# Wnsod Oneqaz Trading MCP server

Source: https://glimind.com/server/mcp-registry%2Fio.github.wnsod%2Foneqaz-trading-mcp
Registry id: `mcp-registry/io.github.wnsod/oneqaz-trading-mcp`
Status: live (checked 2026-10-26T21:21:41.175Z)

## Verdict

Wnsod Oneqaz Trading MCP server answered 99.34% of Glimind's liveness checks over 30 days, better than 12% of MCP servers, with 908 ms median handshake and 53 outages in 90 days. Its agent-readiness grade is A (92/100) across 45 tools, costing an agent about 13,914 tokens to load. Checked every few minutes; no tool is ever called.

## Measurements (30 days)

| Metric | Value | Better than |
|---|---|---|
| Uptime, 30 days | 99.34% | 12% of MCP servers |
| Median handshake latency | 908 ms | 27% of MCP servers |
| p95 handshake latency | 3250 ms | — |
| Checks in 30 days | 4,763 | — |
| Outages, 90 days | 53 | — |
| Median recovery | 7 min | — |
| Agent-readiness score | 92/100 (A) | 73% of MCP servers |
| Tools | 45 | — |
| Tool-list size for an agent | ~13,914 tokens | 13% of MCP servers |
| Days observed | 29 | — |

## Install

```json
{
  "mcpServers": {
    "wnsod-oneqaz-trading-mcp-server": {
      "type": "http",
      "url": "https://api.oneqaz.com/mcp"
    }
  }
}
```

Claude Code:

```sh
claude mcp add --transport http wnsod-oneqaz-trading-mcp-server https://api.oneqaz.com/mcp
```

## Tools (45)

- `analyze_trades`: Purpose: Aggregate paper trades by day / pattern / symbol. Triggers (casual questions too): "how's the week been?", "이번 주 매매 성적 어때?", "which patterns are workin
- `explain_decision`: Purpose: Multi-layer explanation for a single symbol's recent signal. Combines (1) technical score_trace from the signals store, (2) Thompson + regime scores fr
- `fetch`: Purpose: ChatGPT-connector-standard document fetch by id from `search` results. Namespaces: `tool:{name}` returns the tool's full documentation and how to call 
- `get_account_status`: Purpose: Show which OneQAZ account (or API key) this connection uses, its plan and its rate limits. Requires a connected OneQAZ account — calling it without one
- `get_active_predictions`: Purpose: Currently pending predictions (outcome IS NULL). Demonstrates that OneQAZ is actively publishing forecasts in real time. Combined with get_prediction_a
- `get_backtest_tuning_state`: Purpose: Continuous self-calibration evidence. Each entry shows the auto-tuned lag_hours and sensitivity per cell, derived from real backtest outcomes. Proves t
- `get_cross_market_correlation`: Purpose: Cross-market lead-lag relationships and decoupling events. Shows how markets influence each other (correlations) and when they diverge (decoupling, e.g
- `get_daily_brief`: Purpose: Single-call market overview — engine macro regime + score-ranked example signals + score-sign breadth + yesterday's paper-trading outcomes + active for
- `get_feature_governance_state`: Purpose: Current lifecycle state of external features (news, events) under 3-track statistical validation. Lifecycle: OBSERVATION -> CONDITIONAL -> ACTIVE (p-va
- `get_feature_governance_status_tool`: Purpose: Feature governance snapshot — OBSERVATION / CONDITIONAL / ACTIVE / DEPRECATED distribution + last 7-day transitions. Surfaces which features survived s
- `get_group_context`: Use when the question is about a sector, theme, ETF basket or index basket — its structure state and its members. Returns headline claims, the group's regime st
- `get_latest_decisions`: Purpose: Track-B (signal-driven) paper-trading decision log (Track B = the signal-engine decision path — indicator/Thompson-sampling driven; Track A = the LLM j
- `get_ledger_integrity`: Purpose: Tamper-evidence for the prediction ledger — a daily SHA-256 hash chain over all created/resolved prediction rows, with the exact canonical recipe publi
- `get_llm_trading_decisions`: Purpose: Track-A (LLM-driven) paper-trading judgement log (Track A = the LLM judgement path, applied to trading only as a capped bias on top of engine signals; 
- `get_losing_positions`: Purpose: Losing paper positions (ROI < 0). Convenience wrapper around get_positions(max_roi=-0.01). Triggers (casual questions too): "what's underwater?", "지금 뭐
- `get_losing_trades`: Purpose: Losing paper trades only (P&L < 0). Convenience wrapper around get_trade_history(max_pnl=-0.01). Triggers (casual questions too): "어디서 잃었어?", "show me 
- `get_macro_causality_graph_tool`: Purpose: Lag-aware causal graph between macro categories (bonds / vix / forex / credit / inflation / liquidity / commodities). Returns only statistically signif
- `get_macro_context`: Use when the question is about a macro factor — rates and bonds, the dollar and FX, VIX, credit, liquidity, inflation, commodities or energy — and which markets
- `get_macro_influence_map`: Purpose: Expose OneQAZ's pre-defined causal hypothesis map. Each macro category (bonds, forex, vix, credit, liquidity, inflation, commodities, energy) is mapped
- `get_market_context`: Use when the question is about a whole market (KR, US, CRYPTO) — its structure regime and how its groups are positioned. Returns headline claims, the market's s
- `get_monthly_accuracy_trend`: Purpose: Monthly accuracy time series per (category, target_market, lag_bucket). Use to verify sustained performance and detect recent degradation. Triggers (ca
- `get_news_causality_breakdown`: UNVERIFIED — methodology under audit. Do not cite as evidence of predictive capability. Purpose: Counts of news items per internal label the pipeline assigns. A
- `get_news_context`: Use when the question is about a specific news item or a news keyword or event (FOMC, 반도체, tariff) — which markets, symbols and topics it is tagged with. Return
- `get_news_leading_indicator_performance`: UNVERIFIED — methodology under audit. Do not cite as evidence of predictive capability. Purpose: Inventory of the news pipeline's event-leading groupings — whic
- `get_performance_metrics`: Purpose: Portfolio-level performance metrics (MDD / Sharpe / Sortino / Calmar / monthly returns / equity curve) over a FIXED window — the single canonical compu
- `get_position_detail`: Purpose: Per-symbol paper position deep-dive (position + recent trades + decisions). Triggers (casual questions too): "how's the BTC position doing?", "삼성전자 얼마나
- `get_positions`: Purpose: List current paper-trading positions, with dynamic filters (ROI / strategy / sort). Triggers (casual questions too): "what are you holding?", "current 
- `get_prediction_accuracy`: Purpose: Per-cell (category, target_market, lag_bucket) hit rates WITH the honest baselines (schema 1.1): persistence_accuracy (the null model — regimes are sti
- `get_profitable_positions`: Purpose: Profitable paper positions (ROI > 0). Convenience wrapper around get_positions(min_roi=0.01). Triggers (casual questions too): "what's winning right no
- `get_resolved_predictions`: Purpose: Raw, row-level prediction ledger — every macro regime prediction's full lifecycle (created_at -> resolved_at -> outcome). This is the auditable evidenc
- `get_role_analysis`: Purpose: Role-aware signal alignment per symbol (timing / trend / swing / regime) plus hierarchy alignment. Triggers (casual questions too): "is BTC bullish acr
- `get_sector_correlations_tool`: Purpose: Intra-market ETF / group correlation matrix and auto-cluster output. Quantifies structural co-movement (e.g. ARKK <-> QQQ) for diversification and sect
- `get_signal_calibration`: Purpose: Reliability diagram data for Level-1 signal confidence — realized hit rate per confidence bucket ([0.5,0.6) ... [0.9,1.0]) with ECE summary. Lets an ag
- `get_signal_detail`: Purpose: Per-symbol signal deep-dive — latest signal + history + feedback. Triggers (casual questions too): "why is BTC a buy?", "그 시그널 근거가 뭐야?", "signal histor
- `get_signals`: Purpose: Query signals with dynamic filters (symbol / interval / action / score / confidence). Triggers (casual questions too): "should I buy / sell X?", "살까 말까
- `get_strategy_distribution`: Purpose: Per-strategy breakdown across current paper positions (count, avg P&L, win rate per strategy). Triggers (casual questions too): "what strategies are yo
- `get_strategy_leaderboard`: Purpose: Top RL-learned research strategies — GLOBAL pool + per-symbol partition. Layer E evidence (Layer E = strategy-performance tier of the 5-layer trust pyr
- `get_structure_calibration`: Purpose: Level 2 (ETF / basket / sector granularity — Level 1 is individual symbols) prediction calibration. Returns hit_rate_ema per (market, group, interval, 
- `get_structure_validation_history`: Purpose: Daily validation history of Level 2 structure predictions (Level 2 = ETF / basket / sector granularity). Each row shows the hit_rate for a specific day
- `get_symbol_context`: Use when the question is about one stock or coin — its current signal state, the OneQAZ structure group it belongs to, and which assets have tracked lead-lag li
- `get_symbol_peer_links_tool`: Purpose: Symbol-level lead-lag links (e.g. META -> AMZN, lag=15m, rho=+0.53). When `symbol` is set, only peers that lead or follow that symbol are returned. Tri
- `get_trade_history`: Purpose: Query paper-trading history with dynamic filters (action / P&L / time / symbol). Triggers (casual questions too): "what trades happened lately?", "최근 거
- `get_trade_outcomes_bulk`: Purpose: Cursor-paginated bulk export of the prediction -> trade -> outcome chain — paper trades with realized P&L, each linked (best-effort, same-symbol 2h win
- `get_winning_trades`: Purpose: Winning paper trades only (P&L > 0). Convenience wrapper around get_trade_history(min_pnl=0.01). Triggers (casual questions too): "what worked?", "뭐가 제
- `search`: Purpose: ChatGPT-connector-standard discovery search over OneQAZ's live surface — tools, resources, and the latest score-ranked combined signals across crypto /

Measured by Glimind (https://glimind.com): MCP handshake + tool list only, no tool is ever called. CC BY 4.0.