QuantToGo MCP Server
@michaeljiangmingfeng-debug
QuantToGo MCP Server について
Macro-factor quantitative signal source for AI agents via MCP. 宏观因子量化信号源。
基本情報
カテゴリ
金融とコマース
ライセンス
MIT
ランタイム
python
トランスポート
stdio
公開者
michaeljiangmingfeng-debug
投稿者
michaeljiangmingfeng-debug
設定
以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。
{
"mcpServers": {
"quanttogo": {
"command": "npx",
"args": [
"-y",
"quanttogo-mcp"
]
}
}
}ツール
ツールは検出されませんでした
ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。
概要
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.
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