jetpack is in alpha so please let us know if you run into any problems or have any feedback - thanks!

Show HN: GitGuard - Painless GitHub PR Automations

Show HN: GitGuard - Painless GitHub PR Automations Hey HN,Every team I've been on has cobbled together some sort of combination of GitHub branch protections and custom scripts to make sure that PRs conform to organization policies and best practices.Things like:- When {X} file is changed, require review from team {Y}- When a new db migration is added, ensure that a special set of tests pass- Require multiple approvals when the PR is very large- Add a special label to PRs that include breaking changes- Allow emergencies / hotfixes to break glass and bypass all of the aboveMost teams tend to start out with a little script running in GitHub actions to enforce all of these policies but it tends to get out of hand and become hard to maintain. PRs that should require scrutiny slip through the cracks, and others that should be allowed through are unnecessarily blocked.That's why I made GitGuard (<a href="https://gitguard.dev/" rel="nofollow">https://gitguard.dev/</a>)GitGuard lets you write and maintain these policies in a custom DSL so simple it looks like pseudocode. The policies are checked on every single PR nearly instantly (no need to wait for a GitHub actions runner) and the results are reported in plain english.Right now policies can make simple assertions about PR metadata and take some stateful actions (adding labels, requesting review) but I'd love to hear more from HN about how GitGuard could be even more useful.

Show HN: HN v0.2.1 – Native macOS app for reading HN

Show HN: HN v0.2.1 – Native macOS app for reading HN Hey HN folks,Last week I released the first public version of 120 HN — a fully native Hacker News client for macOS. This week, I'm excited to share version 0.2.1 with some essential updates:The app now remembers window size, position, and sidebar state between sessionsImproved AI summaries: more concise, relevant with link back to the comments, easier to read with short paragraph form.Minor tweaks to navigation and layout for a smoother experienceSneak peek: local LLM support is coming in the next release.As always, the app is free to use. Any suggestions or comments would be appreciated.Thanks for checking it out.

Show HN: Timep – a next-gen profiler and flamegraph-generator for bash code

Show HN: Timep – a next-gen profiler and flamegraph-generator for bash code timep is a TIME Profiler for bash code that will give you an accurate per-command execution time breakdown of any bash script or function.Unlike other profilers, timep also recovers and hierarchally records metadata on subshell and function nesting, allowing it to recreate the full call-stack tree for the bash code being profiled. If you call timep with the `--flame` flag, it will automatically generate a flamegraph .svg image where each block represents the wall-clock time spent on a particular command (top level) or its parent subshells/functions (all the other levels).Using timep is simple - just source the timep.bash file then add timep before whatever you want to profile. You do not need to change in the code being profiled - timep handles everything for you. Example usage:<pre><code> . ./timep.bash timep someFunc timep -flame someScript <inputFile </code></pre> timep will generate 2 profiles for you: one showing each individual command (with full subshell/function nesting chains), and one that combines repeated loops commands into a count + total runtime line with minimal "extra" metadata.See the github README for more info on the available flags and output profile specifics.timep works by cramming all the timing instrumentation logic into a DEBUG trap that roughly does the following:1. record end timestamp for previous command 2. compare current state to state saved in variables last DEBUG trap to determine what sort of command is happening. e.g., if BASH_SUBSHELL increased then we know we just entered a subshell or background fork. 3. once we know what type of command is happening, generate a log line for the previous command (now that we have its end time 4. save current state in various variables (for use next debug trap) 5. record start time for the next commandthen after the profiled code is done running, timep post-processes the logs to produce the final profile

Show HN: c0admin – A terminal-based AI assistant for Linux sysadmins

Show HN: c0admin – A terminal-based AI assistant for Linux sysadmins I made a small CLI tool called `c0admin`. Runs locally using your own Gemini API key. No signup, no server, no tracking.You just run `c0admin` in your terminal, and it gives you suggestions interactively.

Show HN: Ncrypt – Query encrypted files privately with FHE

Show HN: Ncrypt – Query encrypted files privately with FHE Hey HN,We're building ncrypt, an open-source encrypted file manager that allows you to store, manage, and privately query your files using fully homomorphic encryption (FHE). This project originally started as a simple SFTP-like CLI for my personal S3 buckets which I used to send and retrieve encrypted files and have more granular control over key rotation.As the number of files that I was storing grew, file discovery started to become a problem, and I found myself frequently having to download and decrypt files to inspect their contents. Rather than leaving them unencrypted in S3 and therefore easier to search, I started looking into the concept of searching over encrypted data using fully homomorphic encryption. This led me to Zama's concrete-python library (<a href="https://github.com/zama-ai/concrete">https://github.com/zama-ai/concrete</a>), which provides a simple Python interface for performing FHE operations.FHE is notoriously slow, so rather than trying to search over entire files I focused on a more tractable problem, indexing and searching over file metadata (summaries, keywords, embeddings, etc) which was small enough to make search practical. While still not fast compared to traditional file management tools, ncrypts search performance is decent if you keep directory sizes relatively small (under 25 files), and most of the heavy lifting happens during metadata extraction, not at search time.The two types of encrypted queries we currently support are keyword search and cosine similarity search over vector embeddings, which are generated using user-specified huggingface models. Ncrypt currently supports metadata extraction for text, image, and audio files. Check out our code and give it a try at <a href="https://github.com/ncryptai/ncrypt">https://github.com/ncryptai/ncrypt</a>.We love feedback!

Show HN: Clai - Vendor agnostic Claude Code/Gemini CLI written in Go

Show HN: Reactylon – Open-source framework for building 3D/XR apps with React