easy-stock — A desktop app using AI agents to analyze Chinese A-shares, offering market insights and portfolio optimization.
Analyzed by Sai Pavan Gopularam · AI · Finance · View on GitHub
- Stars: 1465
- Forks: 132
- Commits last 30 days: 75
- Health: Active (75 commits this month)
- Language: Go
- License: Other
What It Is
Imagine having a personal AI stock analyst that lives on your computer, specifically trained to understand the nuances of the Chinese A-share market. That's easy-stock. It's a desktop application built with Go, React, and Electron, combining traditional market data with advanced AI agents to help investors make sense of complex stock movements.
This tool aims to move beyond simple data display. It tackles the challenge of interpreting market structure, identifying themes, and understanding investor sentiment. By automating data collection, synthesizing expert opinions, and providing AI-driven insights, easy-stock helps users build a more evidence-based and continuously evolving research system for their investments.
License Verdict
PolyForm Noncommercial License — No Commercial Use — Commercial Use Prohibited • Requires Written Permission for Business
This project is licensed under the PolyForm Noncommercial License 1.0.0. This means you cannot use it for any direct or indirect commercial purpose without explicit written permission from the author. This includes SaaS, paid services, or integrating it into commercial products. It is strictly for personal learning, research, and experimental use.
How to Use It
easy-stock is a desktop application. You download the pre-built executable for your operating system from GitHub Releases and install it. Initial setup involves configuring your chosen Large Language Model (LLM) API keys, such as DeepSeek or Kimi, and potentially logging into stock data sources like Xueqiu or Taoguba, as detailed in the user guide.
Prerequisites:
- Access to LLM API (e.g., DeepSeek, Kimi)
Estimated setup time: 15 minutes.
## 1. Download the latest release from GitHub:
## https://github.com/jundizhou/easy-stock/releases/latest
## 2. Install the desktop application for your OS (macOS .dmg, Windows .exe).
## 3. Open easy-stock and navigate to settings to configure your LLM API key.
## (e.g., DeepSeek API Key, Kimi API Key)What I'd Build With This
AI-Powered A-Share Daily Briefing (micro-saas)
Leverage the '大 V 自动复盘' and '观点共识' features to generate a concise, AI-summarized daily briefing on A-share market sentiment and key themes. Deliver this via email or a private Telegram channel before market open. Target busy individual investors or small fund managers who need quick, synthesized market intelligence without sifting through dozens of articles.
Effort: 1 Week Build Time (after commercial license acquired) · Target: Individual A-Share Investors, Small Fund Managers · Pricing: $29/month
Intelligent A-Share Research Platform (saas)
Build a web-based SaaS platform replicating and enhancing easy-stock's core features, including individual stock research, portfolio inspection, and AI optimization. Offer advanced analytics on market sentiment, sector trends, and historical performance. Target professional traders, financial advisors, and prop trading firms in China seeking an edge in automated, evidence-based research beyond traditional terminals.
Effort: 6 Months Build Time (after commercial license acquired) · Target: Professional Traders, Financial Advisors, Prop Trading Firms · Pricing: $199-$499/month per user
Custom AI Quant Research Engine (enterprise)
Offer a bespoke, on-premise or private cloud deployment of easy-stock's Go backend and AI agent architecture. Integrate with a client's existing data feeds and proprietary models to provide a tailored AI-driven quantitative research engine. Focus on large asset management firms, hedge funds, or institutional investors who require deep customization, high data security, and specialized A-share market intelligence for strategic decision-making.
Effort: 3 Months Sales Cycle + 6 Months Dev (after commercial license acquired) · Target: Large Asset Managers, Hedge Funds, Institutional Investors · Pricing: $50,000 - $250,000+ /year
Sai Pavan Gopularam's Take
This project is seriously impressive, showing how AI agents can dissect complex financial markets. The problem is, it's under a non-commercial license, so you can't just take it and launch a business without getting explicit permission. If you *could* license it commercially, a SaaS offering for A-share professional investors could easily fetch $200/month per user, given its deep feature set.
Watch Out For
- Non-Commercial License: The project is licensed under PolyForm Noncommercial License 1.0.0, strictly prohibiting any commercial use without explicit written permission from the author. This means you cannot build a business with it out-of-the-box.
- A-Share Market Focus: This tool is specifically designed and optimized for the Chinese A-share market, including its unique market structure, data sources, and expert opinions. Adapting it for other markets would require significant re-engineering and data integration.
- Local-First Data Storage: easy-stock stores all its research, articles, and historical data locally on your machine. While great for privacy, this design choice limits multi-device synchronization or collaborative features without custom backend development.
- AI is a Research Assistant, Not a Decision Maker: The project explicitly states that AI aims to provide better perception and efficient research, not to make investment decisions. AI outputs and third-party data can have delays, omissions, or errors, requiring independent judgment from the user.
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