
Nomas - Structured SEC Data for Research, APIs, and Agents
Query normalized SEC filings, insider trades, and holdings via APIs or RAG exports.
@nomasfyi · X
mcp server with sanitized SEC data
The full gallery
Tech stack
19 projects

Query normalized SEC filings, insider trades, and holdings via APIs or RAG exports.
@nomasfyi · X
mcp server with sanitized SEC data

Supplier and customer relationships pulled from SEC filings, with the source sentence behind every tie. Earnings dates, market-implied expected moves, options positioning and ETF e
Varamir
Bloomberg charges hedge funds $25k/year to see who actually supplies who. Varamir does it free. →

Upload a CAS PDF to get AI portfolio analysis with benchmark comparisons and allocation insights.
@iASHeeesh · X

AI-powered terminal for analyzing IDX stocks with broker analysis, foreign flow tracking, and technical signals.
@eglant_stock · X
Ini yang kadang pasar belum hargai sepenuhnya. Riset mendalam soal human capital di balik adopsi teknologi bisa dilihat di Bagi yang mau diskusi lebih lanjut soal tren ini, bisa join komunitas kami di Bagi yang mau diskusi lebih lanjut soal tren ini, bisa join komunitas kami di Bagi yang mau diskusi lebih lanjut soal tren ini, bisa join komunitas kami di Bagi yang mau diskusi lebih lanjut soal tren ini, bisa join komunitas kami di

Analyze stocks with AI equity research, valuations, and swing trade recommendations.
@WingGirlTrader · X
Here is a prime example of how AI is having the day trader look more like an investment portfolio manager. I mean this is exactly what you are talking about. Its here already.. and with vibe coding, it is super low cost. In this case below FREE at

Track real-time Indian stock prices, charts, and market analysis on NSE and BSE exchanges.
@SammedChougule · X
✨ What's New in Stocker? Just shipped a major update to Stocker. This release is all about one thing: Cleaner UI. Faster insights. Better investing experience. Here's what's new 👇 #Buildinpublic #FinTech #Stocker #Softwareengineer #StockMarket

Analyze US stocks by watching AI investment personas debate each company.
hobbescotch · HN
Noema – AI personas debate US listed stocks

Financial tools for IPO tracking, retirement planning, mortgage calculation, and company/advisor fraud verification.
@Meesam970 · X
KairosTrue — is set of financial tools Market Intelligence tools (ipo tracker, inside trading alert) Retirement planner and mortgage tool cluster Fraud protection tool you can search any company and advisor here to check its legitimacy

Analyze football markets with pressure graphs and backtest trading strategies.
@KSertttttttt · X

Track and manage your stock, ETF, and fixed-income investment portfolio with automatic quotes and generate PDF/Excel reports.
@nkrbrasilmix · X
Check out what I just built with Lovable!

Filter thousands of US stocks across 24 screeners to identify trading opportunities.
@serkanglatt · X
Developing — 24 proven stock screeners sift through thousands of US tickers to surface just the few worth your time. Unusual stock options activity, options flow & options-backed signals let you see where institutional money is flowing.

Analyze cryptocurrency markets with Chan Theory patterns, K-line charts, and anomaly detection.
@onehopeA9 · X
用 DAPPOS @dappOS_com 做了一个加密货币缠论分析网站,也是我一直想做没时间做的! 来看看缠论三买的威力: 不是不会写代码。 我自己是程序员,真要硬写当然能写。 但问题是:没时间。🤡 做交易的人都懂,真正消耗人的不是“看一根 K 线”,而是把一堆信息拼起来: K 线结构。 缠论笔、中枢。 一买二买三买。 一卖二卖三卖。 资金费率。 持仓量变化。 成交量异动。 市场舆情。 这些模块涉及太多方面,写得出来,但太费时间。 所以我一直想做一个自己的交易雷达: 接币安历史数据。 用 TradingView 展示 K 线。 自动画缠论结构。 标注买卖点。 再把资金费率、持仓量、成交量和币安广场热度放进去。 想法很清楚。 但一直躺在 TODO 里。 最近用 xbubble 的 Coding 功能试了一下,直接把需求丢进去: “做一个加密货币缠论分析网站,接入币安一年历史数据,用 TradingView 展示 K 线,自动画笔、中枢、一买二买三买、一卖二卖三卖,增加异动分析和币安广场舆情热度。” 它真给我生成了一个能跑的原型。 这次最戳我的不是“AI 会写代码”。 而是 xBubble 把最消耗时间的工程杂活压短了。 以前我自己做: ❌ 搭项目结构 ❌ 爬数据源和图表库 ❌ 写 K 线处理 ❌ 写缠论结构识别 ❌ 做前端交互 ❌ 部署、改样式、修细节 一圈下来,核心想法还没验证,人先累了。 现在变成: ✅ 先描述业务目标 ✅ 让 xBubble 生成可运行原型 ✅ 我再校验规则、调整逻辑、优化体验 ✅ 把时间花在交易理解和产品迭代上 这对程序员其实很有价值。 因为程序员最缺的不是能力,而是时间和注意力。 我这个原型现在大概有几块: 第一,TradingView K 线主图。 用币安数据展示行情,再叠加缠论结构。 第二,笔和中枢。 把原本需要手动盯的结构,先自动画出来。 第三,买卖点雷达。 一买、二买、三买,一卖、二卖、三卖,先帮我筛可能的位置。 第四,异动面板。 资金费率、持仓量、成交量变化,和 K 线结构一起看。 第五,舆情热度。 把币安广场讨论热度也拉进来,看看市场情绪是不是和盘面互相印证。 你可以理解成: 我不是让 AI 替我交易。 我是让 AI 帮我做一个交易前的信息雷达。 我觉得 xBubble 和普通 AI