Home / LLM agents & research
guangxiangdebizi/TradingAgents-MCPmode
Multi-agent stock analysis system using MCP tools
What it is
A multi-agent trading analysis system that integrates Model Context Protocol tools. Several specialised agents split the work of market analysis, investment suggestions and risk management to form a complete decision process. Quant researchers, developers and investors who want LLM help with stock analysis are the target users. Documentation is mainly in Chinese, and the quality of its analysis depends on the language model and data sources connected.
At a glance
Research onlyOur rating, based on popularity, maintenance and how ready it is for real use.
| Best for | Developers |
|---|---|
| Used for | Strategy research, AI agents |
| Markets | US equities, China A-shares |
| Stack | Python |
| Learning curve | Moderate learning curve |
| Practical value | Medium practical value |
| Cost | Free and open source |
| Hardware | No GPU needed |
| Maintenance | No commits in over six months |
GitHub stars, last 30 days
Daily snapshots since 2026-09-28 (up to 30 days): +1 over the period, now 339. Gaps mean no snapshot was taken that day.
TradingAgents-MCPmode 是一个创新的多智能体交易分析系统，集成了 Model Context Protocol (MCP) 工具，实现了智能化的股票分析和交易决策流程。系统通过多个专业化智能体的协作，提供全面的市场分析、投资建议和风险管理。
Similar tools
LLM multi-agent investment research framework specialized for A-shares
Multi-agent LLM research assistant for Chinese A-shares
Multi-agent LLM research system for China A-shares
Multi-agent LLM framework for financial trading analysis
Python design patterns for building an AI stock trading bot
LLM trading research agent with multi-market backtesting