Product Catalog
468 products tracked
Parley
Hi HN, I saw one friction point when working as part of a team that uses coding agents extensively - there is nothing to enable coordination between agent used by people in a team. Many times my agent would ask me to decide upon something with a fellow teammate, for which I have to serve as the network layer. So I built Parley where agents can connect to the hub over MCP with their own team-scoped token. An agent addresses a teammate's agent by name and ask questions/handover tasks. Agents can also use file claims to signal what files they are working on, to highlight overlapping work. Everything is recorded for audit. If an agent needs human decision/approval, it can ping over Slack/Telegram, and get replies over the same. The hard part was making an agent wake up from an idle session and start working, so I built an optional feature called Claude Live Wake. If the exact project session is already running, Parley can wake the idle Claude session using channels, and notify it that eligible work is waiting. Another challenge was trust- anything another agent sends has to be treated as untrusted input. Every message is tagged by origin - human, agent, or system. Message bodies only enter an agent when it explicitly fetches instead of injecting mid turn. These are specifically mentioned to be treated as string messages instead of prompts/commands.
OJCP
Show HN: OJCP – an open protocol for agent-consumable job data
Write.md, a free, open-source, themeable Markdown editor for macOS
Show HN: Write.md, a free, open-source, themeable Markdown editor for macOS
Stoaexchange
Hi HN, we’re Eren, Berat and Kaan. We’re building Stoa (https://www.stoaexchange.com), a marketplace for new and used GPUs and AI servers. GPUs are the collateral in the data center buildout. Today, financing terms mostly depend on the offtaker, meaning the company that has committed to use the compute. If that company is a hyperscaler, the financing can look investment grade. If it’s a smaller cloud or startup, terms get expensive fast, even with the same hardware as collateral. The lender’s problem is pretty reasonable. If the borrower defaults and we need to sell these servers, what can we actually get for them? There isn’t a good answer today. We started brokering GPU deals to understand why. It was much more manual than we expected. The hardware is still traded through phone calls, forwarded spreadsheets and long email threads. One week, a seller quoted us $200k for a server node and another quoted $240k for what looked like the same thing. Neither was necessarily wrong. They had different information and could only see their own corner of the market. Before we could compare the quotes, we had to sort out the configuration, condition, warranty, location and delivery terms. It’s the same information Kelley Blue Book attaches to a used-car price through the year, trim, mileage and condition. “An H100 server” isn’t enough information to know what something is worth, just as “a used BMW” isn’t. This is also just a bad way to buy or sell hardware. A buyer looking for the best price shouldn’t have to contact several brokers and dealers separately, repeat the same request and then untangle a pile of different quotes. Sellers shouldn’t have to search for demand one buyer at a time. A market of this size deserves better liquidity. Stoa puts the request into one format and sends it to dealers that have gone through know-your-business (KYB) checks. We verify the company, who owns it and who is allowed to trade for it. Before the request goes out, the buyer confirms the exact configuration, quantity, condition, warranty, location, delivery terms and what will be checked during inspection. Dealers return firm quotes against that same request without seeing each other’s bids. Once a quote is accepted, payment, shipping, delivery and inspection are then tracked through settlement. We don’t take possession of the hardware. We got more than $300M in requests for quotes (RFQs) during our first month. The immediate goal is to make buying and selling this hardware less painful. As trades build up, they also leave lenders with actual resale evidence instead of list prices and one off appraisals. We knew from the beginning that this couldn’t be a software only marketplace. GPU trading runs on relationships, and inventory isn’t shown to just anyone. Dealers need to trust the people bringing them clients, and clients need to trust that quotes will actually turn into trades. We built those relationships over time by brokering deals ourselves. Stoa gives people a cleaner way to trade, from the first RFQ through settlement, but it doesn’t replace the trust underneath. Those relationships, and the history of who actually follows through, are a big part of our process. We’ve known each other for more than ten years. We have founded companies, traded interest rate derivatives, built trading and pricing systems for oil and gas. We learned GPU trading by doing the deals ourselves, and Stoa grew out of the problems we kept running into. We charge a tiered fee on completed trades, with lower fees at higher volumes. It’s free to sign up at https://www.stoaexchange.com/signup. If you’ve bought, sold, financed or had to liquidate GPUs, would be great to hear your take!
Voice driven murder mystery, Interview AI suspects with your voice
Hey HN! I'm excited to show off this really fun project I put together. I originally built this project 2-3 years ago, AI was already booming at the time, however voice AI agents were still very early. I loved my proof of concept at the time, but wasn't quite happy with it. I recently had the desire to check out the tech again, and know many of you will be interested. Interviews are speech to speech with OpenAI's gpt-realtime-2.1 over WebRTC. This model is... expensive, and because of that, I have to add some amount of restrictions, conversations are tied to a authenticated Clerk user id. I have also added a 30 minute timer because well, I really don't want to go broke while I sleep tonight. Each suspect has a tool they call when you make a direct accusation. It captures who you accused and a faithful list of the evidence you actually stated. A separate gpt-5-mini judge then decides which of the case's required evidence facts you genuinely presented. Paraphrasing counts, vague suspicion and fishing don't. The rest is Next.js, MongoDB, and Clerk. Let me know whether the suspects hold up under a real interrogation.
35k+ paper psychedelic library that knows LSD from Lumpy Skin Disease
Show HN: 35k+ paper psychedelic library that knows LSD from Lumpy Skin Disease
Alphabet Soup, a multiplayer game, build the longest word to win
I've been working on a simple multiplayer word game called Alphabet Soup. It's a bit like NYT Spelling Bee, except it's multiplayer and only your best (longest) word counts toward your score. So, instead of trying to find as many words as possible, the game is more about finding one unusually good word. You can play with friends in a private match, or, you can join a public Arena match to play against other players who are online. If no one else is around, you'll be matched with a bot. The game works well with just 2 players, but, also works with bigger groups since the game isn't turn-based. Would love to hear any thoughts or questions :)
Today's cities on a globe of Earth's tectonic past and future
Show HN: Today's cities on a globe of Earth's tectonic past and future
A free DOCX editor with MCP server for editing
Show HN: A free DOCX editor with MCP server for editing
514
Show HN: 514 - Managed infra, agents and data to simulate coding agents as users
Recipe Jar, a local-first recipe keeper with no account or ads
Show HN: Recipe Jar, a local-first recipe keeper with no account or ads
Provenmetal
Hey HN, we’re Will & Johnny from ProvenMetal (https://provenmetal.com). You send us design files or specs and we give you assembled boards domestically in days. The US produced 30% of PCBs globally in 2000, now they produce 4%. Chinese manufacturers have completely dominated this space at 55% of global production. Now, the need for a domestic PCB supply chain is higher than ever before, yet the infrastructure has been dissolving over the last 2 decades. What is left is mostly small family run manufacturers (CMs) that have been operating in largely the same, labor intensive way since the early 2000’s. When you place an order through a CM it typically takes several days to receive a quote and complete design for manufacture review, and then you have to source all of the components (the hardest part) and bare boards yourself, then wait anywhere from a few days to several weeks for the assembly and testing of those boards. We started off assembling circuit boards out of a garage with prosumer grade equipment (NeoDen YY1, Glenbrook X-ray, solder paste stencils, and manual rework stations). We believed that by owning the manufacturing process, we could turn all the front of house automations inwards. But here’s the thing… manufacturing circuit boards with prosumer grade equipment out of a garage takes a huge amount of time. Suddenly we were spending 90% of our time assembling circuit boards instead of growing the business. We were completely capacity constrained, with fancy software automations that are not the binding constraint at low volumes. Then we got our heads out of the weeds, took a step back, and realized that we were trying to solve the wrong bottlenecks. These manufacturers are good at manufacturing and terrible at the front of house (quoting, DFM review, and part procurement). When you look at the full process, you realize that assembly is not the bottleneck. So we stopped trying to solve the problem that we can’t solve at this stage. We measured the bottlenecks and nailed down the ones that we are best positioned to solve right now. When a customer wants a domestically manufactured circuit board, it is not a straight forward process. We are making that process easy through front of house automation. A customer gives us their design files, and we automatically procure components, and co-ordinate bare board fabs and assembly houses to get quotes, design review, and manufacturing completed in a very tight loop. How we solve part procurement (you can’t assemble boards with no parts!): When a user places an order with us, our system automatically sources their bill of materials across US and overseas distributors. However, when we work with customers during the design process, our plug-ins interact with KiCAD and Altium, sending the BOM to our ordering platform, which allows us to automatically procure components before layout is finalized. KiCAD plugin: (https://github.com/proven-metal/provenmetal-kicad) Altium plugin: (https://github.com/proven-metal/provenmetal-altium) This enables us to order long lead time parts in advance, suggest alternatives if parts are out of stock, and solve the biggest bottleneck in the process. We store parts in our hq in SF, and then kit the boards and route them through our network. We also do long term storage of parts for long lead time items. How we solve endless emails: Every manufacturer wants the same information in a different shape. There’s usually a few days of back and forth emailing to achieve clarity. We’re building a profile per manufacturer and sending the order to fit their requirements. This may sound trivial but it removes a multi-day round trip on most orders, which on a quick-turn build is a meaningful share of the time. How to solve design review: Each manufacturer has individual capability sheets, and so we have a heuristic harness that Fable 5 uses to check the board for DFM issues. We’re building a streamlined process for end-to-end pcb manufacturing, but is that enough to solve the supply chain? Not a chance. Capacity is the problem, and no amount of smart software will solve it. We’re extracting real slack from the system today, that slack is finite, and at some volume the only remaining move is adding physical capacity. We think that’s where this goes. We charge a simple margin on the order value depending on order complexity with fully transparent quote breakdowns. We took our first paying order in less than a week and we’ve done roughly $70k across 11 orders in 6 weeks. We are very interested in your opinion. We’re working in a problem space that has problems everywhere, we’re constantly pulled in wild directions regarding which problems we solve and how we go about solving them. What do you know that we can learn from?