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Add backtester-mcp to Trading & Backtesting (#351)

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Baz Cosmopoulos
2026-04-22 08:19:44 -03:00
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@@ -239,6 +239,7 @@ A curated list of insanely awesome libraries, packages and resources for Quants
- [antback](https://github.com/ts-kontakt/antback) - `Python` - A lightweight, event-loop-style backtest engine that allows a function-driven imperative style using efficient stateful helper functions and data containers.
- [VARRD](https://github.com/augiemazza/varrd) - `Python` - AI-powered trading edge discovery platform that validates trading ideas with event studies, statistical tests, and real market data. Web app, MCP server, CLI (`pip install varrd`), and Python SDK.
- [JIT-Optimization-Engine](https://github.com/cloudsealed/JIT-Optimization-Engine) - `Python` - High-performance analytical core using LLVM JIT (Numba) to process large-scale telemetry for quant diagnostics.
- [backtester-mcp](https://pypi.org/project/backtester-mcp/) - `Python` - Local-first backtesting engine with built-in overfitting checks (PBO, deflated Sharpe, bootstrap CI, walk-forward) and a native MCP server for AI agents. [GitHub](https://github.com/bcosm/backtester-mcp)
- [backtest](https://cran.r-project.org/web/packages/backtest/index.html) - `R` - Exploring Portfolio-Based Conjectures About Financial Instruments.
- [pa](https://cran.r-project.org/web/packages/pa/index.html) - `R` - Performance Attribution for Equity Portfolios.
- [QuantTools](https://quanttools.bitbucket.io/_site/index.html) - `R` - Enhanced Quantitative Trading Modelling.