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 fidetolabs · MCP Server · ★ 177
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is qanat safe to install? View the security audit →
Qanat Declare the alpha as a DAG. Hand the backtest to an agent. Quick start · Agents · How it works ·
| Stars | 177 |
| Forks | 35 |
| Language | Python |
| Category | MCP Server |
| License | MIT |
| Quality Score | 66.5268492420697/100 |
| Last Updated | 2026-09-14 |
| Created | 2026-09-05 |
| Platforms | mcp, python |
| Est. Tokens | ~19k |
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qanat is Agent-native workflow engine for building and backtesting alphas as DAGs.. It is categorized as a MCP Server with 177 GitHub stars.
qanat is primarily written in Python. It covers topics such as alpha-research, backtesting, dag.
You can find installation instructions and usage details in the qanat GitHub repository at github.com/fidetolabs/qanat. The project has 177 stars and 35 forks, indicating an active community.
qanat is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to qanat on Agent Skills Hub include maverick-mcp, QuantGPT, best-of-algorithmic-trading. 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: