QuantToGo MCP — Macro Factor Quantitative Signal Source

Name: QuantToGo MCP — Macro Factor Quantitative Signal Source
Author: QuantToGo

@QuantToGo

关于 QuantToGo MCP — Macro Factor Quantitative Signal Source

A macro-factor quantitative signal source accessible via MCP. 8 transparent, auditable strategies spanning China A-shares, offshore RMB, US tech, and retail sentiment. Built on persistent macro factors (capital flows, behavioral incentives, regulatory boundaries), not ML pattern

#quantitative-trading #finance #trading-signals #macro-factor #us-stocks #china-stocks #ai-agent #signal-source

基本信息

分类

其他

传输方式

stdio

发布者

QuantToGo

提交者

michaeljiangmingfeng-debug

配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "quanttogo": {
      "command": "npx",
      "args": [
        "quanttogo-mcp"
      ]
    }
  }
}

工具

未检测到工具

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

What is QuantToGo MCP — Macro Factor Quantitative Signal Source?

A macro-factor quantitative signal source accessible via the Model Context Protocol (MCP). It provides 8 tools and 1 resource for AI agents to discover strategies, register for a free trial, query live trading signals, and check subscription status—all within the conversation. All performance shown is forward-tracked from live signals, not backtested. QuantToGo is not a trading platform, asset manager, or copy-trading community; it is a quantitative signal source that publishes systematic trading signals based on macroeconomic factors.

How to use QuantToGo MCP — Macro Factor Quantitative Signal Source?

Install and configure the server by adding a JSON block to your MCP client (Claude Desktop, Cursor, Coze, or any Streamable HTTP client). For local execution use "command": "npx", "args": ["-y", "quanttogo-mcp"]. For remote access use the SSE URL https://mcp.quanttogo.com/sse or Streamable HTTP endpoint https://mcp-us.quanttogo.com:8443/mcp. No additional configuration is required; AI agents can immediately call tools like list_strategies, register_trial, and get_signals.

Key features of QuantToGo MCP — Macro Factor Quantitative Signal Source

Quantitative signal source with 8 MCP tools and 1 resource
Macrofactor-driven strategies (sentiment, FX, trend, liquidity)
Zero configuration setup for AI agents
Live forward-tracked, auditable performance (not backtested)
Free 30-day trial with instant API key via email
Supports both local (npx) and remote (SSE/HTTP) transports
Strategies focus on ETF/futures to avoid individual stock risk

Use cases of QuantToGo MCP — Macro Factor Quantitative Signal Source

AI assistants can discover and compare the live performance of all strategies
Users can register for a free trial and receive trading signals within the chat
Check remaining trial days and subscription status interactively
Obtain the latest buy/sell signals for a specific strategy in real time
Evaluate multiple strategies side-by-side using a quantitative framework

FAQ from QuantToGo MCP — Macro Factor Quantitative Signal Source

How is QuantToGo different from a trading platform or asset manager?

QuantToGo is a signal source—like a weather forecast for financial markets. It publishes trading signals; you decide whether to act in your own brokerage account. It never touches your funds.

What are the runtime requirements?

The MCP server runs via npx (Node.js required) for local setups, or connects remotely via SSE/Streamable HTTP. No other dependencies are needed.

Where do the signals and performance data live?

All signals are published on QuantToGo’s servers and are immutable—timestamped at publication. Performance is forward-tracked and auditable through GitHub commit history.

Is there a free trial? How do I get an API key?

Yes, a 30-day free trial is available. Use the register_trial tool with your email to get an API key instantly. The key is required for signal tools.

What transports and authentication are supported?

Supports local stdio (via npx) and remote SSE (URL: https://mcp.quanttogo.com/sse) and Streamable HTTP (https://mcp-us.quanttogo.com:8443/mcp). No auth is needed for discovery tools; signals require an API key obtained via trial registration.