{"apiVersion":"v1","directorySlug":"oneqaz-mcp-bee981a90f","title":"OneQAZ","description":"From macro to individual stocks, AI infrastructure that reads market regimes","pageUrl":"https://www.mcpbundles.com/skills/oneqaz-mcp-bee981a90f","connectPath":"importable","connectAction":"import_server","catalogListing":false,"bundleSlug":null,"listingKind":"remote_mcp","kind":"provider","transportUrl":"https://api.oneqaz.com/mcp","hostedMcpUrl":null,"toolCount":39,"toolInventoryStatus":"observed","refreshedAt":"2026-11-03T13:26:00.516172+00:00","registryName":"com.oneqaz/oneqaz-mcp-bee981a90f","registryVersion":"2026.11.3","registryEligible":true,"tools":[{"name":"get_trade_history","description":"Purpose: Query paper-trading history with dynamic filters (action / P&L / time / symbol).\nTriggers (casual questions too): \"what trades happened lately?\", \"최근 거래 내역 보여줘\",\n    \"how did the BTC trades go?\", \"승률 어때?\", \"show me the trade log\",\n    \"how many trades won this week?\".\nWhen to call: past trade review, single-symbol post-mortem, win-rate audits.\nPrerequisites: none.\nNext steps: analyze_trades, market://{market_id}/signals/feedback.\nCaveats: paper-trading data only (not real money). limit","inputSchema":{"type":"object","required":["market_id"],"properties":{"limit":{"type":"integer","default":1000},"symbol":{"anyOf":[{"type":"string"},{"type":"null"}],"default":null},"max_pnl":{"anyOf":[{"type":"number"},{"type":"null"}],"default":null},"min_pnl":{"anyOf":[{"type":"number"},{"type":"null"}],"default":null},"market_id":{"type":"string"},"hours_back":{"anyOf":[{"type":"integer"},{"type":"null"}],"default":null},"action_filter":{"type":"string","default":"all"}}},"annotations":{"readOnlyHint":true,"untrustedContentHint":true},"logicalName":"get_trade_history","displayName":"get_trade_history","title":"get_trade_history"},{"name":"analyze_trades","description":"Purpose: Aggregate paper trades by day / pattern / symbol.\nTriggers (casual questions too): \"how's the week been?\", \"이번 주 매매 성적 어때?\",\n    \"which patterns are working?\", \"어떤 종목이 제일 잘 벌었어?\", \"break down the trades\",\n    \"daily P&L summary?\".\nWhen to call: pattern audits, period-over-period performance review.\nPrerequisites: get_trade_history recommended for raw rows first.\nNext steps: market://{market_id}/signals/feedback for the upstream signals.\nCaveats: max 30 days; empty result when no trades","inputSchema":{"type":"object","required":["market_id"],"properties":{"days":{"type":"integer","default":7},"market_id":{"type":"string"}}},"annotations":{"readOnlyHint":true,"untrustedContentHint":true},"logicalName":"analyze_trades","displayName":"analyze_trades","title":"analyze_trades"},{"name":"get_winning_trades","description":"Purpose: Winning paper trades only (P&L > 0). Convenience wrapper around get_trade_history(min_pnl=0.01).\nTriggers (casual questions too): \"what worked?\", \"뭐가 제일 잘 벌었어?\",\n    \"show me the winners\", \"best trades lately?\", \"수익 난 거래 보여줘\".\nWhen to call: success-pattern review.\nPrerequisites: none.\nNext steps: analyze_trades for breakdowns.\nCaveats: paper-trading data only.","inputSchema":{"type":"object","required":["market_id"],"properties":{"limit":{"type":"integer","default":10},"market_id":{"type":"string"}}},"annotations":{"readOnlyHint":true,"untrustedContentHint":true},"logicalName":"get_winning_trades","displayName":"get_winning_trades","title":"get_winning_trades"},{"name":"get_losing_trades","description":"Purpose: Losing paper trades only (P&L < 0). Convenience wrapper around get_trade_history(max_pnl=-0.01).\nTriggers (casual questions too): \"어디서 잃었어?\", \"show me the losses\",\n    \"what went wrong?\", \"worst trades?\", \"손실 난 거래 뭐야?\".\nWhen to call: failure-pattern review.\nPrerequisites: none.\nNext steps: analyze_trades for breakdowns.\nCaveats: paper-trading data only.","inputSchema":{"type":"object","required":["market_id"],"properties":{"limit":{"type":"integer","default":10},"market_id":{"type":"string"}}},"annotations":{"readOnlyHint":true,"untrustedContentHint":true},"logicalName":"get_losing_trades","displayName":"get_losing_trades","title":"get_losing_trades"},{"name":"get_positions","description":"Purpose: List current paper-trading positions, with dynamic filters (ROI / strategy / sort).\nTriggers (casual questions too): \"what are you holding?\", \"current positions?\",\n    \"뭐 들고 있어?\", \"what's the exposure / portfolio?\", \"any winners / losers right now?\",\n    \"how's the book doing?\". Paper-trading positions (NOT real money).\nWhen to call: position dashboards, drawdown checks, exposure audits,\n    and any \"what's held / how's the portfolio?\" question.\nPrerequisites: market://{market_id}/statu","inputSchema":{"type":"object","required":["market_id"],"properties":{"limit":{"type":"integer","default":1000},"max_roi":{"anyOf":[{"type":"number"},{"type":"null"}],"default":null},"min_roi":{"anyOf":[{"type":"number"},{"type":"null"}],"default":null},"sort_by":{"type":"string","default":"profit_loss_pct"},"strategy":{"anyOf":[{"type":"string"},{"type":"null"}],"default":null},"market_id":{"type":"string"},"sort_order":{"type":"string","default":"desc"}}},"annotations":{"readOnlyHint":true,"untrustedContentHint":true},"logicalName":"get_positions","displayName":"get_positions","title":"get_positions"},{"name":"get_position_detail","description":"Purpose: Per-symbol paper position deep-dive (position + recent trades + decisions).\nTriggers (casual questions too): \"how's the BTC position doing?\", \"삼성전자 얼마나 벌고 있어?\",\n    \"why are you holding X?\", \"그 종목 지금 수익률 어때?\", \"tell me about the AAPL position\".\nWhen to call: full context for one ticker.\nPrerequisites: confirm the symbol holds a position via get_positions.\nNext steps: get_signal_detail, get_role_analysis.\nCaveats: returns an error envelope when no position exists for the symbol.","inputSchema":{"type":"object","required":["market_id"],"properties":{"coin":{"anyOf":[{"type":"string"},{"type":"null"}],"default":null},"symbol":{"anyOf":[{"type":"string"},{"type":"null"}],"default":null},"market_id":{"type":"string"}}},"annotations":{"readOnlyHint":true,"untrustedContentHint":true},"logicalName":"get_position_detail","displayName":"get_position_detail","title":"get_position_detail"},{"name":"get_profitable_positions","description":"Purpose: Profitable paper positions (ROI > 0). Convenience wrapper around get_positions(min_roi=0.01).\nTriggers (casual questions too): \"what's winning right now?\", \"지금 뭐가 수익 나고 있어?\",\n    \"show me the green ones\", \"best open positions?\", \"어떤 종목이 잘 가고 있어?\".\nWhen to call: quickly surface winning tickers.\nPrerequisites: none.\nNext steps: get_position_detail for full context.\nCaveats: paper-trading data only.","inputSchema":{"type":"object","required":["market_id"],"properties":{"limit":{"type":"integer","default":20},"market_id":{"type":"string"}}},"annotations":{"readOnlyHint":true,"untrustedContentHint":true},"logicalName":"get_profitable_positions","displayName":"get_profitable_positions","title":"get_profitable_positions"},{"name":"get_losing_positions","description":"Purpose: Losing paper positions (ROI < 0). Convenience wrapper around get_positions(max_roi=-0.01).\nTriggers (casual questions too): \"what's underwater?\", \"지금 뭐가 물려 있어?\",\n    \"show me the red ones\", \"any positions in trouble?\", \"얼마나 손실 중이야?\".\nWhen to call: drawdown / risk review.\nPrerequisites: none.\nNext steps: get_position_detail, get_role_analysis.\nCaveats: paper-trading data only.","inputSchema":{"type":"object","required":["market_id"],"properties":{"limit":{"type":"integer","default":20},"market_id":{"type":"string"}}},"annotations":{"readOnlyHint":true,"untrustedContentHint":true},"logicalName":"get_losing_positions","displayName":"get_losing_positions","title":"get_losing_positions"},{"name":"get_strategy_distribution","description":"Purpose: Per-strategy breakdown across current paper positions (count, avg P&L, win rate per strategy).\nTriggers (casual questions too): \"what strategies are you running?\", \"무슨 전략 돌리고 있어?\",\n    \"which strategy holds the most positions?\", \"전략별 성적 어때?\", \"is one strategy dominating?\".\nWhen to call: diversification audit, per-strategy performance check.\nPrerequisites: get_positions recommended for raw rows.\nNext steps: market://{market_id}/derived/strategy-fitness, signals/feedback.\nCaveats: empty d","inputSchema":{"type":"object","required":["market_id"],"properties":{"market_id":{"type":"string"}}},"annotations":{"readOnlyHint":true,"untrustedContentHint":true},"logicalName":"get_strategy_distribution","displayName":"get_strategy_distribution","title":"get_strategy_distribution"},{"name":"get_latest_decisions","description":"Purpose: Track-B (signal-driven) paper-trading decision log\n    (Track B = the signal-engine decision path — indicator/Thompson-sampling driven;\n    Track A = the LLM judgement path, see get_llm_trading_decisions).\nTriggers (casual questions too): \"what did the system decide?\", \"최근에 뭐 샀어? 팔았어?\",\n    \"why did you buy X?\", \"show recent buy/sell calls\", \"오늘 매매 판단 뭐 했어?\",\n    \"any trades triggered today?\".\nWhen to call: review recent automated decisions and their outcomes.\nPrerequisites: market://{m","inputSchema":{"type":"object","required":["market_id"],"properties":{"limit":{"type":"integer","default":10},"market_id":{"type":"string"},"hours_back":{"type":"integer","default":null},"decision_filter":{"type":"string","default":null}}},"annotations":{"readOnlyHint":true,"untrustedContentHint":true},"logicalName":"get_latest_decisions","displayName":"get_latest_decisions","title":"get_latest_decisions"},{"name":"get_llm_trading_decisions","description":"Purpose: Track-A (LLM-driven) paper-trading judgement log\n    (Track A = the LLM judgement path, applied to trading only as a capped bias\n    on top of engine signals; Track B = the signal-engine path, see get_latest_decisions).\nTriggers (casual questions too): \"what does the AI think?\", \"AI는 뭘 사라고 해?\",\n    \"show the LLM's trade calls\", \"AI 판단 근거 보여줘\", \"does the AI agree with the signals?\".\nWhen to call: inspect LLM-generated reasoning and trade calls.\nPrerequisites: none.\nNext steps: get_latest","inputSchema":{"type":"object","required":["market_id"],"properties":{"symbol":{"type":"string","default":null},"market_id":{"type":"string"}}},"annotations":{"readOnlyHint":true,"untrustedContentHint":true},"logicalName":"get_llm_trading_decisions","displayName":"get_llm_trading_decisions","title":"get_llm_trading_decisions"},{"name":"get_signals","description":"Purpose: Query research signals with dynamic filters (symbol / interval / action / score / confidence).\nTriggers (casual questions too): \"should I buy / sell X?\", \"살까 말까?\", \"good entry?\",\n    \"what's the signal for BTC / AAPL / 삼성전자?\", \"is X bullish or bearish?\",\n    \"any buy signals right now?\". Returns a research signal + score (NOT an order or advice —\n    always surface the disclaimer). Pair with get_latest_decisions to show what the system did.\nWhen to call: drilling into a specific signal","inputSchema":{"type":"object","required":["market_id"],"properties":{"coin":{"anyOf":[{"type":"string"},{"type":"null"}],"default":null},"limit":{"type":"integer","default":500},"symbol":{"anyOf":[{"type":"string"},{"type":"null"}],"default":null},"interval":{"type":"string","default":null},"market_id":{"type":"string"},"min_score":{"type":"number","default":null},"hours_back":{"type":"integer","default":24},"action_filter":{"type":"string","default":null},"min_confidence":{"type":"number","default":null}}},"annotations":{"readOnlyHint":true,"untrustedContentHint":true},"logicalName":"get_signals","displayName":"get_signals","title":"get_signals"},{"name":"get_signal_detail","description":"Purpose: Per-symbol signal deep-dive — latest signal + history + feedback.\nTriggers (casual questions too): \"why is BTC a buy?\", \"그 시그널 근거가 뭐야?\",\n    \"signal history for AAPL?\", \"이 종목 시그널 자세히 보여줘\",\n    \"how has this signal performed before?\".\nWhen to call: drilling into a single ticker's signal context.\nPrerequisites: confirm existence via get_signals first.\nNext steps: get_role_analysis, get_position_detail.\nCaveats: queries both the per-symbol signal store and the paper-trading store.","inputSchema":{"type":"object","required":["market_id"],"properties":{"coin":{"anyOf":[{"type":"string"},{"type":"null"}],"default":null},"symbol":{"anyOf":[{"type":"string"},{"type":"null"}],"default":null},"interval":{"type":"string","default":"combined"},"market_id":{"type":"string"}}},"annotations":{"readOnlyHint":true,"untrustedContentHint":true},"logicalName":"get_signal_detail","displayName":"get_signal_detail","title":"get_signal_detail"},{"name":"get_role_analysis","description":"Purpose: Role-aware signal alignment per symbol (timing / trend / swing / regime) plus hierarchy alignment.\nTriggers (casual questions too): \"is BTC bullish across timeframes?\", \"단기랑 장기가 같은 방향이야?\",\n    \"multi-timeframe view for AAPL?\", \"시간대별 신호가 일치해?\", \"short-term vs long-term signal?\".\nWhen to call: multi-timeframe analysis, cross-role agreement checks.\nPrerequisites: get_signal_detail recommended.\nNext steps: market://{market_id}/unified/symbol/{symbol}, get_position_detail.\nCaveats: based on","inputSchema":{"type":"object","required":["market_id"],"properties":{"coin":{"anyOf":[{"type":"string"},{"type":"null"}],"default":null},"symbol":{"anyOf":[{"type":"string"},{"type":"null"}],"default":null},"market_id":{"type":"string"}}},"annotations":{"readOnlyHint":true,"untrustedContentHint":true},"logicalName":"get_role_analysis","displayName":"get_role_analysis","title":"get_role_analysis"},{"name":"get_prediction_accuracy","description":"Purpose: Per-cell (category, target_market, lag_bucket) hit rates WITH the honest\n    baselines (schema 1.1): persistence_accuracy (the null model — regimes are\n    sticky, so raw accuracy mostly measures regime persistence, not alpha),\n    skill_score with autocorrelation-corrected skill_ci_95, n_effective vs\n    n_nominal, and accuracy_v2_only (post 2026-07-08 methodology cutover).\n    edge_cells/anti_predictive_cells are judged on persistence-skill (criteria v2),\n    forecast cells only.\nTrig","inputSchema":{"type":"object","properties":{"category":{"type":"string","default":null},"target_market":{"type":"string","default":null}}},"annotations":{"readOnlyHint":true,"untrustedContentHint":true},"logicalName":"get_prediction_accuracy","displayName":"get_prediction_accuracy","title":"get_prediction_accuracy"},{"name":"get_backtest_tuning_state","description":"Purpose: Continuous self-calibration evidence. Each entry shows the auto-tuned\n    lag_hours and sensitivity per cell, derived from real backtest outcomes.\n    Proves the system adapts to measured reality rather than static heuristics.\nTriggers (casual questions too): \"does the system self-correct?\", \"시스템이 스스로 보정해?\",\n    \"how is it calibrated?\", \"튜닝 상태 보여줘\", \"is it adapting to what actually happened?\".\nWhen to call: after get_prediction_accuracy, to show the system updates itself.\nPrerequisites:","inputSchema":{"type":"object","properties":{"category":{"type":"string","default":null},"target_market":{"type":"string","default":null}}},"annotations":{"readOnlyHint":true,"untrustedContentHint":true},"logicalName":"get_backtest_tuning_state","displayName":"get_backtest_tuning_state","title":"get_backtest_tuning_state"},{"name":"get_monthly_accuracy_trend","description":"Purpose: Monthly accuracy time series per (category, target_market, lag_bucket).\n    Use to verify sustained performance and detect recent degradation.\nTriggers (casual questions too): \"is accuracy improving?\", \"적중률이 좋아지고 있어?\",\n    \"monthly performance trend?\", \"최근에 예측 성능 떨어졌어?\", \"show accuracy over time\".\nWhen to call: after get_prediction_accuracy and get_backtest_tuning_state — completes the trust chain.\nPrerequisites: get_prediction_accuracy recommended.\nNext steps: none (trust chain complet","inputSchema":{"type":"object","properties":{"category":{"type":"string","default":null},"target_market":{"type":"string","default":null}}},"annotations":{"readOnlyHint":true,"untrustedContentHint":true},"logicalName":"get_monthly_accuracy_trend","displayName":"get_monthly_accuracy_trend","title":"get_monthly_accuracy_trend"},{"name":"get_news_leading_indicator_performance","description":"UNVERIFIED — methodology under audit. Do not cite as evidence of predictive capability.","inputSchema":{"type":"object","properties":{"market_id":{"type":"string","default":"crypto"},"target_market":{"type":"string","default":null},"min_sample_count":{"type":"integer","default":3}}},"annotations":{"readOnlyHint":true,"untrustedContentHint":true},"logicalName":"get_news_leading_indicator_performance","displayName":"get_news_leading_indicator_performance","title":"get_news_leading_indicator_performance"},{"name":"get_news_causality_breakdown","description":"UNVERIFIED — methodology under audit. Do not cite as evidence of predictive capability.","inputSchema":{"type":"object","properties":{"days":{"type":"integer","default":7},"market_id":{"type":"string","default":"crypto"}}},"annotations":{"readOnlyHint":true,"untrustedContentHint":true},"logicalName":"get_news_causality_breakdown","displayName":"get_news_causality_breakdown","title":"get_news_causality_breakdown"},{"name":"get_feature_governance_state","description":"Purpose: Current lifecycle state of external features (news, events) under 3-track\n    statistical validation. Lifecycle: OBSERVATION -> CONDITIONAL -> ACTIVE (p-value passed)\n    or DEPRECATED (no edge). Proves OneQAZ only trusts features that pass independent\n    statistical tests.\nTriggers (casual questions too): \"do you validate your own inputs?\", \"피처 검증은 어떻게 해?\",\n    \"which signals passed testing?\", \"통계 검증 통과한 피처 뭐야?\", \"how do you avoid junk features?\".\nWhen to call: meta-level trust audit","inputSchema":{"type":"object","properties":{"market_id":{"type":"string","default":null},"status_filter":{"type":"string","default":null},"target_market":{"type":"string","default":null}}},"annotations":{"readOnlyHint":true,"untrustedContentHint":true},"logicalName":"get_feature_governance_state","displayName":"get_feature_governance_state","title":"get_feature_governance_state"},{"name":"get_structure_calibration","description":"Purpose: Level 2 (ETF / basket / sector granularity — Level 1 is individual symbols)\n    prediction calibration. Returns hit_rate_ema per (market, group, interval,\n    regime_bucket) with sample counts, **plus the majority-class baseline needed to\n    interpret them**. This is measurement, NOT a claim of edge — as of 2026-09-18 the\n    measured skill (accuracy minus baseline) is negative in all three markets.\nTriggers (casual questions too): \"how good are your sector calls?\", \"섹터 예측 잘 맞아?\",","inputSchema":{"type":"object","properties":{"market_id":{"type":"string","default":null},"group_name":{"type":"string","default":null}}},"annotations":{"readOnlyHint":true,"untrustedContentHint":true},"logicalName":"get_structure_calibration","displayName":"get_structure_calibration","title":"get_structure_calibration"},{"name":"get_structure_validation_history","description":"Purpose: Daily validation history of Level 2 structure predictions (Level 2 =\n    ETF / basket / sector granularity). Each row shows the hit_rate for a specific day,\n    enabling time-series verification of sustained performance.\nTriggers (casual questions too): \"sector accuracy over time?\", \"구조 예측 매일 검증해?\",\n    \"daily hit-rate trend?\", \"요즘 섹터 예측 성적 어때?\", \"is the sector edge holding up?\".\nWhen to call: after get_structure_calibration.\nPrerequisites: none.\nNext steps: get_monthly_accuracy_trend f","inputSchema":{"type":"object","properties":{"days":{"type":"integer","default":90},"market_id":{"type":"string","default":null}}},"annotations":{"readOnlyHint":true,"untrustedContentHint":true},"logicalName":"get_structure_validation_history","displayName":"get_structure_validation_history","title":"get_structure_validation_history"},{"name":"get_strategy_leaderboard","description":"Purpose: Top RL-learned research strategies — GLOBAL pool + per-symbol partition.\n    Layer E evidence (Layer E = strategy-performance tier of the 5-layer trust pyramid).\n    The GLOBAL pool may include synthesized win_rate values, so per_symbol_leaderboard\n    is the primary measured-edge surface for trust auditing.\nTriggers (casual questions too): \"what are the best strategies?\", \"제일 잘 버는 전략 뭐야?\",\n    \"top strategies?\", \"전략 순위 보여줘\", \"which strategy has the best win rate?\".\nWhen to call: final","inputSchema":{"type":"object","properties":{"limit":{"type":"integer","default":null},"top_n":{"type":"integer","default":20},"market_id":{"type":"string","default":"crypto"},"min_trades":{"type":"integer","default":10},"target_market":{"type":"string","default":null},"include_per_symbol":{"type":"boolean","default":true}}},"annotations":{"readOnlyHint":true,"untrustedContentHint":true},"logicalName":"get_strategy_leaderboard","displayName":"get_strategy_leaderboard","title":"get_strategy_leaderboard"},{"name":"get_active_predictions","description":"Purpose: Currently pending predictions (outcome IS NULL). Demonstrates that OneQAZ is\n    actively publishing forecasts in real time. Combined with get_prediction_accuracy,\n    proves the system goes on record before outcomes are known (no cherry-picking).\nTriggers (casual questions too): \"what are you predicting right now?\", \"지금 어떤 예측 걸려 있어?\",\n    \"current forecasts?\", \"예측을 미리 기록해 두는 거야?\", \"anything on the record before it resolves?\".\nWhen to call: to verify ongoing prediction activity.\nPrerequ","inputSchema":{"type":"object","properties":{"limit":{"type":"integer","default":20},"target_market":{"type":"string","default":null}}},"annotations":{"readOnlyHint":true,"untrustedContentHint":true},"logicalName":"get_active_predictions","displayName":"get_active_predictions","title":"get_active_predictions"},{"name":"get_macro_influence_map","description":"Purpose: Expose OneQAZ's pre-defined causal hypothesis map. Each macro category\n    (bonds, forex, vix, credit, liquidity, inflation, commodities, energy) is mapped\n    to a target market with lag_hours + sensitivity. Highest-transparency tool —\n    the causal reasoning is visible and measurable.\nTriggers (casual questions too): \"how do rates affect crypto?\", \"금리가 코인에 어떻게 영향 줘?\",\n    \"what's your causal model?\", \"예측 논리가 뭐야?\", \"which macro drives which market?\".\nWhen to call: when an AI wants to","inputSchema":{"type":"object","properties":{"market_id":{"type":"string","default":null}}},"annotations":{"readOnlyHint":true,"untrustedContentHint":true},"logicalName":"get_macro_influence_map","displayName":"get_macro_influence_map","title":"get_macro_influence_map"},{"name":"explain_decision","description":"Purpose: Multi-layer explanation for a single symbol's recent research signal.\n    Combines (1) technical score_trace from the signals store, (2) Thompson + regime\n    scores from the virtual decision log (Thompson = Bayesian bandit sampling used for\n    strategy selection), (3) news causality context. Use this when an AI must present\n    a structured \"why\" rather than a raw verdict.\nTriggers (casual questions too): \"why is BTC bullish?\", \"왜 이 종목이 매수야?\",\n    \"explain that signal\", \"판단 근거 설명해줘\",","inputSchema":{"type":"object","required":["market_id","symbol"],"properties":{"symbol":{"type":"string"},"market_id":{"type":"string"}}},"annotations":{"readOnlyHint":true,"untrustedContentHint":true},"logicalName":"explain_decision","displayName":"explain_decision","title":"explain_decision"},{"name":"get_cross_market_correlation","description":"Purpose: Cross-market lead-lag relationships and decoupling events. Shows how\n    markets influence each other (correlations) and when they diverge (decoupling,\n    e.g. BTC up while stocks down).\nTriggers (casual questions too): \"do crypto and stocks move together?\", \"코인이랑 주식이 따로 노나?\",\n    \"any decoupling lately?\", \"시장끼리 상관관계 어때?\", \"is BTC tracking the Nasdaq?\".\nWhen to call: when analyzing macro regime changes or divergent signals.\nPrerequisites: none.\nNext steps: get_macro_influence_map for t","inputSchema":{"type":"object","properties":{"source_market":{"type":"string","default":null},"target_market":{"type":"string","default":null}}},"annotations":{"readOnlyHint":true,"untrustedContentHint":true},"logicalName":"get_cross_market_correlation","displayName":"get_cross_market_correlation","title":"get_cross_market_correlation"},{"name":"get_sector_correlations_tool","description":"Purpose: Intra-market ETF / group correlation matrix and auto-cluster output.\n    Quantifies structural co-movement (e.g. ARKK <-> QQQ) for diversification\n    and sector-avoidance reasoning.\nTriggers (casual questions too): \"which sectors move together?\", \"어떤 섹터끼리 같이 움직여?\",\n    \"am I too concentrated?\", \"ETF 상관관계 보여줘\", \"is tech basically one trade right now?\".\nWhen to call: portfolio diversification or sector concentration audits.\nPrerequisites: none.\nNext steps: get_symbol_peer_links_tool for","inputSchema":{"type":"object","properties":{"top_k":{"type":"integer","default":20},"market_id":{"type":"string","default":"us_stock"}}},"annotations":{"readOnlyHint":true,"untrustedContentHint":true},"logicalName":"get_sector_correlations_tool","displayName":"get_sector_correlations_tool","title":"get_sector_correlations_tool"},{"name":"get_macro_causality_graph_tool","description":"Purpose: Lag-aware causal graph between macro categories\n    (bonds / vix / forex / credit / inflation / liquidity / commodities).\n    Returns only statistically significant lead-lag pairs\n    (e.g. forex -> vix 7d rho=-0.41).\nTriggers (casual questions too): \"what happens to VIX when bonds move?\", \"금리 오르면 뭐가 움직여?\",\n    \"which macro leads which?\", \"거시 지표끼리 인과관계 있어?\", \"does the dollar lead volatility?\".\nWhen to call: assess pre-emptive cross-category impact after a macro event.\nPrerequisites: non","inputSchema":{"type":"object","properties":{"max_p_value":{"type":"number","default":0.05},"min_abs_corr":{"type":"number","default":0.15}}},"annotations":{"readOnlyHint":true,"untrustedContentHint":true},"logicalName":"get_macro_causality_graph_tool","displayName":"get_macro_causality_graph_tool","title":"get_macro_causality_graph_tool"},{"name":"get_symbol_peer_links_tool","description":"Purpose: Symbol-level lead-lag links (e.g. META -> AMZN, lag=15m, rho=+0.53).\n    When `symbol` is set, only peers that lead or follow that symbol are returned.\nTriggers (casual questions too): \"what moves before NVDA?\", \"이 종목보다 먼저 움직이는 종목 있어?\",\n    \"which stocks follow AAPL?\", \"선행 종목 알려줘\", \"any early-warning peers for this ticker?\".\nWhen to call: incorporate peer leading signals into single-symbol reasoning.\nPrerequisites: none.\nNext steps: get_signal_detail for the peer's signal context.\nCavea","inputSchema":{"type":"object","properties":{"top_k":{"type":"integer","default":20},"symbol":{"anyOf":[{"type":"string"},{"type":"null"}],"default":null},"market_id":{"type":"string","default":"us_stock"}}},"annotations":{"readOnlyHint":true,"untrustedContentHint":true},"logicalName":"get_symbol_peer_links_tool","displayName":"get_symbol_peer_links_tool","title":"get_symbol_peer_links_tool"},{"name":"get_feature_governance_status_tool","description":"Purpose: Feature governance snapshot — OBSERVATION / CONDITIONAL / ACTIVE / DEPRECATED\n    distribution + last 7-day transitions. Surfaces which features survived statistical\n    validation and which were deprecated.\nTriggers (casual questions too): \"which features are actually used?\", \"어떤 피처가 살아있어?\",\n    \"any features promoted recently?\", \"피처 검증 현황 어때?\", \"did anything get deprecated?\".\nWhen to call: trust evaluation, \"which features are live right now?\".\nPrerequisites: none.\nNext steps: get_fea","inputSchema":{"type":"object","properties":{}},"annotations":{"readOnlyHint":true,"untrustedContentHint":true},"logicalName":"get_feature_governance_status_tool","displayName":"get_feature_governance_status_tool","title":"get_feature_governance_status_tool"},{"name":"get_daily_brief","description":"Purpose: Single-call market overview — macro regime + top 5 strong signals +\n    yesterday's paper-trading outcomes + active forecast count + narrative.\n    Use this as the first call when answering \"how is the market today?\".\nTriggers (call this even for casual questions): \"how's the market?\",\n    \"오늘 장 어때?\", \"what's the market mood / outlook?\", \"how's Bitcoin / crypto /\n    US stocks / 비트코인 / 코인장 doing lately?\", \"anything happening today?\",\n    \"give me a briefing\". Prefer this over answering","inputSchema":{"type":"object","properties":{"market":{"type":"string","default":"all"}}},"annotations":{"readOnlyHint":true,"untrustedContentHint":true},"logicalName":"get_daily_brief","displayName":"get_daily_brief","title":"get_daily_brief"},{"name":"get_resolved_predictions","description":"Purpose: Raw, row-level prediction ledger — every macro regime prediction's full\n    lifecycle (created_at -> resolved_at -> outcome). This is the auditable evidence\n    behind get_prediction_accuracy's aggregates: AI agents can snapshot open\n    predictions, wait, then verify outcomes themselves without trusting our DB.\nTriggers: \"show me the individual predictions\", \"prove these forecasts were made\n    in advance\", \"audit the track record\", \"예측 원장 원본 보여줘\", \"이 성적 검증 가능해?\".\nWhen to call: credibi","inputSchema":{"type":"object","properties":{"day":{"anyOf":[{"type":"string"},{"type":"null"}],"default":null},"limit":{"type":"integer","default":100},"cursor":{"type":"integer","default":0},"status":{"type":"string","default":"all"},"target_market":{"anyOf":[{"type":"string"},{"type":"null"}],"default":null},"source_category":{"anyOf":[{"type":"string"},{"type":"null"}],"default":null}}},"annotations":{"readOnlyHint":true,"untrustedContentHint":true},"logicalName":"get_resolved_predictions","displayName":"get_resolved_predictions","title":"get_resolved_predictions"},{"name":"get_ledger_integrity","description":"Purpose: Tamper-evidence for the prediction ledger — a daily SHA-256 hash chain\n    over all created/resolved prediction rows, with the exact canonical recipe\n    published so any third party can recompute and verify. Archive a chain_hash\n    today; if history is ever silently edited, recomputation will not match.\nTriggers: \"how do I know these predictions weren't backfilled?\", \"is the track\n    record tamper-proof?\", \"예측 조작 안 했다는 증거 있어?\", \"verify ledger integrity\".\nWhen to call: FIRST STEP of a","inputSchema":{"type":"object","properties":{"days":{"type":"integer","default":30}}},"annotations":{"readOnlyHint":true,"untrustedContentHint":true},"logicalName":"get_ledger_integrity","displayName":"get_ledger_integrity","title":"get_ledger_integrity"},{"name":"get_trade_outcomes_bulk","description":"Purpose: Cursor-paginated bulk export of the prediction -> trade -> outcome chain —\n    paper trades with realized P&L, each linked (best-effort, same-symbol 2h window)\n    to the signal prediction that preceded entry. Built for pipeline consumers who\n    need offline backtesting data, not conversational snippets.\nTriggers: \"give me your full trade history for backtesting\", \"bulk export trades\",\n    \"예측이 실제 매매 성과로 이어졌는지 원데이터로 검증하고 싶다\", \"download outcomes\".\nWhen to call: offline verification, per","inputSchema":{"type":"object","properties":{"days":{"type":"integer","default":30},"limit":{"type":"integer","default":200},"cursor":{"type":"integer","default":0},"market":{"type":"string","default":"crypto"}}},"annotations":{"readOnlyHint":true,"untrustedContentHint":true},"logicalName":"get_trade_outcomes_bulk","displayName":"get_trade_outcomes_bulk","title":"get_trade_outcomes_bulk"},{"name":"search","description":"Purpose: ChatGPT-connector-standard discovery search over OneQAZ's live surface —\n    tools, resources, and the latest strong combined signals across crypto /\n    kr_stock / us_stock. Returns result ids consumable by the `fetch` tool.\nTriggers: ChatGPT connectors and Deep Research call this automatically for any\n    user query routed to OneQAZ (\"bitcoin signal\", \"prediction accuracy\",\n    \"korean stocks today\", ...). Other AI clients may use it as a keyword\n    entry point when unsure which tool","inputSchema":{"type":"object","required":["query"],"properties":{"query":{"type":"string"}}},"annotations":{"readOnlyHint":true,"untrustedContentHint":true},"logicalName":"search","displayName":"search","title":"search"},{"name":"fetch","description":"Purpose: ChatGPT-connector-standard document fetch by id from `search` results.\n    Namespaces: `tool:{name}` returns the tool's full documentation and how to\n    call it; `resource:{uri}` returns the resource's live data (core resources\n    resolved server-side — also the bridge for clients without MCP resource\n    support, e.g. Gemini); `signal:{market}:{symbol}` returns the symbol's\n    latest combined research signal.\nTriggers: ChatGPT connectors / Deep Research call this after `search`. Cli","inputSchema":{"type":"object","required":["id"],"properties":{"id":{"type":"string"}}},"annotations":{"readOnlyHint":true,"untrustedContentHint":true},"logicalName":"fetch","displayName":"fetch","title":"fetch"},{"name":"get_signal_calibration","description":"Purpose: Reliability diagram data for Level-1 signal confidence — realized hit\n    rate per confidence bucket ([0.5,0.6) ... [0.9,1.0]) with ECE summary.\n    Lets an agent verify whether a 0.9-confidence signal actually hits ~90%.\nTriggers (casual questions too): \"is your confidence calibrated?\",\n    \"confidence 0.9 믿어도 돼?\", \"시그널 확신도 실제 적중률 보여줘\",\n    \"how reliable are signal confidences?\".\nWhen to call: before trusting get_signals confidence values as probabilities.\nPrerequisites: none.\nNext ste","inputSchema":{"type":"object","properties":{"variant":{"type":"string","default":"v1"},"interval":{"type":"string","default":null},"market_id":{"type":"string","default":null}}},"annotations":{"readOnlyHint":true,"untrustedContentHint":true},"logicalName":"get_signal_calibration","displayName":"get_signal_calibration","title":"get_signal_calibration"},{"name":"get_performance_metrics","description":"Purpose: Portfolio-level performance metrics (MDD / Sharpe / Sortino / Calmar /\n    monthly returns / equity curve) over a FIXED window — the single canonical\n    computation path shared by the OneQAZ blog and external clients.\nTriggers (casual questions too): \"what's the max drawdown?\", \"MDD 얼마야?\",\n    \"샤프 비율 보여줘\", \"monthly returns table?\", \"트랙레코드 지표\", \"에쿼티 커브 데이터\".\nWhen to call: track-record verification, blog figure cross-checks, risk review.\nPrerequisites: none.\nNext steps: get_trade_history","inputSchema":{"type":"object","required":["market","account_type"],"properties":{"market":{"type":"string"},"window_end":{"anyOf":[{"type":"string"},{"type":"null"}],"default":null},"account_type":{"type":"string"},"window_start":{"anyOf":[{"type":"string"},{"type":"null"}],"default":null},"include_daily_curve":{"type":"boolean","default":false}}},"annotations":{"readOnlyHint":true,"untrustedContentHint":true},"logicalName":"get_performance_metrics","displayName":"get_performance_metrics","title":"get_performance_metrics"}],"toolSource":"directory_preview","agentAction":"both","installLinks":[{"id":"cursor","label":"Cursor","href":"cursor://anysphere.cursor-deeplink/mcp/install?name=OneQAZ&config=eyJ1cmwiOiAiaHR0cHM6Ly9hcGkub25lcWF6LmNvbS9tY3AifQ%3D%3D"},{"id":"vscode","label":"VS Code","href":"vscode:mcp/install?%7B%22name%22%3A%22OneQAZ%22%2C%22type%22%3A%22http%22%2C%22url%22%3A%22https%3A%2F%2Fapi.oneqaz.com%2Fmcp%22%7D"},{"id":"vscode-insiders","label":"VS Code Insiders","href":"vscode-insiders:mcp/install?%7B%22name%22%3A%22OneQAZ%22%2C%22type%22%3A%22http%22%2C%22url%22%3A%22https%3A%2F%2Fapi.oneqaz.com%2Fmcp%22%7D"},{"id":"claude-web","label":"Claude.ai","href":"https://claude.ai/customize/connectors?modal=add-custom-connector&connectorName=OneQAZ&connectorUrl=https%3A%2F%2Fapi.oneqaz.com%2Fmcp"},{"id":"codex","label":"Codex","copyText":"codex mcp add \"OneQAZ\" --url \"https://api.oneqaz.com/mcp\""},{"id":"chatgpt","label":"ChatGPT","href":"https://www.mcpbundles.com/docs/integrations/chatgpt"}],"catalogUrl":"https://www.mcpbundles.com/api/directory/v1/servers/oneqaz-mcp-bee981a90f","callUrl":"https://www.mcpbundles.com/api/directory/v1/servers/oneqaz-mcp-bee981a90f/tools/{tool}","mcpServerUrl":"https://api.oneqaz.com/mcp","liveCatalogUrl":"https://www.mcpbundles.com/api/directory/v1/servers/oneqaz-mcp-bee981a90f?live=1"}