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Oneqaz Trading MCP Server

@oneqaz-trading

基本信息

分类

金融与商务

传输方式

stdio

作者

oneqaz-trading

提交者

Junhyeong Park

关于 Oneqaz Trading MCP Server

Self-verifying trading MCP — regime detection + Trust Layer for crypto, US, KR stocks. 13 trust tools let AI agents verify accuracy, backtest tuning, news causality, feature governance, and strategy performance before recommending. 1,100+ symbols, 24/7 live data.

Oneqaz Trading MCP Server 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "oneqaz-trading-mcp": {
      "command": "docker",
      "args": [
        "build",
        "-t",
        "oneqaz-trading-mcp",
        "."
      ]
    }
  }
}

Oneqaz Trading MCP Server 工具

4

market_id, limit, action_filter, min_pnl, max_pnl, hours_back

market_id, min_roi, max_roi, strategy, sort_by, sort_order, limit

market_id, symbol, min_score, max_score, action_filter, interval

market_id, limit, decision_filter, hours_back

概览

What is Oneqaz Trading Mcp?

Oneqaz Trading Mcp is an MCP server that provides financial market intelligence, including regime detection, self-correcting signals, and macro context across crypto, US stocks, and Korean stocks. It is designed for AI agents and developers who need market-aware context without building the data pipeline themselves.

How to use Oneqaz Trading Mcp?

Connect via a live cloud API at https://api.oneqaz.com/mcp (no install) or run locally using pip install oneqaz-trading-mcp then oneqaz-trading-mcp init and oneqaz-trading-mcp serve. Configure via environment variables such as MCP_SERVER_PORT and DATA_ROOT. After starting, connect any MCP client (e.g., Claude) to the URL http://localhost:8010/mcp.

Key features of Oneqaz Trading Mcp

  • Regime detection (trending, ranging, volatile) per market and globally.
  • Self-correcting signals using Thompson Sampling on trade outcomes.
  • Macro context chain from global regime down to individual symbols.
  • 19 stateless resources and 4 tools for querying signals, positions, decisions.
  • _llm_summary field on every response optimized for AI consumption.
  • 24/7 live cloud API with 1,100+ symbols monitored.

Use cases of Oneqaz Trading Mcp

  • Give AI agents live market awareness with regime and signal context.
  • Build a regime-aware trading system that adapts actions to market state.
  • Perform cross-market macro-to-micro analysis of global flows into assets.
  • Ask Claude directly about market conditions, positions, and risks.

常见问题

1

How is Oneqaz Trading Mcp different from typical financial MCPs?

Oneqaz adds regime detection, self-correcting signals weighted by real outcomes, macro-to-asset context chains, and a live 24/7 cloud API, which typical financial MCPs lack.

2

What are the dependencies and runtime requirements?

For local use, install via pip; Python and SQLite are used. The live API requires no install beyond an MCP client. Docker is also supported.

3

Where does the data live?

Data is stored in a configurable root directory (`DATA_ROOT`) with subdirectories for global regime, coin market, KR market, US market, and external context. The live API uses OneQAZ's cloud servers.

4

What are the rate limits for the live API?

The live API has a daily quota of 1,500 requests per IP and a burst limit of 30 requests per minute per IP. Exceeding limits returns HTTP 429. Local servers have no rate limits.

5

What transports and authentication are supported?

The server uses HTTP as its transport (stateless). No authentication is mentioned for the free-tier live API; local demo data requires no auth.

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