whchien/ai-trader
Backtrader-powered backtesting framework for algorithmic trading, featuring 20+ strategies, multi-market support, CLI tools, and an integrated MCP server for professional traders.
Overview
whchien/ai-trader is a Python MCP server licensed under GPL-3.0. Backtrader-powered backtesting framework for algorithmic trading, featuring 20+ strategies, multi-market support, CLI tools, and an integrated MCP server for professional traders. Topics: ai, algorithmic-trading, backtrader, portfolio-management, stock-price-prediction, trading, ai-agents, cli, mcp, mcp-server, quantitative-finance.
Ranked #1515 out of 25632 indexed tools.
In the top 6% of all indexed tools.
Ecosystem
Python GPL-3.0
aialgorithmic-tradingbacktraderportfolio-managementstock-price-predictiontradingai-agentsclimcpmcp-serverquantitative-finance
Signal Breakdown
Stars 514
Freshness 1mo ago
Issue Health 57%
Contributors 1
Dependents 0
Forks 71
Description Detailed
License GPL-3.0
How to Improve
Freshness high impact
Contributors medium impact
Dependents medium impact
Matched Queries
From the README
# AI-Trader [中文版說明 (Chinese Subpage)](README_zh.md) A professional, config-driven backtesting framework for algorithmic trading, built on Backtrader. Seamlessly test, optimize, and integrate trading strategies with Large Language Models (LLMs) across stocks, crypto, and forex markets. ## Key Features - **Config-Driven Workflows**: Define and manage backtests with version-controllable YAML files for reproducible results. - **Seamless LLM Integration**: Built-in MCP (Model Context Protocol) server allows AI assistants like Claude to run backtests, fetch data, and analyze strategies. - **Multi-Market Support**: Test strategies on US stocks, Taiwan stocks, cryptocurrencies, and forex. - **Extensive Strategy Library**: Comes with over 20 built-in strategies, from classic indicators to advanced adaptive models. - **Powerful CLI**: A rich command-line interface to run backtests, fetch market data, and list strategies. - **Developer Friendly**: Easily create and test custom strategies withRead full README on GitHub →
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