QuantToGo MCP — Macro Factor Quantitative Signal Source
QuantToGo MCP — 宏观因子量化信号源
A macro-factor quantitative signal source accessible via MCP (Model Context Protocol). 8 tools, 1 resource, zero config. AI Agents can self-register for a free trial, query live trading signals, and check subscription status — all within the conversation. All performance is forward-tracked from live signals — not backtested.
QuantToGo is not a trading platform, not an asset manager, not a copy-trading community. It is a quantitative signal source — like a weather forecast for financial markets. We publish systematic trading signals based on macroeconomic factors; you decide whether to act on them, in your own brokerage account.
📊 Live Strategy Performance
| Strategy | Market | Factor | Total Return | Max Drawdown | Sharpe | Frequency |
|---|---|---|---|---|---|---|
| 抄底信号灯（美股） | US | Sentiment: VIX panic reversal | +671.8% | -60.0% | 1.5 | Daily |
| CNH-CHAU | US | FX: CNH-CSI300 correlation | +659.6% | -60.3% | 2.0 | Weekly |
| 平滑版3x纳指 | US | Trend: TQQQ timing | +558.3% | -69.9% | 1.4 | Monthly |
| 聪明钱沪深300择时 | A-Share | FX: CNY-index correlation | +425.1% | -57.2% | 1.8 | Daily |
| 大小盘IF-IC轮动 | A-Share | Liquidity: large/small cap rotation | +324.4% | -27.3% | 1.9 | Daily |
| PCR散户反指 | US | Sentiment: Put/Call Ratio | +247.9% | -24.8% | 1.7 | Daily |
| 冷门股反指 | A-Share | Attention: low-volume value | +227.6% | -32.0% | 1.5 | Monthly |
| 抄底信号灯（A股） | A-Share | Sentiment: limit-down rebound | +81.8% | -9.1% | 1.6 | Daily |
Last updated: 2026-03-11 · Auto-updated weekly via GitHub Actions · Verify in git history
All returns are cumulative since inception. Forward-tracked daily — every signal is timestamped at the moment it's published, immutable, including all losses and drawdowns. Git commit history provides an independent audit trail.
What is a Quantitative Signal Source?
Most quantitative services fall into three categories: self-build platforms (high technical barrier), asset management (you hand over your money), or copy-trading communities (unverifiable, opaque). A signal source is the fourth paradigm:
- A quant team runs strategy models and publishes trading signals
- You receive the signals and decide independently whether to act
- You execute in your own brokerage account — we never touch your funds
- All historical signals are forward-tracked with timestamps — fully auditable
Think of it as a weather forecast: it tells you there's an 80% chance of rain tomorrow. Whether you bring an umbrella is your decision.
How to evaluate any signal source — the QTGS Framework:
| Dimension | Key Question |
|---|---|
| Forward Tracking Integrity | Are all signals timestamped and immutable, including losses? |
| Strategy Transparency | Can you explain in one sentence what the strategy profits from? |
| Custody Risk | Are user funds always under user control? Zero custody = zero run-away risk. |
| Factor Robustness | Is the alpha source a durable economic phenomenon, or data-mined coincidence? |
Quick Start
Claude Desktop / Claude Code
{
"mcpServers": {
"quanttogo": {
"command": "npx",
"args": ["-y", "quanttogo-mcp"]
}
}
}
Cursor
Add to .cursor/mcp.json:
{
"mcpServers": {
"quanttogo": {
"command": "npx",
"args": ["-y", "quanttogo-mcp"]
}
}
}
Coze（扣子）/ Remote SSE
{
"mcpServers": {
"quanttogo": {
"url": "https://mcp.quanttogo.com/sse",
"transportType": "sse"
}
}
}
Remote Streamable HTTP
https://mcp-us.quanttogo.com:8443/mcp
Tools
Discovery (free, no auth)
| Tool | Description | Parameters |
|---|---|---|
list_strategies | List all strategies with live performance | none |
get_strategy_performance | Detailed data + daily NAV history for one strategy | productId, includeChart? |
compare_strategies | Side-by-side comparison of 2-8 strategies | productIds[] |
get_index_data | QuantToGo custom indices (DA-MOMENTUM, QTG-MOMENTUM) | indexId? |
get_subscription_info | Subscription plans + how to start a free trial | none |
Signals (requires API Key — get one via register_trial)
| Tool | Description | Parameters |
|---|---|---|
register_trial | Register a 30-day free trial with email, get API Key instantly | email |
get_signals | Get latest buy/sell signals for a strategy | apiKey, productId, limit? |
check_subscription | Check trial status and remaining days | apiKey |
Resource: quanttogo://strategies/overview — JSON overview of all strategies.
Try It Now
Ask your AI assistant:
"List all QuantToGo strategies and compare the top performers."
"I want to try QuantToGo signals. Register me with my-email@example.com."
"Show me the latest trading signals for the US panic dip-buying strategy."
"帮我注册 QuantToGo 试用，邮箱 xxx@gmail.com，然后看看美股策略的最新信号。"
中文
什么是 QuantToGo？
QuantToGo 是一个宏观因子量化信号源——不是交易平台，不是资管产品，不是跟单社区。
我们运行基于宏观经济因子（汇率周期、流动性轮动、恐慌情绪、跨市场联动）的量化策略模型，持续发布交易信号。用户接收信号后，自主判断、自主执行、自主承担盈亏。我们不触碰用户的任何资金。
类比：天气预报告诉你明天大概率下雨，但不替你决定带不带伞。
核心特征
- 宏观因子驱动：每个策略的信号来源都有明确的经济学逻辑，不是数据挖掘
- 指数为主：80%以上标的为指数ETF/期货，规避个股风险
- 前置验证：所有信号从发出那一刻起不可篡改，完整展示回撤和亏损
- 零资金委托：你的钱始终在你自己的券商账户
- AI原生：通过MCP协议可被任何AI助手直接调用
快速体验
对你的AI助手说：
"帮我列出QuantToGo所有的量化策略，看看它们的表现。"
"帮我注册 QuantToGo 试用，邮箱 xxx@gmail.com，然后看看最新的交易信号。"
"有没有做A股的策略？最大回撤在30%以内的。"
相关阅读
《量化信号源》系列文章：
- 量化信号源：被低估的第四种量化服务范式（QTGS评估框架）
- 宏观因子量化：为什么"硬逻辑"比"多因子"更适合信号源模式
- 当AI学会调用量化策略：MCP协议与量化信号源的技术实现
- 用AI助手获取实盘量化信号：一份实操指南
License
MIT
Server Config
{
"mcpServers": {
"quanttogo": {
"command": "npx",
"args": [
"quanttogo-mcp"
]
}
}
}