Tools

Multi-agent investment research framework where fundamental, sentiment, news and technical analysts, bull and bear researchers, a trader and risk managers debate a stock and produce a report and rating. Covers US, Hong Kong and A-shares. Needs Python and an LLM API key; not investment advice.

Open-source crypto trading framework: download market data, backtest and optimize strategies, and paper trade from the CLI while agents iterate on strategies. Docker recommended; strategies need Python and live trading needs exchange API keys. Backtests don't guarantee returns.

Microsoft's open-source AI quant investment research platform: the qrun command runs dataset building, model training, backtesting and evaluation from a YAML config, with many benchmark models. The official dataset is paused, so prepare market data per the README first.

Quant trading plugin from the wshobson/agents marketplace: quant analyst and risk manager subagents plus backtesting and risk metrics skills for strategy backtests, portfolio optimization and risk measures like VaR, Sharpe ratio and max drawdown. Needs local Python; not investment advice.

Trading research agent from HKU's HKUDS whose MCP server offers 70+ tools for quotes, financials, backtesting and research across A-shares, Hong Kong and US stocks and crypto. Needs local Python; HK, US and crypto research need no API key. For research only; not investment advice.

Plugin marketplace for investment research: six plugin groups covering yfinance market data, earnings previews and recaps, DCF valuation, option payoff charts, ETF premiums, read-only news from X, Discord and other social sources, and TradingView data. Research only, not investment advice.

Finance skills for US, Hong Kong and China A-share markets: news from 10+ sources, quotes and fundamentals, sentiment analysis, time-series forecasts, signal tracking, impact-chain diagrams and reports. Needs Python; some skills download PyTorch models. Not investment advice.

Stock analysis MCP for individual investors: quotes via yfinance, technical indicators such as RSI and MACD, screening strategies, a portfolio tracker and a trade journal. Core tools need no API key; backtesting and deep-research extensions are optional.

68 trading and quant skills focused on crypto and DeFi: market and on-chain data, technical indicators, backtesting, position sizing and risk, prediction markets, and tax tools for cost basis and wash sales. Most need Python and data API keys (often free tiers); get expert review.

Official FinLab quant skill: lets agents use FinLab data (mainly Taiwan stocks, plus US, Japan, Korea and Hong Kong) to write stock-picking strategies, run backtests and analyze factors. Needs a FinLab account (free tier has a daily data cap), Python 3.10+ and uv. Not investment advice.

QuantConnect's official CLI drives the open-source LEAN engine locally or in the cloud to download data, backtest and optimize quant strategies and deploy them live. Requires a paid-tier QuantConnect organization; strategies in Python or C#; local runs need Docker. Get expert review.

Official Alpha Vantage MCP: exposes its API as tools for stock and options quotes, fundamentals, news sentiment, forex, crypto, commodities, economic indicators and dozens of technical indicators. Needs a free API key; a remote OAuth server is also available.