Oneqaz Trading Mcp
About
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.
Details
- Author
- oneqaz-trading
- Downloads
- 239
- Categories
- Finance
Jump to
- 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.
Setting up with Highlight
This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:
- Download and install Highlight from highlightai.com/download
- Navigate to the plugins tab and select "Add Custom Plugin"
-
Configure the plugin with the settings below
Plugin Name
Oneqaz Trading McpCommand (node, npx, python, etc.)Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
- Enable "Start Automatically" if you want the plugin to start when Highlight launches
From the repository
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.
Claude Desktop / Cursor
Paste into your MCP client config file to install this server.
{
"mcpServers": {
"oneqaz trading mcp": {
"oneqaz-trading-mcp": {
"command": "docker",
"args": [
"build",
"-t",
"oneqaz-trading-mcp",
"."
]
}
}
}
}McpServers
{
"oneqaz-trading-mcp": {
"command": "docker",
"args": [
"build",
"-t",
"oneqaz-trading-mcp",
"."
]
}
}oneqaz-trading-mcp
<!-- mcp-name: io.github.wnsod/oneqaz-trading-mcp -->
> The context layer for financial AI.
>
> Your AI agent shouldn't just see prices — it should understand
> what regime the market is in, which signals are actually working right now,
> and how macro flows down to individual assets.
>
> OneQAZ provides this as a single MCP endpoint.
> Crypto, US stocks, Korean stocks. 1,100+ symbols. 24/7 live.
Keywords: MCP, trading, signals, market analysis, regime, portfolio, sentiment, technical analysis, crypto, stocks, Fear & Greed, cross-market, Claude, model context protocol
Why OneQAZ
Financial data APIs are everywhere. Market intelligence is not.
| | Typical financial MCP | OneQAZ |
|---|---|---|
| Price / OHLCV data | ✅ | ✅ |
| Technical indicators | ✅ | ✅ |
| Regime detection (trending / ranging / volatile) | ❌ | ✅ |
| Self-correcting signals (weighted by real outcomes) | ❌ | ✅ |
| Macro → ETF → Individual context chain | ❌ | ✅ |
| Live 24/7 cloud API | ❌ | ✅ |
Signal weights are adjusted continuously based on actual trade outcomes
per regime via Thompson Sampling — not static indicator thresholds.
Every response includes an _llm_summary field optimized for AI consumption.
What your AI gets
- Regime detection: Is the market trending, ranging, or volatile? Per-market and global
- Self-correcting signals: 1,100+ symbols scored by Thompson Sampling on actual trade outcomes
- Macro context chain: Global regime → bonds/forex/VIX/commodities → ETF/basket → individual symbol
- External context: News events, fundamentals, cross-market correlation — pre-processed for LLM consumption
- 19 Resources + 4 Tools: Stateless HTTP, compatible with any MCP client
- _llm_summary on every response: Human-readable text summary optimized for AI agent context windows
Market Coverage
| Market | Exchange | Universe | Symbols |
|--------|----------|----------|---------|
| Crypto | Bithumb | All listed pairs | ~440+ |
| Korean Stocks | KOSPI/KOSDAQ | KOSPI 200 | ~200 |
| US Stocks | NYSE/NASDAQ | S&P 500 | ~500 |
All symbols are monitored 24/7 with automated signal generation, regime detection, and virtual trading.
Quick Start
Option 1: Live API — no install needed
Real-time data, updated every minute.
{
"mcpServers": {
"oneqaz-trading": {
"url": "https://api.oneqaz.com/mcp"
}
}
}
Ask Claude: "What's the current market regime?"
Option 2: Local (demo data)
pip install oneqaz-trading-mcp
oneqaz-trading-mcp init # creates sample SQLite databases
oneqaz-trading-mcp serve # starts at http://localhost:8010
- Swagger UI: http://localhost:8010/docs
- MCP endpoint: http://localhost:8010/mcp
Then connect from Claude:
{
"mcpServers": {
"oneqaz-trading": {
"url": "http://localhost:8010/mcp"
}
}
}
Use Cases
1. Give your AI agent market awareness
Connect OneQAZ and your agent understands market context without you building the pipeline:
```python
Sign in to leave a review
Use Google, GitHub, or an email account so ratings stay tied to real people.
No reviews posted yet.
