io.github.michaeljiangmingfeng-debug/quanttogo-mcp MCP Server
io.github.michaeljiangmingfeng-debug/quanttogo-mcp
Macro-factor quantitative trading signals for AI agents—live performance data, zero custody risk.
What is the io.github.michaeljiangmingfeng-debug/quanttogo-mcp MCP server?
QuantToGo MCP is a quantitative signal source that publishes systematic trading signals based on macroeconomic factors (FX cycles, liquidity rotation, sentiment, cross-market correlation) via the Model Context Protocol. AI agents can discover strategies, register for free trials, and retrieve live buy/sell signals—all within conversation, with full forward-tracked audit trails and zero fund custody.
QuantToGo exposes 8 tools for discovering quantitative trading strategies, comparing live performance, and accessing real-time trading signals. Unlike asset management or copy-trading platforms, it operates as a signal source: you receive timestamped, immutable signals and execute independently in your own brokerage account. All historical signals are forward-tracked with daily NAV data and git-auditable commit history. Use it to evaluate macro-factor strategies (US panic dip-buying, CNH-CSI300 correlation, large/small-cap rotation, sentiment reversals) and integrate live signals into your trading workflow.
How to install io.github.michaeljiangmingfeng-debug/quanttogo-mcp
Copy-paste configuration for popular MCP clients.
Tools & capabilities
Tools this server exposes to the agent.
list_strategies— List all strategies with live performance metrics (returns, max drawdown, Sharpe ratio, frequency)get_strategy_performance— Retrieve detailed performance data and daily NAV history for a single strategycompare_strategies— Side-by-side comparison of 2–8 strategiesget_index_data— Access QuantToGo custom indices (DA-MOMENTUM, QTG-MOMENTUM)get_subscription_info— View subscription plans and free trial enrollment detailsregister_trial— Self-register for a 30-day free trial with email; receive API Key instantlyget_signals— Retrieve latest buy/sell signals for a strategy (requires API Key)check_subscription— Check trial status and remaining days (requires API Key)
Use cases
- Discover and compare live quantitative trading strategies across US and China markets before committing capital
- Register for a free 30-day trial and retrieve real-time buy/sell signals for macro-factor strategies without leaving your AI assistant
- Evaluate strategy robustness by reviewing forward-tracked performance data, max drawdowns, and Sharpe ratios with immutable git audit trails
- Monitor sentiment-based signals (VIX panic reversals, Put/Call Ratio) and liquidity rotation strategies (large/small-cap rotation, CNY-index correlation) for tactical trading decisions
- Integrate live trading signals into your brokerage workflow while maintaining full custody and control of your funds
io.github.michaeljiangmingfeng-debug/quanttogo-mcp MCP server FAQ
QuantToGo is a quantitative signal source—it publishes systematic trading signals based on macroeconomic factors (FX cycles, liquidity rotation, sentiment) but never touches your funds. You receive signals, decide independently whether to act, and execute in your own brokerage account. It's analogous to a weather forecast: it predicts market conditions, but you decide how to respond.
Yes. Discovery tools (list_strategies, get_strategy_performance, compare_strategies, get_subscription_info) are free and require no authentication. To access live trading signals, you can self-register for a 30-day free trial via the register_trial tool using your email; you'll receive an API Key instantly.
In Claude Desktop or Cursor, add the MCP server configuration: use command 'npx' with args ['-y', 'quanttogo-mcp']. Alternatively, for remote access, use the SSE endpoint https://mcp.quanttogo.com/sse or HTTP endpoint https://mcp-us.quanttogo.com:8443/mcp.
Discovery tools require no authentication. To retrieve live trading signals via get_signals or check subscription status, you need an API Key, which you obtain free by calling register_trial with your email address.
All performance is forward-tracked from live signals with daily timestamps. Every signal is immutable and published at the moment it's generated, including all losses and drawdowns. Git commit history provides an independent audit trail; performance is updated weekly via GitHub Actions.
QuantToGo covers US and China markets with 8 live strategies: US panic dip-buying (VIX sentiment), CNH-CSI300 correlation, TQQQ timing, large/small-cap rotation, CNY-index correlation, Put/Call Ratio sentiment, low-volume value, and A-stock limit-down rebounds. Cumulative returns range from +81.8% to +671.8% with Sharpe ratios 1.4–2.0.
README (reference)
Source of truth, from the repository.
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
<!-- PERFORMANCE_TABLE_START -->| 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% | -43.5% | 2.0 | Weekly |
| 平滑版3x纳指 | US | Trend: TQQQ timing | +558.3% | -69.9% | 1.4 | Monthly |
| 大小盘IF-IC轮动 | China | Liquidity: large/small cap rotation | +446.2% | -22.0% | 1.9 | Daily |
| 聪明钱沪深300择时 | China | FX: CNY-index correlation | +385.8% | -29.9% | 1.8 | Daily |
| PCR散户反指 | US | Sentiment: Put/Call Ratio | +247.9% | -24.8% | 1.7 | Daily |
| 冷门股反指 | China | Attention: low-volume value | +227.6% | -32.0% | 1.5 | Monthly |
| 抄底信号灯(A股) | China | Sentiment: limit-down rebound | +81.8% | -9.1% | 1.6 | Daily |
<!-- PERFORMANCE_TABLE_END -->Last updated: 2026-09-28 · 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。"
🔗 Links
| Audience | URL |
|---|---|
| Visitors / Free Trial | www.quanttogo.com/playground |
| Subscribers / Invited Users | www.quanttogo.com · web.quanttogo.com |
| AI Agents / Mechanism Audit | www.quanttogo.com/ai/ |
<a id="中文"></a>
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。"
🔗 链接
| 用户类型 | 地址 |
|---|---|
| 访客 / 免费试用 | www.quanttogo.com/playground |
| 订阅用户 | www.quanttogo.com · web.quanttogo.com |
| AI 代理 / 机制审计 | www.quanttogo.com/ai/ |
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
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