Investment Research
Top open-source Investment Research AI systems, agents, and MCP tools.
Discover and install verified Investment Research AI systems, autonomous agent skills, and Model Context Protocol servers on AIStoreHub. Reusable, security-scanned, and ready for 1-click execution in Cursor, Claude Code, and terminal workflows.
Available AI Systems & Skills (20)
Open in Advanced FilterHunterCode · Community Edition · 腾讯 WorkBuddy 金融版的开源本地替代方案 · open-source, local alternative to Tencent WorkBuddy Finance Edition · 多智能体投研终端 A股/港股/美股 · 推理在你机器上跑 · 仓位不出你硬盘 · BYOK · Apache 2.0 · docker compose 自托管
Opptrix — AI驱动的全球多市场投研工作台 | Open-source LLM research assistant for China A-shares. 170+ MCP tools, factor screening, backtest, watchlist & Electron desktop. TypeScript · React · Fastify monorepo.
A股多Agent投研框架 — 适配A股数据源(龙虎榜/游资/解禁等)，7位分析师基于A股规则的辩论决策，基于TradingAgents深度改造，适配大A。A-share multi-agent investment research framework — 7 AI analysts, bull/bear debate, risk assessment。
A股 PEG 估值分析工具 — 彼得·林奇 PEG 投资法本地化实践 | A-share PEG valuation tool with AI-powered analysis
AI 时代的伯克希尔：基于 Claude Code / Codex 的价值投资研究框架。巴菲特·芒格·段永平·李录四大师方法论 + 多Agent并行研究。| AI-era Berkshire: a value investing research framework built for Claude Code / Codex. 4 masters' methodologies + multi-agent adversarial analysis.
Reusable Skills for LLMQuant Agent, Claude Code, Claude.ai, Cursor, Hermes Agent, OpenClaw and Codex, grounded in LLMQuant Data
Vibe-Research：A 股、美股、港股的投研工作台 · 自选与持仓、每日复盘、产业资讯、产业研究、个股深挖、回测、研报库，168 个数据端点。支持 Claude Code、Codex、WorkBuddy 订阅或任意模型 API。 | A research workbench for China A-shares, US and HK stocks.
🔌 Claude Code Plugin for institutional-grade equity research. Install with /plugin marketplace add. Generates professional buy/sell recommendations with comprehensive fundamental analysis, technical indicators, and risk assessment. Educational use only - not financial advice.
Alpha Desk — a deepseek-harness (dsh) skill pack that turns an agent session into a compliance-first AI investment desk: multi-strategy fund backtesting via ai-hedge-fund, a tools/pre-execute risk gate, cron monitoring and thesis memory. 把 dsh 会话变成合规、可复现、可追责的 AI 投研工作台。
Serenity-inspired Agent Skill for supply-chain bottleneck stock research
Local-first A-share research workbench for DeepSeek Harness: market dashboards, watchlists, valuation, four investor agents, versioned reports, and continuous post-report chat.
Agent-native investment research workspace for evidence-tracked, refreshable investment theses across equities, earnings, macro, and portfolio review.
A股全栈数据工具包：行情K线·当日逐笔·研报·信号·资金面·新闻·财务·公告·打板·ETF期权·舆情·宏观利率·期货大宗(含大商所日K)·事件驱动·可转债 | 15层·87端点·34数据源·除iwencai外免Key | A-share data for AI agents: K-lines, ticks, reports, fund flow, news, financials, filings, options, macro, futures, events, convertibles | 15 layers·87 endpoints·34 sources
EvoQuant is a self-evolving AI research agent specialized in quantitative investment research. It runs the full research loop autonomously
A data platform for investment research. Ingests financial data sources and computes point-in-time financial metrics for valuation and screening. Delivered as an MCP server.
研迹 Trail｜本地优先的 AI 投资研究工作台。连接行情、K 线与深度研究，让判断可追溯、风险可复核。Local-first AI investment research desktop with an evidence-grounded copilot.
Multi-agent crew that autonomously scrapes financial filings, runs balance sheet ratio analysis, and drafts company investment memos.
The most complete open-source, self-hosted Agentic Trading OS—AI research, Python strategies, factor discovery, backtesting, optimization, paper/live multi-asset execution, risk controls, monitoring, MCP, and multi-tenant SaaS in one auditable stack.
Industry and company research domain pack for DeepSeek Harness: methodology skills, industry chain mapping, public-source policy/news tracking, company research cards, and auditable research reports. Research only - not investment advice.
Build & Monetize for Investment Research
Have you created an autonomous agent, MCP server, or Claude Code skill for Investment Research? Publish it to AIStoreHub with dual-currency checkout (USD $ + INR ₹) and earn 85–90% net revenue.