Show HN: Dependicus, a dashboard for your monorepo's dependencies https://ift.tt/AOLem6p

Show HN: Dependicus, a dashboard for your monorepo's dependencies Late last year, I was digging into some dependency-related tech debt, and struggling with how long it takes to run pnpm's introspection commands like 'pnpm why' in a medium-size monorepo. So I started working on a simple static site generator that would let me view the output of these expensive commands all at once, to make problems clearly visible instead of requiring deep exploration one at a time. Once I had that working, I realized I had enough data to add ticket tracking. It uses the data it gathers from the package manager to keep Linear or GitHub issues updated. And by auto-assigning those issues to coding agents, I get a Dependabot-but-better experience: agents keep up with API updates in addition to just bumping versions, and group related updates automatically. It's still early days, but it's working really well for us and I think people will find value in it, so I'm sharing here! https://descriptinc.github.io/dependicus/ April 16, 2026 at 12:02AM

Show HN: MCP server gives your agent a budget (save tokens, get smarter results) https://ift.tt/zD7ofRZ

Show HN: MCP server gives your agent a budget (save tokens, get smarter results) As a consultant I foot my own Cursor bills, and last month was $1,263. Opus is too good not to use, but there's no way to cap spending per session. After blowing through my Ultra limit, I realized how token-hungry Cursor + Opus really is. It spins up sub-agents, balloons the context window, and suddenly, a task I expected to cost $2 comes back at $8. My bill kept going up, but was I really going to switch to a worse model? No. So I built l6e: an MCP server that gives your agent the ability to budget. It works with Cursor, Claude Code, Windsurf, Openclaw, and every MCP-compatible application. Saving money was why I built it, but what surprised me was that the process of budgeting changed the agent's behavior. An agent that understands the limitations of the resources doesn't try to speculatively increase the context window with extra files. It doesn't try to reach every possible API. The agent plans ahead, sticks to it, and ends work when it should. It works, and we've been dogfooding it hard. After v1 shipped, the rest of l6e was all built with it. We launched the entire docs site using frontier models for $0.99. The kicker was every time l6e broke in development, I could feel the pain. The agent got sloppy, burned through context, and output quality dropped right along with it. Install: pip install l6e-mcp Docs: https://docs.l6e.ai GitHub: https://ift.tt/Ze3Aaxg Website: https://l6e.ai Happy to answer questions about the system design, calibration models, or why I can't go back to coding without it. https://l6e.ai April 15, 2026 at 10:38PM

Show HN: A Claude Code–driven tutor for learning algorithms in Go https://ift.tt/wTClJbg

Show HN: A Claude Code–driven tutor for learning algorithms in Go https://ift.tt/9o8brjG April 15, 2026 at 12:41AM

Show HN: LangAlpha – what if Claude Code was built for Wall Street? https://ift.tt/nqNr1Zw

Show HN: LangAlpha – what if Claude Code was built for Wall Street? Some technical context on what we ran into building this. MCP tools don't really work for financial data at scale. One tool call for five years of daily prices dumps tens of thousands of tokens into the context window. And data vendors pack dozens of tools into a single MCP server, schemas alone can eat 50k+ tokens before the agent does anything useful. So we auto-generate typed Python modules from the MCP schemas at workspace init and upload them into the sandbox. The agent just imports them like a normal library. Only a one-line summary per server stays in the prompt. We have around 80 tools across our servers and the prompt cost is the same whether a server has 3 tools or 30. This part isn't finance-specific, it works with any MCP server. The other big thing was making research actually persist across sessions. Most agents treat a single deliverable (a PDF, a spreadsheet) as the end goal. In investing that's day one. You update the model when earnings drop, re-run comps when a competitor reports, keep layering new analysis on old. But try doing that across agent sessions, files don't carry over, you re-paste context every time. So we built everything around workspaces. Each one maps to a persistent sandbox, one per research goal. The agent maintains its own memory file with findings and a file index that gets re-read before every LLM call. Come back a week later, start a new thread, it picks up where it left off. We also wanted the agent to have real domain context the way Claude Code has codebase context. Portfolio, watchlist, risk tolerance, financial data sources, all injected into every call. Existing AI investing platforms have some of that but nothing close to what a proper agent harness can do. We wanted both and couldn't find it, so we built it and open-sourced the whole thing. https://ift.tt/gE3LiU7 April 14, 2026 at 09:48PM

Show HN: pg_grpc – Call gRPC services directly from PostgreSQL https://ift.tt/qvzCXYM

Show HN: pg_grpc – Call gRPC services directly from PostgreSQL https://ift.tt/XMWEcKJ April 14, 2026 at 12:50AM

Show HN: 15 yrs of Django in prod: patterns I keep using (agent skills) https://ift.tt/f0FaTcP

Show HN: 15 yrs of Django in prod: patterns I keep using (agent skills) https://ift.tt/umWRb9H April 13, 2026 at 10:16PM

Show HN: Rekal – Long-term memory for LLMs in a single SQLite file https://ift.tt/kNahWFX

Show HN: Rekal – Long-term memory for LLMs in a single SQLite file I got tired of repeating myself to my LLM every session. rekal is an MCP server that stores memories in SQLite and retrieves them with hybrid search (BM25 + vectors + recency decay). One file, local embeddings, no API keys. https://ift.tt/TGSsyj8 April 13, 2026 at 04:25AM

Show HN: Claudraband – Claude Code for the Power User https://ift.tt/qvPm9yA

Show HN: T4 – a versioned datastore with branching and time-travel (S3-backed) https://ift.tt/xDNasBV

Show HN: T4 – a versioned datastore with branching and time-travel (S3-backed) Hi HN, I built t4, a datastore that stores its WAL and snapshots in S3. Instead of traditional storage, it writes append-only segments to object storage and reconstructs state from checkpoints + WAL. A side effect of this model is that the database becomes naturally versioned: - you can restore any past state - branch from any point (with copy-on-write) - replay history I started this as an experiment to replace etcd in Kubernetes, but it’s evolving into a general-purpose versioned state store. Curious what people think about: - using object storage as the primary persistence layer - whether branching/time-travel is actually useful in practice https://ift.tt/S3mcvgj April 13, 2026 at 12:22AM

Show HN: A living Vancouver. Connor is walking dogs at the SPCA this morning https://ift.tt/csFKEgx

Show HN: A living Vancouver. Connor is walking dogs at the SPCA this morning I've spent most of my career in marketing, which for the last few years has meant building consumer personas for campaigns. I wanted to see if I could make these real, living in real neighborhoods, had real weather, real budgets, real Saturday lunches. I always wanted to build a world, not a segment. This is that. 140 people so far, split across Vancouver (100), San Francisco (20), and Tokyo (20). Each one is about 1,000 lines of profile — family, finances, daily schedule, health, worldview, media diet, the channels you'd actually reach them through and the ones that will explicitly never work on them. Demographics are census-grounded income, age, ethnicity, household composition follow normal distributions against StatsCan, ACS, and Japanese e-Stat data, so the panel is roughly representative of the city instead of representative of whatever's overrepresented in an LLM's training corpus. The specific details come from real stories. They live in real local time on a live map. Right now it's Saturday 11:32 AM in Vancouver. Connor Hughes, a 31-year-old software developer at Clio in Gastown, is on his SPCA volunteer shift, he walks shelter dogs at the Boundary Road location every other Saturday morning. Hassan Khoury is in the morning lunch rush with Tony at his Lebanese café — it's his busiest day of the week. Ahmad Noori is pulling Saturday overtime on a construction site. Jordan Whitehorse is on mid-shift at East Cafe on Hastings. Every day is unique, no two days repeat. A 3 AM job fetches live data: weather from Open-Meteo, grocery CPI from StatsCan food vectors, Metro Vancouver transit delays from Google Routes API against specific corridors, Vancouver gas prices, sunrise and sunset. Each persona has a modifier file that reacts to all of it. When Vancouver gas hits $1.85/L, Jaspreet the long-haul trucker's Coquihalla run to Calgary stops feeling worth it, his margins are thin, his mood takes a hit. When food CPI spikes, Gurinder at the Amazon warehouse stops buying the $9 Subway and brings roti from home. A health flare rolls probabilistically each morning which maybe nothing, maybe Tanya's six month old had a rough night, maybe Frank's back is acting up. The days stack up and get remembered. Every persona has a journal, today's entry in a markdown file, a week of them compressed into a "dream" of ~30 lines that keeps the shape without the texture, a month compressed into ~15 lines. It's their journal. I'm not writing it; the simulation is. Click any persona to open their detail, or hit "Talk to [name]" to have a conversation and they run on Claude Haiku with their full profile and recent diary entries as context. Not a product, not a startup, just a thing I've been quietly working on. They feel, in a way I didn't expect, like my fully grown kids. Happy to answer questions. https://brasilia-phi.vercel.app April 12, 2026 at 01:42AM

Show HN: We scanned uscis.gov for third-party trackers. The results are jarring https://ift.tt/FXehWsU

Show HN: We scanned uscis.gov for third-party trackers. The results are jarring https://ift.tt/8vgjlKP April 11, 2026 at 08:43PM

Show HN: OpenDescent, decentralised encrypted messenger, no servers, no accounts https://ift.tt/YJX29uN

Show HN: OpenDescent, decentralised encrypted messenger, no servers, no accounts https://ift.tt/3Xrn4ge April 11, 2026 at 11:33PM

Show HN: FluidCAD – Parametric CAD with JavaScript https://ift.tt/w4qkXYN

Show HN: FluidCAD – Parametric CAD with JavaScript Hello HN users, This is a CAD by code project I have been working on on my free time for more than year now. I built it with 3 goals in mind: - It should be familiar to CAD designers who have used other programs. Same workflow, same terminology. - Reduce the mental effort required to create models as much as possible. This is achieved by: - Provide live rendering and visual guidance as you type. - Allow the user to reference existing edges/faces on the scene instead of having to calculate everything. - Provide interactive mouse helpers for features that are hard to write by code: Only 3 interactive modes for now: Edge trimming, Sketch region extrude, Bezier curve drawing. - Implicit coding whenever possible: e.g: There are sensible defaults for most parameters. The program will automatically fuse intersecting objects together so you do not have to worry about what object needs to be fused with what. - It should be reasonably fast: The scene objects are cached and only the updated objects are re-computed. I think I have achieved these goals to a good extent. The program is still in early stages and there are many features I want to add, rewrite but I think it is already usable for simple models. https://fluidcad.io/ April 11, 2026 at 01:39AM