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QuantToGo MCP Server

@michaeljiangmingfeng-debug

代码仓库主页

关于 QuantToGo MCP Server

Macro-factor quantitative signal source for AI agents via MCP. 宏观因子量化信号源。

基本信息

分类

金融与商务

许可证

MIT

运行时

python

传输方式

stdio

发布者

michaeljiangmingfeng-debug

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": [
        "-y",
        "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 Server?

QuantToGo MCP Server is 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 live trading signals, self-register for a free trial, and check subscription status. All performance data is forward-tracked from live signals, not backtested.

How to use QuantToGo MCP Server?

Install by adding a configuration entry to your MCP client (e.g., Claude Desktop, Cursor, or Coze). Use npx -y quanttogo-mcp for local stdio transport, or connect via remote SSE or Streamable HTTP endpoints. Then ask your AI assistant to list strategies, register a trial, or query signals.

Key features of QuantToGo MCP Server

  • 8 tools for discovery, registration, and signal retrieval
  • 1 resource: quanttogo://strategies/overview
  • Zero configuration – works out of the box
  • Self-registration for 30-day free trial with email
  • All signal performance is forward-tracked and immutable
  • AI-native – callable directly by any MCP-compatible agent

Use cases of QuantToGo MCP Server

  • An AI assistant lists all strategies and compares their live performance
  • A user registers for a free trial and receives an API key instantly
  • An agent queries the latest buy/sell signals for a specific strategy
  • Compare up to 8 strategies side-by-side within a conversation

FAQ from QuantToGo MCP Server

What does QuantToGo provide vs. a trading platform or asset manager?

QuantToGo is a quantitative signal source, not a trading platform, asset manager, or copy-trading community. It publishes systematic trading signals based on macroeconomic factors; users decide whether to act on them in their own brokerage accounts.

What are the runtime/dependency requirements?

The server is an npm package (quanttogo-mcp) and requires Node.js to run via npx. No additional configuration is needed.

Where do the signals and performance data live?

All signals are timestamped at the moment of publication and stored immutably. The git history of the repository provides an independent audit trail. Live performance data is hosted on QuantToGo servers and accessed via the MCP tools.

What transports and authentication are supported?

Transports: local stdio, remote SSE (https://mcp.quanttogo.com/sse), and Streamable HTTP (https://mcp-us.quanttogo.com:8443/mcp). Authentication: free tools require no API key; signal tools require an API key obtained via register_trial with an email address.

Are there any known limits?

The README does not mention explicit limits, but the free trial is 30 days, and subscription info is available via get_subscription_info.

评论

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