经 AI Skill Hub 精选评估,Vibe交易智能体 获评「推荐使用」。已获得 7.2k 颗 GitHub Star,这款AI工具在功能完整性、社区活跃度和易用性方面表现出色,AI 评分 7.8 分,适合有一定技术背景的用户使用。
Vibe交易智能体 是一款基于 Python 开发的开源工具,专注于 交易自动化、算法交易、MCP工具 等核心功能。作为 GitHub 开源项目,它拥有活跃的社区支持和持续的版本迭代,代码完全透明可审计,支持本地部署以保护数据隐私。无论是个人使用还是集成到企业工作流,都能提供稳定可靠的解决方案。
Vibe交易智能体 是一款基于 Python 开发的开源工具,专注于 交易自动化、算法交易、MCP工具 等核心功能。作为 GitHub 开源项目,它拥有活跃的社区支持和持续的版本迭代,代码完全透明可审计,支持本地部署以保护数据隐私。无论是个人使用还是集成到企业工作流,都能提供稳定可靠的解决方案。
# 方式一:pip 安装(推荐)
pip install vibe-trading
# 方式二:虚拟环境安装(推荐生产环境)
python -m venv .venv
source .venv/bin/activate # Windows: .venv\Scripts\activate
pip install vibe-trading
# 方式三:从源码安装(获取最新功能)
git clone https://github.com/HKUDS/Vibe-Trading
cd Vibe-Trading
pip install -e .
# 验证安装
python -c "import vibe_trading; print('安装成功')"
# 命令行使用
vibe-trading --help
# 基本用法
vibe-trading input_file -o output_file
# Python 代码中调用
import vibe_trading
# 示例
result = vibe_trading.process("input")
print(result)
# vibe-trading 配置文件示例(config.yml) app: name: "vibe-trading" debug: false log_level: "INFO" # 运行时指定配置文件 vibe-trading --config config.yml # 或通过环境变量配置 export VIBE_TRADING_API_KEY="your-key" export VIBE_TRADING_OUTPUT_DIR="./output"
<p align="center"> <b>English</b> | <a href="README_zh.md">中文</a> | <a href="README_ja.md">日本語</a> | <a href="README_ko.md">한국어</a> | <a href="README_ar.md">العربية</a> </p>
<p align="center"> <img src="assets/icon.png" width="120" alt="Vibe-Trading Logo"/> </p>
<p align="center"> <b>One Command to Empower Your Agent with Comprehensive Trading Capabilities</b> </p>
<p align="center"> <img src="https://img.shields.io/badge/Python-3.11%2B-3776AB?style=flat&logo=python&logoColor=white" alt="Python"> <img src="https://img.shields.io/badge/Backend-FastAPI-009688?style=flat" alt="FastAPI"> <img src="https://img.shields.io/badge/Frontend-React%2019-61DAFB?style=flat&logo=react&logoColor=white" alt="React"> <a href="https://pypi.org/project/vibe-trading-ai/"><img src="https://img.shields.io/pypi/v/vibe-trading-ai?style=flat&logo=pypi&logoColor=white" alt="PyPI"></a> <a href="LICENSE"><img src="https://img.shields.io/badge/License-MIT-yellow?style=flat" alt="License"></a> <br> <a href="https://github.com/HKUDS/.github/blob/main/profile/README.md"><img src="https://img.shields.io/badge/Feishu-Group-E9DBFC?style=flat-square&logo=feishu&logoColor=white" alt="Feishu"></a> <a href="https://github.com/HKUDS/.github/blob/main/profile/README.md"><img src="https://img.shields.io/badge/WeChat-Group-C5EAB4?style=flat-square&logo=wechat&logoColor=white" alt="WeChat"></a> <a href="https://discord.gg/2vDYc2w5"><img src="https://img.shields.io/badge/Discord-Join-7289DA?style=flat-square&logo=discord&logoColor=white" alt="Discord"></a> </p>
<p align="center"> <a href="https://vibetrading.wiki/">Website</a> · <a href="https://vibetrading.wiki/docs/">Docs</a> · <a href="#-news">News</a> · <a href="#-key-features">Features</a> · <a href="#-shadow-account">Shadow Account</a> · <a href="#-demo">Demo</a> · <a href="#-quick-start">Quick Start</a> · <a href="#-examples">Examples</a> · <a href="#-api-server">API / MCP</a> · <a href="#-roadmap">Roadmap</a> · <a href="#-contributing">Contributing</a> </p>
<p align="center"> <a href="#-quick-start"><img src="assets/pip-install.svg" height="45" alt="pip install vibe-trading-ai"></a> </p>
---
![]() 🔍 Self-Improving Trading Agent
• Natural-language market research
• Strategy drafts and file/web analysis • Memory-backed workflows |
![]() 🐝 Multi-Agent Trading Teams
• Investment, quant, crypto, and risk teams
• Streaming progress and persisted reports • Workers grounded with fetched market data |
![]() 📊 Cross-Market Data & Backtesting
• A/HK/US equities, crypto, futures, and forex
• Data fallback and composite backtests • PIT data, validation, and run cards |
![]() 👥 Shadow Account
• Broker-journal behavior diagnostics
• Rule-based Shadow Account comparisons • Exportable audit reports and strategy code |
Detailed inventories are folded below to keep the main README scannable. Open them when you want to inspect the available building blocks.
<details> <summary><b>Finance Skill Library</b> <sub>77 skills across 8 categories</sub></summary>
| Category | Skills | Examples |
|---|---|---|
| Data Source | 7 | data-routing, tushare, yfinance, okx-market, akshare, mootdx, ccxt |
| Strategy | 17 | strategy-generate, cross-market-strategy, technical-basic, candlestick, ichimoku, elliott-wave, smc, multi-factor, ml-strategy |
| Analysis | 17 | factor-research, macro-analysis, global-macro, valuation-model, earnings-forecast, credit-analysis, dividend-analysis |
| Asset Class | 9 | options-strategy, options-advanced, convertible-bond, etf-analysis, asset-allocation, sector-rotation |
| Crypto | 7 | perp-funding-basis, liquidation-heatmap, stablecoin-flow, defi-yield, onchain-analysis |
| Flow | 7 | hk-connect-flow, us-etf-flow, edgar-sec-filings, financial-statement, adr-hshare |
| Tool | 11 | backtest-diagnose, report-generate, pine-script, doc-reader, web-reader, vnpy-export, alpha-zoo |
| Risk Analysis | 1 | ashare-pre-st-filter |
</details>
<details> <summary><b>Preset Trading Teams</b> <sub>29 swarm presets</sub></summary>
| Preset | Workflow |
|---|---|
investment_committee | Bull/bear debate → risk review → PM final call |
global_equities_desk | A-share + HK/US + crypto researcher → global strategist |
crypto_trading_desk | Funding/basis + liquidation + flow → risk manager |
earnings_research_desk | Fundamental + revision + options → earnings strategist |
macro_rates_fx_desk | Rates + FX + commodity → macro PM |
quant_strategy_desk | Screening + factor research → backtest → risk audit |
technical_analysis_panel | Classic TA + Ichimoku + harmonic + Elliott + SMC → consensus |
risk_committee | Drawdown + tail risk + regime review → sign-off |
global_allocation_committee | A-shares + crypto + HK/US → cross-market allocation |
<sub>Plus 20+ additional specialist presets — run vibe-trading --swarm-presets to explore all.
</sub>
</details>
<details> <summary><b>Alpha Zoo</b> <sub>452 pre-built quant alphas across 4 zoos</sub></summary>
pytest-socket network kill-switchLICENSE.md declaring formulas as mathematical content| Zoo | Count | Source | License |
|---|---|---|---|
| **qlib158** | 154 | Microsoft Qlib Alpha158 (Apache-2.0, commit-pinned) | Apache-2.0 |
| **alpha101** | 101 | Kakushadze (2015), "101 Formulaic Alphas", arXiv:1601.00991 | Formulas are mathematical content |
| **gtja191** | 191 | Guotai Junan (2014), "191 Short-period Trading Alpha Factors" | Formulas are mathematical content |
| **academic** | 6 | Fama-French 5 + Carhart momentum (price-based proxies) | Public academic literature |
Run vibe-trading alpha list to browse, vibe-trading alpha show <id> for formulas + source, vibe-trading alpha bench --zoo X --universe Y --period Z to score a whole zoo.
</details>
LANGCHAIN_PROVIDER=openai-codex, then run vibe-trading provider login openai-codex. This does not use OPENAI_API_KEY.Supported LLM providers: OpenRouter, OpenAI, DeepSeek, Gemini, Groq, DashScope/Qwen, Zhipu, Moonshot/Kimi, MiniMax, Xiaomi MIMO, Z.ai, Ollama (local). See .env.example for config.
Tip: All markets work without any API keys thanks to automatic fallback. yfinance (HK/US), OKX (crypto), mootdx (A-shares, TCP-direct, no IP throttle), and AKShare (A-shares, US, HK, futures, forex) are all free. Tushare token is optional — mootdx is the preferred no-token A-share fallback, with AKShare as a broader backup.
pip install vibe-trading-ai
Then run a first research task:
vibe-trading init
vibe-trading run -p "Backtest a BTC-USDT 20/50 moving-average strategy for 2024 and summarize return and drawdown"
Package name vs commands: The PyPI package isvibe-trading-ai. Once installed, you get three commands: | Command | Purpose | |---------|---------| |vibe-trading| Interactive CLI / TUI | |vibe-trading serve| Launch FastAPI web server | |vibe-trading-mcp| Start MCP server (for Claude Desktop, OpenClaw, Cursor, etc.) |
vibe-trading init # interactive .env setup
vibe-trading # launch CLI
vibe-trading serve --port 8899 # launch web UI
vibe-trading-mcp # start MCP server (stdio)
```bash git clone https://github.com/HKUDS/Vibe-Trading.git cd Vibe-Trading cp agent/.env.example agent/.env
```bash git clone https://github.com/HKUDS/Vibe-Trading.git cd Vibe-Trading python -m venv .venv
```bash pip install vibe-trading-ai
Create ~/.vibe-trading/agent.json:
{
"mcpServers": {
"my-server": {
"command": "uvx",
"args": ["my-mcp-server"]
}
}
}
Run any CLI command — tools from my-server are automatically injected into the agent's registry after local tools:
vibe-trading run "use my-server to do X"
|
https://github.com/user-attachments/assets/4e4dcb80-7358-4b9a-92f0-1e29612e6e86 </td> <td width="50%"> https://github.com/user-attachments/assets/3754a414-c3ee-464f-b1e8-78e1a74fbd30 </td> </tr> <tr> <td colspan="2" align="center"><sub>☝️ Natural-language backtest & multi-agent swarm debate — Web UI + CLI</sub></td> </tr> </table> </div> --- Edit agent/.env — uncomment your LLM provider and set API keydocker compose up --build ``` Open Docker publishes the backend on .venv\Scripts\Activate.ps1 # Windows PowerShellpip install -e . cp agent/.env.example agent/.env # Edit — set your LLM provider API key vibe-trading # Launch interactive TUI bash
🧠 Environment VariablesCopy
<sub>* Ollama does not require an API key. OpenAI Codex uses ChatGPT OAuth and stores tokens via Free data (no key needed): A-shares via AKShare, HK/US equities via yfinance, crypto via OKX, 100+ crypto exchanges via CCXT. The system automatically selects the best available source for each market. Web UI SettingsThe Web UI Settings page lets local users update the LLM provider/model, base URL, generation parameters, reasoning effort, and optional market data credentials such as the Tushare token. Settings are persisted to Settings reads are side-effect free: --- Config reference
Config file location: For URL-based transports, Terminal 1: API servervibe-trading serve --port 8899 🖥 CLI ReferenceThe interactive TUI (
<details> <summary><b>Slash commands inside TUI</b></summary>
</details> <details> <summary><b>Single run & flags</b></summary>
</details> --- Save your preferences oncevibe-trading run -p "Remember: I prefer RSI-based strategies, max 10% drawdown, hold period 5–20 days" 🌐 API Server
Interactive docs: Per-session overrides (API)When creating a session via the API you can pass
🧪 Research WorkflowMost runs follow the same evidence path: route the request, load the right market context, execute tools, validate outputs, and keep the artifacts inspectable.
--- Path C: MCP pluginSee MCP Plugin section below. Swarm Workflows```bash 🔌 MCP PluginVibe-Trading exposes 22 MCP tools for any MCP-compatible client. Runs as a stdio subprocess — no server setup needed. 21 of 22 tools work with zero API keys (HK/US/crypto). Only <details> <summary><b>Claude Desktop</b></summary> Add to
</details> <details> <summary><b>OpenClaw</b></summary> Add to
</details> <details> <summary><b>Cursor / Windsurf / other MCP clients</b></summary>
</details> MCP tools exposed (22): <details> <summary><b>Install from ClawHub (one command)</b></summary>
This downloads the skill + MCP config into your agent's skills directory. No cloning needed. Browse on ClawHub: clawhub.ai/skills/vibe-trading </details> <details> <summary><b>OpenSpace — self-evolving skills</b></summary> All 77 finance skills are published on open-space.cloud and evolve autonomously through OpenSpace's self-evolution engine. To use with OpenSpace, add both MCP servers to your agent config:
OpenSpace will auto-discover all 77 skills, enabling auto-fix, auto-improve, and community sharing. Search for Vibe-Trading skills via </details> ---
🇨🇳 中文文档镜像
AI 翻译
2026-05-28
英文原文章节由系统翻译为中文摘要,便于快速理解。完整原文见上方 "📑 README 深度解析"。
📌 简介
Vibe-Trading 是您的个人交易智能体(Trading Agent)。通过简单的指令,即可赋予 Agent 强大的市场分析与策略执行能力,让复杂的金融研究变得触手可及。 ⚡ 功能介绍
本项目具备自我进化的交易智能体能力,支持通过自然语言进行市场研究、策略草拟及文件生成。内置强大的 Finance Skill Library,包含 8 个类别、共 77 项专业金融技能,覆盖从传统市场到 Crypto 及 DeFi 的全方位能力。 📋 环境依赖
运行本项目需要准备好支持的 LLM API key,或者使用 Ollama 进行本地部署。若选择本地安装(Path B),需确保 Python 版本为 3.11+;若选择 Docker 部署(Path A),则需安装 Docker 环境。此外,也支持通过 ChatGPT OAuth 使用 OpenAI Codex。 🛠 安装步骤(Docker/pip/源码)
提供多种安装方式:1. 通过 PyPI 一键安装:`pip install vibe-trading-ai`;2. Docker 部署(零配置):克隆仓库并使用 `docker compose up --build`;3. 本地源码安装:克隆仓库后创建 `.venv` 虚拟环境并执行 `pip install -e .`。 🚀 使用教程
安装完成后,您可以使用 `vibe-trading` 命令启动交互式 TUI 界面进行任务。也可以通过 `vibe-trading run -p "任务描述"` 执行非交互式指令(如回测策略)。系统支持记忆您的偏好,例如通过指令设定风险控制参数,实现个性化交易体验。 ⚙️ 配置说明(含 MCP / env)
项目通过 `agent/.env` 文件进行配置。您需要根据需求取消注释对应的 LLM provider 并设置相应的 API key。若使用 Docker 部署,后端默认运行在 `127.0.0.1:8899`。若需在公网暴露 API,请务必设置强密码级的 `API_AUTH_KEY` 以确保安全。 🔌 API 说明
本项目提供灵活的接口调用方式。支持通过 `vibe-trading serve --port 8899` 启动 API 服务器。交互式 TUI 具备原生终端渲染能力,支持 Markdown 和表格展示;而对于脚本化调用,可通过 `--json` 参数获取结构化输出。 🔄 工作流/模块
系统采用严谨的研究工作流:首先进行 Plan 阶段,智能体根据请求选择相关的 Finance Skills、工具及数据源;随后执行工具并加载市场上下文;最后通过验证输出并生成可供检查的 Artifacts(研究产物),确保每一步决策都有据可查。
🎯 aiskill88 AI 点评
A 级
2026-05-16
融合LLM与量化交易的创新工具,MCP框架设计合理,功能完整,星数高表明认可度好,但交易类应用需谨慎对待。 📚 实用指南(长尾问题)
适合谁
最佳实践
常见错误
部署方案
⚡ 核心功能
👥 适合谁
⭐ 最佳实践
⚠️ 常见错误
👥 适合人群🎯 使用场景
⚖️ 优点与不足✅ 优点
⚠️ 不足
⚠️ 使用须知
AI Skill Hub 为第三方内容聚合平台,本页面信息基于公开数据整理,不对工具功能和质量作任何法律背书。 建议在沙箱或测试环境中充分验证后,再部署至生产环境,并做好必要的安全评估。 📄 License 说明
✅ MIT 协议 — 最宽松的开源协议之一,可自由商用、修改、分发,仅需保留版权声明。 🔗 相关工具推荐📚 相关教程推荐 📰 相关 AI 新闻
🍿 AI 圈相关吃瓜
🗺️ 相关解决方案
🧩 你可能还需要
基于当前 Skill 的能力图谱,自动补全的工具组合
❓ 常见问题 FAQ支持股票、期货、加密货币等多个市场,具体支持情况需查看官方文档。
💡 AI Skill Hub 点评
AI Skill Hub 点评:Vibe交易智能体 的核心功能完整,质量良好。对于AI爱好者来说,这是一个值得纳入个人工具库的选择。建议先在非生产环境试用,再逐步推广。 🌐 原始信息
🔗 原始来源
🐙 GitHub 仓库 https://github.com/HKUDS/Vibe-Trading
🌐 官方网站 https://pypi.org/project/vibe-trading-ai/
收录时间:2026-05-13 · 更新时间:2026-05-16 · License:MIT · AI Skill Hub 不对第三方内容的准确性作法律背书。 |