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.

Command-line edition of the open-source OpenBB investment research platform: query stock prices, financial statements, macroeconomic and other financial data from the terminal, and automate data pulls with Routine scripts. Officially maintained; some sources need API keys.

Multi-agent simulated hedge fund: agents modeled on investors like Buffett and Munger work with quant and risk modules to analyze stocks, with backtesting. Good for teaching investment frameworks. Needs Financial Datasets and model API keys; no real trading, 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.

Financial research terminal agent, like Claude Code for finance: breaks company research questions into steps, pulls financial statements and market data, and self-checks before answering. Needs Bun, a model API key and a Financial Datasets API key; for learning and research only.

Live stock and crypto quotes in the terminal with portfolio profit and loss tracking, using Yahoo Finance and Coinbase data. The main view is an interactive dashboard; ticker print exports holdings from your config at current prices as JSON or CSV for scripts and agents.

Language and toolset for double-entry bookkeeping in text files: bean-check validates the ledger, bean-format normalizes it, and Fava or beanquery handle reports and queries. Plain-text ledgers are easy for agents to generate and keep in version control.

Plain-text double-entry accounting: track income, expenses, investments and time, generate balance sheets, income statements and budget reports in one command, with CSV import and JSON output for agent reconciliation and reporting. Converts to and from Beancount.

Open-source PDF table extraction with a camelot CLI: exports tables from financial reports, bank statements and statistical reports to Excel, CSV or Markdown, with an accuracy score. Needs Python 3.10+; handles text-based PDFs by default, scans need the ml and ocr extras. Double-check results.

Fetches US, Hong Kong and China A-share stock data with zero runtime dependencies: real-time quotes, daily, weekly and monthly candles and search as JSON, falling back across Tencent, Sina and Eastmoney sources. Also runs as an MCP server. Unofficial public APIs, no stability guarantee.

Longbridge's official CLI: real-time HK and US quotes, candles, options and warrants, news and filings, positions and cash, and order placement (previewed by default, executed only on confirmation). All commands output JSON for agents. Needs a Longbridge account and browser login.

Unofficial Yahoo Finance data tool with a yahoo-finance CLI, an MCP server and an agent skill: stock quotes, price history, financials, option chains and analyst ratings. Needs Node.js 22+, no API key. The API is unofficial and may change; for research only.

Kraken exchange's official CLI: quotes and trading for crypto, tokenized US stocks, forex and futures, with a built-in MCP server and paper trading that need no API key. Experimental; live trading needs a Kraken account and API key and uses real money, so check local rules and confirm trades.

Beancount plain-text accounting in Rust (rledger): validate ledgers, run BQL queries, build balance sheets and income statements, import bank CSV/OFX, track budgets, returns and capital gains. Has an MCP server and ag-rledger (JSON output) for agents. Tax figures need an accountant's review.

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.