No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by cloudQuant · MCP Server · ★ 181
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
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🚀 Backtrader Professional Python Algorithmic Trading Backtesting Framework English | 中文 📖 Documentation (EN) · 📖 中文文档 · 🌐 GitHub Pages 🐛 Report Bug · 💬 Discussions Installation I have published the pybind11-based Python wheel to PyPI: https://pypi.org/project/back-trader-cpp/ You can install it directly: It currently supports Python 3.8-3.14 and covers macOS, Windows, Linux, and other systems. C++ and pybind11 Performance Highlights 117 strategy benchmark cases, with the C++ version reaching 117/117 success and 0 metric mismatches; C++ total-time median speedup: 128.82x; C++ run-time median speedup: 235.78x; pybind11 total-time median speedup: 43.39x; pybind11 run-time median speedup: 57.60x.
| Stars | 181 |
| Forks | 41 |
| Language | Python |
| Category | MCP Server |
| License | GPL-3.0 |
| Quality Score | 67.6020696434207/100 |
| Last Updated | 2026-09-16 |
| Created | 2024-12-20 |
| Platforms | browser, mcp, python |
| Est. Tokens | ~23k |
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backtrader is High-performance Python backtesting & live-trading framework: 45%+ faster than upstream, 50+ indicators, tick-to-daily strategies, plus an AI-native workflow (MCP server, agent skills, web platform).. It is categorized as a MCP Server with 181 GitHub stars.
backtrader is primarily written in Python. It covers topics such as algorithmic-trading, backtesting, cryptocurrency.
You can find installation instructions and usage details in the backtrader GitHub repository at github.com/cloudQuant/backtrader. The project has 181 stars and 41 forks, indicating an active community.
backtrader is released under the GPL-3.0 license, making it free to use and modify according to the license terms.
The top alternatives to backtrader on Agent Skills Hub include maverick-mcp, best-of-algorithmic-trading, superior-skills. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: