Ross ROSS = Recommend OSS · open-source software intelligence for agents

OpenByteInc/QuantDinger

AI quantitative trading platform for crypto, stocks, and forex with backtesting, live trading, market data, and multi-agent research.vibe-trading ,trading-agents,ai-trader,ai-trading observed · 2026-08-28

github.com/OpenByteInc/QuantDinger · homepage · Python · Apache-2.0 (permissive) observed · 2026-08-28

Health v2 · maintenance only

82/100

  • Activity 99
  • Release rhythm 98
  • Longevity 17
How is this computed?

round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.

  • gap_med: 0
  • age_days: 248
  • days_rel: 15
  • days_push: 9
  • n_releases_24m: 46

Full methodology

Adoption not part of the score

11112 stars · 2332 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

QuantDinger is an open-source, self-hosted AI quantitative trading platform covering crypto, stocks, and forex. It combines AI multi-agent research with Python strategy development, backtesting, paper trading, live execution, and monitoring in one stack.

Use cases

  • backtest trading strategies on crypto and stocks
  • run AI agents to research trading ideas
  • execute live trades via Binance, Alpaca, or Coinbase
  • paper trade strategies before going live
  • self-host a quantitative trading platform
  • monitor live trading performance
  • connect trading tools to LLMs via MCP server

When to choose

  • you want an all-in-one self-hosted quant trading stack with AI research, backtesting, and live execution
  • you trade across crypto, stocks, and forex and need multi-exchange support
  • you want to expose trading capabilities to LLM agents through MCP

When to avoid

  • you need a lightweight backtesting library to embed in your own code rather than a full platform
  • you require guaranteed profitability or financial advice - trading involves risk
  • you cannot self-host Docker-based services with PostgreSQL and Redis

Facets

application · maturity active

trading agent-framework mcp monitoring data-visualization self-hosted fintech artificial-intelligence analytics python self-hosted windows quantitative-finance backtesting live-trading crypto stocks forex trading-agents mcp-server alpaca binance coinbase paper-trading strategy-development cryptocurrency ai-agents docker web-server linux macos

2 sources

Member repositories

RepositoryRoleHealth v2
OpenByteInc/QuantDingermain82

For agents

markdown · JSON · MCP: product_card(name="OpenByteInc/QuantDinger")

Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem