# Vibe-Trading

> An open-source research workspace that turns finance questions into runnable analysis, backtests and multi-agent reviews

- Category: Agents & Automation / Finance & Market Agents
- Language: Python
- Licence: MIT
- Repository: https://github.com/HKUDS/Vibe-Trading
- Website: https://vibetrading.wiki/
- Canonical page: https://ai-tldr.dev/tools/vibe-trading/
- Updated: 2026-07-10

## In short

Vibe-Trading is an open-source research workspace from HKUDS that connects natural-language prompts to market-data loaders, strategy generation, backtest engines, reports, exports and persistent research memory. It sits in the Finance & Market Agents category of the Agents & Automation tools and is open-source, written in Python and licensed MIT. To get started: install from PyPI.

## Overview

Vibe-Trading is an open-source research workspace from HKUDS that connects natural-language prompts to market-data loaders, strategy generation, backtest engines, reports, exports and persistent research memory. You ask a finance question in plain language and it answers by running real tools against real data, leaving behind strategy code, metrics, validation artifacts and run cards rather than a chat transcript.

The project is built for research, simulation and backtesting. It can also trade autonomously through a broker you authorise yourself, but it holds no funds, never trades outside the limits you set, and can be halted instantly. Broker credentials go to the OS keyring rather than config files, and every run writes a hash manifest over the prompt, skills, tool registry and package versions plus a hash-chained audit ledger, so you can answer "what methodology produced that number?" after the fact.

Beyond the single agent, Vibe-Trading runs multi-agent analyst teams — investment, quant, crypto, macro and risk workflows — with streaming progress and persisted reports. It reaches markets across A-share, Hong Kong, US, Canada, UK, India and Korea equities plus crypto, futures and forex, ships a pre-built alpha zoo you can bench in one line, and exposes the same runtime through a CLI, a FastAPI web UI, a REST API and an MCP server that plugs into Claude Desktop, Cursor and other MCP clients.

## What it does

- Natural-language market research with tool calls, document and chart reading, and reusable session context
- Multi-agent trading teams for investment, quant, crypto, macro and risk reviews, with streaming progress and persisted reports
- Cross-market backtesting across A-share, HK, US, Canada, UK, India and Korea equities plus crypto, futures and forex, with point-in-time data, validation artifacts and run cards
- A pre-built alpha zoo benched in one command, categorising alphas as alive, reversed or dead on your own universe
- Broker connectors kept read-only or paper by default, with credentials in the OS keyring, a committed mandate, an order guard and an instant halt
- Governance in every run: a hash manifest over prompt, skills, tool registry and package versions, plus a hash-chained audit ledger
- One runtime behind four transports — interactive CLI/TUI, FastAPI web UI, REST API, and an MCP server for Claude Desktop, Cursor and other clients
- Exportable artifacts including reports, TradingView Pine Script, TDX and MetaTrader 5

## Getting started

Vibe-Trading is on PyPI as `vibe-trading-ai` and needs Python 3.11+ and an LLM API key from any supported provider — or a local Ollama install, which needs no key.

1. Install from PyPI

   One pip install gives you three commands: `vibe-trading` (CLI/TUI), `vibe-trading serve` (web server) and `vibe-trading-mcp` (MCP server).

```bash
pip install vibe-trading-ai
```

2. Configure a provider

   `init` walks you through an interactive .env setup. Supported providers include OpenRouter, OpenAI, Anthropic, DeepSeek, Gemini, Groq, DashScope/Qwen, Zhipu, Moonshot/Kimi, MiniMax and local Ollama.

```bash
vibe-trading init
```

3. Run a first research task

   Pass a prompt with -p and the agent fetches data, writes and runs the backtest, and summarises the result.

```bash
vibe-trading run -p "Backtest a BTC-USDT 20/50 moving-average strategy for 2024 and summarize return and drawdown"
```

4. Bench the alpha zoo

   Score a whole family of pre-built quant alphas against your universe and period in one line.

```bash
vibe-trading alpha bench --zoo gtja191 --universe csi300 --period 2018-2025 --top 20
```

5. Launch the web UI or the MCP server

   `serve` starts the FastAPI web UI; `vibe-trading-mcp` starts the MCP server over stdio so Claude Desktop, Cursor or another MCP client can call the same tools.

```bash
vibe-trading serve --port 8899
vibe-trading-mcp
```

## When to use it

- Ask a market question in plain language and get an answer backed by fetched data, tool calls and a reproducible run record
- Prototype and backtest a strategy idea across several markets without wiring up data loaders and an engine yourself
- Run a team of analyst agents over the same thesis to get investment, quant and risk views side by side
- Give an existing MCP client — Claude Desktop, Cursor, OpenClaw — a set of read-only market-data and quant tools

## Version history

- 2026-07-10 v0.1.11: Adds NSE and BSE as first-class backtest markets, a point-in-time fundamentals layer that grows the Alpha Zoo to 460 factors, and research delivery across 16 messaging channels.