@_zheergen: Wow! Someone built a Claude Code for financial markets! It can not only analyze stocks and dig into earnings reports, but also let multiple AI analysts work at the same time — automated market monitoring, research report generation, and even connecting to brokerages for trading. LangAlpha, 2.2K Stars, Apache-2.0 open source, a platform built specifically for…

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The open-source project LangAlpha has been released, dubbed the Claude Code for financial markets: it brings together multi-AI analyst collaboration, financial data, long-term memory, automated report generation, market alerts, and brokerage trading interfaces, with support for custom models and local self-hosting.

Wow! Someone built a Claude Code for financial markets! It can not only analyze stocks and dig into earnings reports, but also let multiple AI analysts work at the same time — automated market monitoring, research report generation, and even connecting to brokerages for trading. LangAlpha, 2.2K Stars, Apache-2.0 open source — an AI Agent work platform built specifically for financial research and investment. Previously, using AI to research stocks meant constantly asking questions about quotes, earnings reports, and valuations, then having to reorganize the context from scratch the next day to continue. This system is something else: it directly integrates financial data, AI Agents, long-term memory, and trading tools, letting AI continuously follow up on the same investment research task. Core capabilities: 1️⃣ Multi-AI collaboration: multiple analysts research financial statements, valuation, options, and macro data simultaneously, with automatic result aggregation 2️⃣ Financial data analysis: access to stocks, Crypto, forex, options, SEC filings, and macro data 3️⃣ Automated report generation: built-in financial research Skills, supporting DCF valuation, earnings analysis, Excel models, and PDF reports 4️⃣ AI chart reading and drawing: reads real-time charts and automatically marks support/resistance, trend lines, Fibonacci levels, and key events 5️⃣ Automated market alerts: set price trigger conditions and scheduled research tasks, pushed via Telegram, Discord, and other channels 6️⃣ Brokerage trading interfaces: connect to Robinhood, IB, moomoo, Webull, with different operations executed based on the brokerage and granted permissions What's really impressive is that you can just tell the AI: "Research NVDA, analyze its latest earnings report and valuation, generate an investment report, check it once a week, and alert me if the price breaks below the specified level." It saves research materials in the workspace so you can continue the analysis later without starting over every time. It also supports models like ChatGPT and Claude, and offers web, desktop, and Docker self-hosting options. If you work on stock research, financial AI Agents, or quantitative system development, this project is worth checking out! GitHub: https://github.com/ginlix-ai/LangAlpha…
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The harness for agentic trading.

Open-source AI agents that research the market, build the thesis, and trade your own brokerage account within the permissions you set.

Try LangAlpha ↗ · Get started · Agentic trading · Harness design · Full-stack architecture · Security English · 简体中文 · 日本語

Subagents: four analysts work the question under the lead agent, each card counting its tools and tokens, and one /html-report turns their findings into the primer on the right

Live chart: each note sits on the day the stock reacted, and the chat lists every move in a table with the source behind it

Sources: switch between this turn’s 14 sources and the thread’s 560, grouped into web search and crawling, SEC filings, market data and data tools, each with the prompt or arguments it ran with

Packages: six built-in bundles of MCP servers and skills, each switched on or off as one, with room for 50 of your own

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