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Products that do what I built an AI agent that helps me invest does
A while back, I built a simple app to track stocks. It pulled market data and generated daily reports based on my risk tolerance. Basically a personal investment assistant. It worked well enough that I kept going. Now, the same framework helps me with real estate: comparing neighborhoods, checking flood risk, weather patterns, school zones, old vs. new builds, etc. It’s a messy, multi-variable decision—which turns out to be a great use case for AI agents. Instead of ChatGPT or Grok 4, I use mcp-agent, which lets me build a persistent, multi-agent system that pulls live data, remembers my…
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We’re thrilled to announce the launch of our AI-powered stock market analyst chatbot, designed to help you analyze stocks and gain valuable market insights with ease. Our intuitive conversational chat interface makes it simple for anyone to get started. Why You’ll Love It: Our AI Analyst uses a long-term value-growth investing strategy, similar to those employed by legendary investors like Warren Buffett, Mohnish Pabrai, Phil Town and Charlie Munger. It’s built to provide you with thorough, data-driven analysis to help you make informed investment decisions. Key Features: - Comprehensive…
2024 · decodeinvesting.com
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We created autonomous AI Agents that monitor the stock market for you while you go about your day. How it works: Tell our AI Assistant what you want to monitor, and it creates a project for our team of autonomous AI Agents. You'll get notifications (email + app) when significant events matching your criteria are detected. For short-term projects, you'll be notified when your analysis is ready. Behind the scenes: When you give the AI Assistant a request to monitor an entity (like a stock or group of stocks), an AI Project Manager plans the project and breaks the project down into manageable…
2024 · decodeinvesting.com
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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…
Apr 2026 · github.com
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Connect Your AI to Institutional-Grade Market Intelligence Plug any AI client, from ChatGPT to custom agents, directly into our financial data engine. Get real-time stock prices, fundamentals, institutional trading insights, and other financial data delivered through a universal Model Context Protocol (MCP) server.
Mar 2026 · financialdata.net
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Hey HN, I just spent the last few weeks building a database for agents. Over the last year I built PostHog AI, the company's business analyst agent, where we experimented on giving raw SQL access to PostHog databases vs. exposing tools/MCPs. Needless to say, SQL wins. I left PostHog 3 weeks ago to work on side-projects. I wanted to experiment more with SQL+agents. I built an MVP exposing business data through DuckDB + annotated schemas, and ran a benchmark with 11 LLMs (from Kimi 2.5 to Claude Opus 4.6) answering business questions with either 1) per-source MCP access (e.g. one Stripe…
Apr 2026 · github.com
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Hey HN! I built PRISM-INSIGHT, a multi-agent system where 13 specialized AI agents collaborate to analyze Korean stocks (KOSPI/KOSDAQ). It's completely open source and has been running live since March 2025. [What it does] The system automatically detects surging stocks twice daily, generates analyst-level reports, and executes trading strategies. Each agent specializes in something different – technical analysis, trading flows, financials, news, market conditions, etc. They work together like a real research team. [Why I built this] I wanted to see if GPT-4 and GPT-5 could genuinely…
Nov 2025
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For the last few months I have been analysing Peter Lynch’s books on stock picking and doing prompt engineering to check if AI could create useful stock analyses. To my surprise it started making reports that allow me to understand companies much faster with well cited sources. I hope you find it interesting and useful :) Perter Lynch’s books I analyzed: Learn to earn, One up on Wall Street, Beating the street
Jun 2026 · github.com
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Hey HN! Today I'm launching Pane, a tool that gives AI context on your financial data. Once connected, any MCP-compatible client (Claude, Cursor, ChatGPT, etc.) can answer questions like: - "What did I spend on food this month?" - "What's my net worth right now?" - "Show me my recurring subscriptions" - "How much do I owe across all credit cards?" - "What are my investment holdings?" It's been really transformative in helping me and some of my friends understand their finances, where they are overspending, or even being double billed in some cases. I'm very aware that this is a somewhat…
Mar 2026 · pane.money
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We’re DJ & Josh, co-founders of MichaelAI(https://michaelai.io) - we’re excited to share our new artificially intelligent investment analyst, Michael. Josh’s six-year stint at a hedge fund exposed him to the challenges of investment analysis. He had access to abundant resources, including data collected by junior analysts, detailed reports, refined data from third-party providers, and access to industry thought leaders. However, the process demands significant time commitment, continuous engagement with other parties, nuanced data, and the potential to miss out on crucial…
2023 · michaelai.io
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I'm Canadian, live abroad, and my money is scattered across two countries, multiple currencies, banks, brokerages, real estate, and some private equity. No app could hold all of it, and none could answer a simple question like "what's my actual USD exposure?" Brisa pulls everything together (Plaid + manual accounts + real estate + PE, all multi-currency) and puts an AI on top that has my full financial picture in context. Instead of clicking through charts, I can just ask. Would appreciate any feedback!
Jul 2026 · demo.joinbrisa.com
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Multi-agent AI that builds your investment portfolio
Jun 2026 · prospect-ai.moisesprat.dev
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I built a web page that aggregates data about data center buildup, sovereign fund investments into AI and bottlenecks. The objective is to predict AI race cooldown by looking at a potential decrease of activity involving these elements. The website looks at the quarterly forms from the 5 biggest hyperscalers and adds their CapEx into the mix, calculating a composite index in the end showing how likely it is for the AI race to slow down. Enjoy!
Jul 2026 · laurentiugabriel.github.io
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Recently, I was exploring the OpenAI Agents SDK and building MCP agents and agentic Workflows. To implement my learnings, I thought, why not solve a real, common problem? So I built this multi-agent job search workflow that takes a LinkedIn profile as input and finds personalized job opportunities based on your experience, skills, and interests. I used: - OpenAI Agents SDK to orchestrate the multi-agent workflow - Bright Data MCP server for scraping LinkedIn profiles & YC jobs. - Nebius AI models for fast + cheap inference - Streamlit for UI (The project isn't that complex - I kept it…
2025
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I built Hermes, an open-source Python framework for multi-agent financial research. Most AI “equity research” demos stop at generating text. In practice, real workflows require pulling structured XBRL financials from SEC filings, extracting labeled sections like MD&A and Risk Factors, merging macro and market data, building actual Excel models with formulas, and generating investment memos in Word or PDF. Hermes is designed to handle that full pipeline end to end. It includes 35 financial data tools covering SEC EDGAR (via edgartools), FRED, Yahoo Finance market data, and RSS-based financial…
Feb 2026 · github.com
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