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Show HN: A large format XY scanning hyperspectral camera

Show HN: A large format XY scanning hyperspectral camera

Show HN: A large format XY scanning hyperspectral camera

Show HN: We packaged an MCP server inside Chromium

Hey HN, we just shipped a browser with an inbuilt MCP server!<p>We're a YC startup (S24) building BrowserOS — an open‑source Chromium fork. We'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/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'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'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 "test the auth flow with my Google Sign‑In." Here's a video of claude-code using browserOS to improve the css styling with back-and-forth checking: <a href="https://youtu.be/vcSxzIIkg_0" rel="nofollow">https://youtu.be/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's a video of claude-code opening top 5 hacker news posts and summarizing: <a href="https://youtu.be/rPFx_Btajj0" rel="nofollow">https://youtu.be/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's a rough architecture diagram: <a href="https://dub.sh/browseros-mcp-diag" rel="nofollow">https://dub.sh/browseros-mcp-diag</a><p>-- How to install and use it: We put together a short guide here: <a href="https://git.new/browseros-mcp" rel="nofollow">https://git.new/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'll be hanging around all day, would love to get your feedback and answer any questions!

Show HN: We packaged an MCP server inside Chromium

Hey HN, we just shipped a browser with an inbuilt MCP server!<p>We're a YC startup (S24) building BrowserOS — an open‑source Chromium fork. We'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/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'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'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 "test the auth flow with my Google Sign‑In." Here's a video of claude-code using browserOS to improve the css styling with back-and-forth checking: <a href="https://youtu.be/vcSxzIIkg_0" rel="nofollow">https://youtu.be/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's a video of claude-code opening top 5 hacker news posts and summarizing: <a href="https://youtu.be/rPFx_Btajj0" rel="nofollow">https://youtu.be/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's a rough architecture diagram: <a href="https://dub.sh/browseros-mcp-diag" rel="nofollow">https://dub.sh/browseros-mcp-diag</a><p>-- How to install and use it: We put together a short guide here: <a href="https://git.new/browseros-mcp" rel="nofollow">https://git.new/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'll be hanging around all day, would love to get your feedback and answer any questions!

Show HN: We packaged an MCP server inside Chromium

Hey HN, we just shipped a browser with an inbuilt MCP server!<p>We're a YC startup (S24) building BrowserOS — an open‑source Chromium fork. We'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/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'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'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 "test the auth flow with my Google Sign‑In." Here's a video of claude-code using browserOS to improve the css styling with back-and-forth checking: <a href="https://youtu.be/vcSxzIIkg_0" rel="nofollow">https://youtu.be/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's a video of claude-code opening top 5 hacker news posts and summarizing: <a href="https://youtu.be/rPFx_Btajj0" rel="nofollow">https://youtu.be/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's a rough architecture diagram: <a href="https://dub.sh/browseros-mcp-diag" rel="nofollow">https://dub.sh/browseros-mcp-diag</a><p>-- How to install and use it: We put together a short guide here: <a href="https://git.new/browseros-mcp" rel="nofollow">https://git.new/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'll be hanging around all day, would love to get your feedback and answer any questions!

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/WebAssembly to run Google's Jpegli inside a Web Worker. Now there's a small UI and it handles a bunch of formats.<p>Just about the only thing it can't decode is JXL - but there'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's the fun in that?<p>Would love feedback on edge cases and defaults.<p>Tested on Firefox, Chrome, and Safari.<p>Cheers!

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/WebAssembly to run Google's Jpegli inside a Web Worker. Now there's a small UI and it handles a bunch of formats.<p>Just about the only thing it can't decode is JXL - but there'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's the fun in that?<p>Would love feedback on edge cases and defaults.<p>Tested on Firefox, Chrome, and Safari.<p>Cheers!

Show HN: How Useless Are You? A brutally honest skills check

We built this to answer "am I a fit for this role?"<p>after noticing how hard it is to get honest feedback when applying to a YC startup or something else entirely.<p>It's a custom 5-minute challenge that roasts you after.<p>Added a leaderboard for those who want to see how they stack up.<p>Roast us below.

Show HN: We priced basic needs in work hours (global ranking and CSVs)

Show HN: Inkeep (YC W23) – Agent Builder to create agents in code or visually

Hi HN! I'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://go.inkeep.com/video">https://go.inkeep.com/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'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://go.inkeep.com/quickstart">https://go.inkeep.com/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/Claude/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/Docker with a fair-code license and there'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/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://docs.inkeep.com">https://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?

Show HN: Inkeep (YC W23) – Agent Builder to create agents in code or visually

Hi HN! I'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://go.inkeep.com/video">https://go.inkeep.com/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'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://go.inkeep.com/quickstart">https://go.inkeep.com/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/Claude/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/Docker with a fair-code license and there'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/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://docs.inkeep.com">https://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?

Show HN: Inkeep (YC W23) – Agent Builder to create agents in code or visually

Hi HN! I'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://go.inkeep.com/video">https://go.inkeep.com/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'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://go.inkeep.com/quickstart">https://go.inkeep.com/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/Claude/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/Docker with a fair-code license and there'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/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://docs.inkeep.com">https://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?

Show HN: Inkeep (YC W23) – Agent Builder to create agents in code or visually

Hi HN! I'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://go.inkeep.com/video">https://go.inkeep.com/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'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://go.inkeep.com/quickstart">https://go.inkeep.com/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/Claude/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/Docker with a fair-code license and there'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/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://docs.inkeep.com">https://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?

Show HN: Wispbit - Linter for AI coding agents

Hey HN! Ilya and Nikita here. We're building wispbit (<a href="https://wispbit.com" rel="nofollow">https://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'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'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'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'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've opened up signups for free to HN folks at <a href="https://wispbit.com" rel="nofollow">https://wispbit.com</a>. We're also around to chat and answer questions!

Show HN: Trott – search,sort,extract social media videos(ig,yt,tiktok)

I built Trott out of frustration with my own “Saved” folders on Instagram and YouTube. I’d save reels and shorts—workout tips, recipes, travel spots—thinking I’d find them again later. But, like most people, I ended up with a black hole of unsorted videos: no search, no filters, and if I ever did find the right video again, I’d have to dig through the whole thing just to get that one detail I needed.<p>When I tried looking for solutions, I found only genre-specific apps or tools that demanded manual uploads or new workflows. None felt like they understood how real users behave or save content. So I decided to build Trott.<p>What makes Trott different?<p>You can share any Instagram Reel or YouTube Short (TikTok support launches next week) to Trott, straight from your phone’s native share menu—no manual uploads.<p>Trott uses AI to extract relevant info automatically (ingredients, places, products, etc.) and sorts everything for you.<p>It’s fully searchable with natural language. Just type something like “that Kyoto café from Instagram” and Trott finds it.<p>For travel videos, it can even produce Google Maps routes from extracted locations.<p>App Store: <a href="https://apps.apple.com/in/app/trott/id6751728352">https://apps.apple.com/in/app/trott/id6751728352</a> Play Store: <a href="https://play.google.com/store/apps/details?id=in.hattimatimlabs.trott&hl=en_IN">https://play.google.com/store/apps/details?id=in.hattimatiml...</a><p>I’d love to hear how you organize your own saved content—or if you’ve just given up and let it pile up like I used to. Open to all questions, feedback, and bug reports. Happy to discuss the tech details behind Trott if you’re interested!

Show HN: Trott – search,sort,extract social media videos(ig,yt,tiktok)

I built Trott out of frustration with my own “Saved” folders on Instagram and YouTube. I’d save reels and shorts—workout tips, recipes, travel spots—thinking I’d find them again later. But, like most people, I ended up with a black hole of unsorted videos: no search, no filters, and if I ever did find the right video again, I’d have to dig through the whole thing just to get that one detail I needed.<p>When I tried looking for solutions, I found only genre-specific apps or tools that demanded manual uploads or new workflows. None felt like they understood how real users behave or save content. So I decided to build Trott.<p>What makes Trott different?<p>You can share any Instagram Reel or YouTube Short (TikTok support launches next week) to Trott, straight from your phone’s native share menu—no manual uploads.<p>Trott uses AI to extract relevant info automatically (ingredients, places, products, etc.) and sorts everything for you.<p>It’s fully searchable with natural language. Just type something like “that Kyoto café from Instagram” and Trott finds it.<p>For travel videos, it can even produce Google Maps routes from extracted locations.<p>App Store: <a href="https://apps.apple.com/in/app/trott/id6751728352">https://apps.apple.com/in/app/trott/id6751728352</a> Play Store: <a href="https://play.google.com/store/apps/details?id=in.hattimatimlabs.trott&hl=en_IN">https://play.google.com/store/apps/details?id=in.hattimatiml...</a><p>I’d love to hear how you organize your own saved content—or if you’ve just given up and let it pile up like I used to. Open to all questions, feedback, and bug reports. Happy to discuss the tech details behind Trott if you’re interested!

Show HN: Trott – search,sort,extract social media videos(ig,yt,tiktok)

I built Trott out of frustration with my own “Saved” folders on Instagram and YouTube. I’d save reels and shorts—workout tips, recipes, travel spots—thinking I’d find them again later. But, like most people, I ended up with a black hole of unsorted videos: no search, no filters, and if I ever did find the right video again, I’d have to dig through the whole thing just to get that one detail I needed.<p>When I tried looking for solutions, I found only genre-specific apps or tools that demanded manual uploads or new workflows. None felt like they understood how real users behave or save content. So I decided to build Trott.<p>What makes Trott different?<p>You can share any Instagram Reel or YouTube Short (TikTok support launches next week) to Trott, straight from your phone’s native share menu—no manual uploads.<p>Trott uses AI to extract relevant info automatically (ingredients, places, products, etc.) and sorts everything for you.<p>It’s fully searchable with natural language. Just type something like “that Kyoto café from Instagram” and Trott finds it.<p>For travel videos, it can even produce Google Maps routes from extracted locations.<p>App Store: <a href="https://apps.apple.com/in/app/trott/id6751728352">https://apps.apple.com/in/app/trott/id6751728352</a> Play Store: <a href="https://play.google.com/store/apps/details?id=in.hattimatimlabs.trott&hl=en_IN">https://play.google.com/store/apps/details?id=in.hattimatiml...</a><p>I’d love to hear how you organize your own saved content—or if you’ve just given up and let it pile up like I used to. Open to all questions, feedback, and bug reports. Happy to discuss the tech details behind Trott if you’re interested!

Show HN: Greenonion.ai – AI-Powered Design Assistant

Hi HN<p>I’m excited to launch GreenOnion.ai — a platform that helps anyone create beautiful, editable design layouts instantly using AI.<p>A lot of “AI design” tools today generate images. GreenOnion doesn’t. You bring your own images — our AI handles the layout, composition, colors, and typography to turn them into cohesive, ready-to-use designs.<p>Every element is structured and editable — text, spacing, colors, hierarchy — not just pixels on a canvas. It’s real design generation, not image generation.<p>What it does:<p>Describe what you want (e.g. “modern poster for a coffee brand”)<p>AI builds a layout around your content and image<p>Edit and refine everything in the browser<p>Export for web, print, or campaigns<p>Why we built it: Design shouldn’t be locked behind complex tools or templates. If you can describe an idea, you should be able to see it take form — and still have full control to adjust it.<p>It’s live and working today: <a href="https://greenonion.ai" rel="nofollow">https://greenonion.ai</a><p>I’d love your feedback — whether it’s about the product, the concept, or where you think AI-driven design should go next.<p>Thanks for reading, — Yanjie Founder, GreenOnion.ai

Show HN: Firm, a text-based work management system