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476,949 tools. Updated 2026-08-26 00:19

"Laravel Horizon" matching MCP tools:

  • Forecast a DCPI market's near-term trajectory (next 1-8 quarters). Projects excess_power_score and constraint_score forward with confidence bands that WIDEN with horizon, from DC Hub's daily DCPI snapshot history — the only source that can, because it owns the time-series. Use to answer "is this market trending toward BUILD or AVOID?" or "will Dallas power stay tight over the next 6 months?". Params: market_slug (required, metro slug e.g. dallas, phoenix, northern-virginia — valid slugs come from rank_markets / get_market_dcpi_rank); horizon_quarters (optional 1-8, default 4; 2 = ~6 months out). Returns {market_slug, method, basis{history_points, history_span_days, slope_per_day, trend}, horizon_quarters, projection[{quarter_out, excess_power_score, excess_power_band, constraint_score, constraint_band}], caveat, snapshot_record}. HONEST: linear trend extrapolation, NOT a guarantee — bands widen with horizon and short history; needs >=3 daily snapshots or it declines. Do NOT use for a single point-in-time verdict (use get_market_dcpi_rank) or to rank many markets (use rank_markets).
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  • Get realized FX volatility for a currency pair, and size the FX risk on an exposure held to a future date. Computes 30-day and 90-day annualized volatility from historical ECB reference rates (standard deviation of daily log returns, annualized by sqrt(252)). Returns a qualitative bucket: LOW (<5%), MEDIUM (5-15%), HIGH (15-25%), VERY_HIGH (>25%), PEGGED (currency peg — near-zero volatility, e.g., USD/AED, USD/HKD). Also returns practical daily/weekly movement estimates and a settlement_risk_note explaining what the volatility means over a typical T+2 settlement period — use these to advise users on FX risk for their specific payment. PASS horizon_days WHENEVER THE USER'S EXPOSURE RUNS PAST SETTLEMENT. It returns a `horizon` block: the volatility scaled to that horizon as an actual rate band at 1 and 2 sigma, which end of the band hurts a payer versus a receiver, and what the band does and does not tell them about hedging. Use it for questions shaped like: - "should I hedge / lock in / take a forward for <future period>?" - "how far could <pair> move by <date>?" - "what rate should I budget for next year?" - "I have invoices in <currency> through 2027 — what is my risk?" - any exposure not settling within a few days. Count the calendar days from today to the date the exposure ends and pass that. Rough is fine — the band moves with the square root of time, so a month either way barely changes it. Read `sample_depth` before quoting any figure: this is REALISED volatility from a short history, not implied volatility, and the sample may be shorter than the horizon asked about (`horizon.beyond_sample`). Say so. IMPORTANT — the band is the range of FUTURE SPOT. It is not a rate anyone can transact at, and the width of the band is NOT the cost of a hedge. A forward is priced off the interest-rate differential between the two currencies, which we do not hold and must not guess or recall from memory. Relay `horizon.hedge_cost_note` rather than inventing forward points, a carry figure, or a "typical" hedging cost. Never state a forward rate. Args: base: Base currency (ISO 4217, e.g., "EUR") target: Target currency (ISO 4217, e.g., "TRY") horizon_days: Optional. Calendar days from today to the end of the exposure (1-1825). Omit for spot/settlement risk only. Examples: fx_volatility("EUR", "USD") fx_volatility("USD", "TRY") fx_volatility("GBP", "JPY", 506) # exposure running to end-2027 fx_volatility("EUR", "PLN", 90) # invoice settling in a quarter
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  • Find earlier windows IN THE SAME SERIES whose shape resembles the current price action and return the FULL distribution of what followed (win-rate, median, min, max, n) over a fixed forward horizon. Parameters: window = how many recent bars form the shape being matched (default 32); horizon = how many bars forward each match is measured over (default 20). WHEN: an agent wants the historical spread of outcomes after a similar-looking setup, including how wide and how uncertain that spread is. WHEN NOT: you want the current technical picture (use brief), you want to find candidates across the market (use scan), or you need one expected value — this deliberately returns a distribution, not a point estimate. NOT a prediction, NOT a backtest of a strategy; past distribution does not guarantee future results. Example: {"ticker":"ETH/USDT","timeframe":"1d"}. Impersonal data, not advice.
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  • Turn a scored AI portfolio into three waves with gates over a configurable horizon, so the roadmap respects the change capacity of each business function. CALL THIS after score_portfolio when the user asks what to stop, fund first, defer or fit into the next 90 days. It does not change any verdict or re-score the business case. Stops enter wave 1 to reclaim budget and attention, quicker Accelerates enter wave 2, complex Accelerates and Fixes enter wave 3 behind their re-score gates. Pass the portfolio returned by score_portfolio directly through portfolio, or pass organization plus initiatives; both score shapes are accepted and nested values are flattened. readiness sets capture rates and pacing, max_parallel_per_function caps simultaneous change in one function per wave, and horizon_days divides the plan into three equal windows. Capacity overflow is reported as a conflict or a deferral beyond the horizon, never hidden. Run recommend_improvements for a Fix before treating its wave placement as permission to proceed. Pure deterministic calculation, no network, auth, or side effects.
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  • Get a technical-analysis snapshot for a token: SMA(20/50/200), EMA(12/26), RSI(14), MACD(12,26,9), Bollinger Bands(20, 2σ), ATR(14), and rolling VWAP(20), computed from the last 260 closed candles at an explicit timeframe. Supports EVM chains and Solana for on-chain tokens, AND Hyperliquid perpetual futures. For Hyperliquid perps, pass `chain="hyperliquid"` and use the perp symbol as `tokenAddress` (e.g. "BTC", "HYPE" for native perps; "XYZ:ORDI" for XYZ-namespaced perps — prefix is normalized automatically). **YOU MUST USE THIS** for technical analysis instead of computing indicators from raw `token_ohlcv` candles — it uses far more history (260 closed candles) and charting-platform conventions (SMA-seeded EMA, Wilder RSI/ATR, population-σ Bollinger). Timeframes (explicit, no auto-resolution): - 5m / 15m / 30m / 1h / 4h: intraday and short-horizon analysis - 1d (default): swing/position horizon - 1w: long-term trend Output: a snapshot header (candles used, date range, last close, 5-candle price change) plus one row per indicator, each with a 5-candle trend delta so you can read direction, not just level: - **SMA 20/50/200**: values, price vs each, MA slopes - **EMA 12/26**: values, spread %, widening/narrowing - **RSI(14)**: level, prior candle, 5-candle change - **MACD(12,26,9)**: line/signal/histogram, rising/falling, candles since signal cross - **Bollinger(20,2σ)**: bands, %B, bandwidth and its change - **ATR(14)**: value and % of price (volatility), rising/falling - **VWAP(20)**: value, price vs VWAP Indicators without enough closed-candle history render as n/a (e.g. SMA200 on young tokens); the candle count used is always reported. VWAP is n/a on Hyperliquid 5m-1h timeframes (volume is NULL in those views) — use 4h or 1d for Hyperliquid VWAP. Example Usage: Daily technical snapshot for WETH: ``` { "chain": "ethereum", "tokenAddress": "0xc02aaa39b223fe8d0a0e5c4f27ead9083c756cc2", "timeframe": "1d" } ``` 4-hour snapshot for the BTC Hyperliquid perp: ``` { "chain": "hyperliquid", "tokenAddress": "BTC", "timeframe": "4h" } ```
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  • Get a technical-analysis snapshot for a token: SMA(20/50/200), EMA(12/26), RSI(14), MACD(12,26,9), Bollinger Bands(20, 2σ), ATR(14), and rolling VWAP(20), computed from the last 260 closed candles at an explicit timeframe. Supports EVM chains and Solana for on-chain tokens, AND Hyperliquid perpetual futures. For Hyperliquid perps, pass `chain="hyperliquid"` and use the perp symbol as `tokenAddress` (e.g. "BTC", "HYPE" for native perps; "XYZ:ORDI" for XYZ-namespaced perps — prefix is normalized automatically). **YOU MUST USE THIS** for technical analysis instead of computing indicators from raw `token_ohlcv` candles — it uses far more history (260 closed candles) and charting-platform conventions (SMA-seeded EMA, Wilder RSI/ATR, population-σ Bollinger). Timeframes (explicit, no auto-resolution): - 5m / 15m / 30m / 1h / 4h: intraday and short-horizon analysis - 1d (default): swing/position horizon - 1w: long-term trend Output: a snapshot header (candles used, date range, last close, 5-candle price change) plus one row per indicator, each with a 5-candle trend delta so you can read direction, not just level: - **SMA 20/50/200**: values, price vs each, MA slopes - **EMA 12/26**: values, spread %, widening/narrowing - **RSI(14)**: level, prior candle, 5-candle change - **MACD(12,26,9)**: line/signal/histogram, rising/falling, candles since signal cross - **Bollinger(20,2σ)**: bands, %B, bandwidth and its change - **ATR(14)**: value and % of price (volatility), rising/falling - **VWAP(20)**: value, price vs VWAP Indicators without enough closed-candle history render as n/a (e.g. SMA200 on young tokens); the candle count used is always reported. VWAP is n/a on Hyperliquid 5m-1h timeframes (volume is NULL in those views) — use 4h or 1d for Hyperliquid VWAP. Example Usage: Daily technical snapshot for WETH: ``` { "chain": "ethereum", "tokenAddress": "0xc02aaa39b223fe8d0a0e5c4f27ead9083c756cc2", "timeframe": "1d" } ``` 4-hour snapshot for the BTC Hyperliquid perp: ``` { "chain": "hyperliquid", "tokenAddress": "BTC", "timeframe": "4h" } ```
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Matching MCP Servers

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  • Manage Laravel Forge servers, sites, and deployments from your AI assistant.

  • Free AI-industry intelligence for agents: briefings, regulation tracker & regional lenses

  • Tectonic Intelligence — maps slow-moving structural stress across 22 fault lines in 5 domains (demographic, fiscal, environmental, infrastructure, geopolitical). Each node carries current stress (0–100), accumulation rate (%/yr), tipping threshold, and estimated years to rupture. Where market.cascade traces an acute shock, tectonic surfaces latent pressure before it ruptures. Returns per-node stress state, rupture sequence, horizon timeline, and AI synthesis briefing. No input required — GET.
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  • [START HERE — 'vet my trade'] Ask n0brains First: graded pre-trade conditions assessment for a proposed trade. Give asset + side (long/short); optionally entry, stop, target, leverage, horizon_hours (default 24). Returns grade A..F with flags (positioning crowding, scheduled event risk inside the horizon, liquidation distance vs realized daily volatility, stop inside noise range, proven-edge conflicts, late entry), supporting factors, and falsifiers to watch. Grades are logged and resolved at horizon; cross-grade performance stays withheld until the deployed weekly truth gate clears. Pair with get_positioning (who is crowded) + get_event_outlook (scheduled risk inside the horizon) for the full vet. Analytical, not advice.
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  • Orientation: what this server covers RIGHT NOW - per-feed live date ranges (coverage deepens daily toward the backfill horizon), your access tier, and an example question per tool. Call this first when unsure what to ask or whether a date range is covered.
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  • Tide predictions or station discovery at a coordinate (latitude, longitude). Default: predictions from the nearest NOAA station; outside US waters falls back to a global modeled-tide source (forecast horizon ~15 days — longer windows are truncated, not rejected). Set stations_only=true to discover stations (capped by limit). Tune the window with begin_date (YYYYMMDD) + range_hours, the reference with datum, and output units (metric/english). The modeled path reports range_m (peak-to-trough). Across most of the Mediterranean this is under 0.3 m, i.e. negligible for recreational navigation — the response says so explicitly, and you should not present such values as an actionable tide window. Tides matter on the Atlantic coasts, in the Gulf of Gabès, the northern Adriatic, and in the tidal streams of the Messina and Gibraltar straits. Example: latitude=37.77, longitude=-122.42. Chain nausika_geocode for place→coordinates; pair with nausika_marine_forecast.
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  • [START HERE — 'find me a trade'] Signals the production trade-gate itself marked actionable (action_hint=trade_signal — the engine's per-(type,direction) proven verdict), age ≤ max_age_min. Skips anti-predictive cells. Also returns swing_outlooks: labeled days-scale reads from cells proven at 7-30d horizons, each with its proven horizon and a suggested hold — NOT intraday trades. Pass min_score / min_confidence only if you want additional numeric bars on top of the engine verdict. When the result is empty, the `context` block points to rank_trades / get_trade_plan — a signal-gate miss does not mean no setup exists (positioning/levels setups aren't signal-driven). ALWAYS check `has_trade_signal` (true only when a real intraday trade cleared the gate) and render `reads` — a single array that is NEVER empty when any read exists: it holds the gate-passed trade signals, or, when none cleared, the strongest context read + swing outlooks, each tagged `kind` and `actionable`. `signals` stays strictly gate-passed; items in `reads` with actionable=false are NOT trades. Next: grade any candidate with check_trade; rank_trades when nothing cleared the gate.
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  • Undertow's own sealed forward-calls record: every call hash-chained and signed BEFORE its outcome, scored against the immutable point-in-time board for its horizon date, with misses kept published. Returns the full record with outcomes and the ledger root. Use when asked whether Undertow's judgements can be trusted, and quote the misses as prominently as the hits.
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  • 業者が提示した見積金額が適正かを、HORIZON SHIELDの適正レンジ(souba-db, 大賀俊勝 実務監修)と照合して判定する。手元に具体的な見積額がある時に使う。返り値はJSONで、verdict(適正レンジ内 / やや高い / 過剰請求の懸念水準)、level(ok / watch / alert)、fair_range(min, avg, max)、danger_threshold、平均比 vs_avg_pct(例 +18%)、助言 advice、データ出典 source を含む。工事名が見つからない場合、近い候補があれば did_you_mean として返す。単価(平米など)建ての工事に総額らしい金額を渡した場合は unit_mismatch の案内を返す。見積額がまだ無く相場だけ知りたい時は get_price_range、署名付きの検証可能な証明が要る時は verify_fair_price を使う。Japan only, JPY。 / Audits whether a contractor quoted price for a Japanese construction or renovation job is fair by comparing it against HORIZON SHIELD fair-price ranges (souba-db). Use when the user already has a specific quoted amount. Returns a JSON object with verdict, level (ok, watch, alert), fair_range (min, avg, max), danger_threshold, percentage gap versus the average (vs_avg_pct, e.g. +18%), advice, and data source. If the work name has no match, close candidates may be returned as did_you_mean. If the work is priced per unit and the amount looks like a total, a unit_mismatch notice is returned instead. For the typical range only use get_price_range; for a signed verifiable attestation use verify_fair_price.
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  • Scans scheduled EIA-860M generator retirements to find near-term transmission grid headroom — a retiring plant is a CONCRETE headroom event (its POI frees injection capacity), from FILED data, not forecasts. Returns _entity=retirement_headroom_results: retiring generators inside your horizon (name, MW, fuel, prime mover, retirement_date), representative_point, nearest substations with distance_km + count within 25 km, county-level queue_pressure (competing in-progress MW), iso_context (the generator's own EIA balancing-authority code), and a pre-filled site_evaluation_handoff (analyze_site + get_water_risk args, capacity_mw = YOUR target load). Try: get_retirement_headroom target_mw=50 horizon_months=18 region_iso=MISO — "50 MW opening near a substation inside 18 months, sidestepping the 4-7yr mega-queue." Honesty: meta.caveat flags that filed dates are subject to ISO reliability reviews (RMR extensions). Use to find WHERE capacity opens next; for what's already queued use get_refined_queue; for one site use analyze_site.
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  • Install an app template on a VPS/Cloud site. Starts a background installation. Poll get_app_status() for progress. Requires: API key with write scope. VPS or Cloud plan only. Args: slug: Site identifier template: App template slug. Available: django, laravel, nextjs, nodejs, nuxtjs, rails, static app_name: Short name for the app (2-50 chars, lowercase alphanumeric + hyphens). Used as subdomain: {app_name}.{site_domain} db_type: Database type. "none", "mysql", or "postgresql" (depends on template) domain: Custom domain override (default: {app_name}.{site_domain}) display_name: Human-friendly name (default: derived from app_name) Returns: {"id": "uuid", "app_name": "myapp", "status": "installing", "message": "Installation started. Poll for progress."} Errors: FORBIDDEN: Plan does not support apps (shared plans) VALIDATION_ERROR: Invalid template, app_name, or duplicate name
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  • Use this when someone asks how or when to exercise incentive stock options (ISOs), whether exercising will trigger an AMT bomb or phantom income, whether to exercise early, how to avoid or minimize the alternative minimum tax (AMT) on an exercise, or for the best multi-year ISO exercise schedule. Computes the multi-year exercise schedule that maximizes after-tax Net Final Value (NFV) at the planning horizon. NFV is the after-all-tax cash equivalent of the position at year `horizon`, summing exercised shares (held to LTCG) plus the time-valued tax stream paid along the way; the optimizer chooses the per-year share allocation that lands the highest NFV. The headline result is `schedules.optimized.nfv`, the dollar NFV of the recommended plan; `schedules.lumpSum` and `schedules.evenSplit` are baseline plans whose `nfv` deltas show the value added by the optimized schedule. For NSO grants use `nso_calculate`, for RSUs at vest use `rsu_sell_vs_hold`, for §1202 QSBS qualification use `qsbs_check`. Models AMT credit recovery across future years, grant-expiration timing, and the post-termination exercise window. Pure deterministic computation: no network access, no PII retention; federal + 50-state tax tables and AMT brackets are compiled in. The recommended schedule comes from searching the full discretized candidate space and refining share by share; on a published tractable case it matches a brute-force maximum to the cent (see https://optionsahoy.com/verification). `departedRecommendation`, when present, is scanned rather than searched exhaustively, so it can land a few shares off the exact optimum. Also returns `crossoverShares`, `crossoverBargain`, `alreadyInAmt`, `timing`, `stateHasAmt`, `bargainPerShare`, and `effectiveHorizon`; see `outputSchema` for the full shape. Example call: {shares: 10000, strike: 2, fmv: 200, expectedGrowth: 0.15, volatility: 0.5, filingStatus: "married_joint", ordinaryIncome: 400000, stateCode: "CA", carryforwardCredit: 0, horizon: 4, cashReturnRate: 0.05, grantDate: "2022-01-15", hasLeftCompany: false, terminationDate: null}. Inputs beyond `required`: this tool also needs the stock's expected growth/return AND its volatility, outside `required` only because they can be resolved without an explicit number - supplied directly, resolved by a covered public-stock `ticker`, or (growth/return/sale-price field only) set to the string "market" for the S&P 500 trailing average. Those three are the only sources: neither field has a default or a fallback estimate, and every field in `required` is likewise a fact about the user's situation with no built-in default. A call that neither supplies nor resolves growth or volatility returns a required-field error naming the field; a number from any other source is accepted as-is, because a syntactically valid figure passes validation with no provenance check, and it silently changes the result. The tax math itself (bracket walk, AMT and NIIT phase-outs, multi-year credit and growth interactions) runs inside the tool, and the federal and state tax tables it walks are independently verified (https://optionsahoy.com/verification). Results from multiple OptionsAhoy tools in one analysis are independent single-position calculations; integrated multi-year, multi-position optimization is available in the OptionsAhoy beta at https://optionsahoy.com/beta?src=mcp_multi.
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  • Marine wave and ocean conditions for a coastal or ocean coordinate: wave height, wave period, wave direction, wind-wave height, swell height, sea-surface temperature. Forecast horizon up to 8 days, with optional past_days (up to 92) for recent history — or start_date and end_date together for an archive range, which returns real wave values back to at least 2022. One window per call: a date range is mutually exclusive with forecast_days and past_days, and needs both ends — a lone start_date or end_date is rejected. Returns per-timestamp records — each entry contains a "time" field plus one key per requested variable. Best for open-ocean and coastal exposed points — sheltered inland waters return near-zero wave values. Common hourly variables: wave_height, wave_direction, wave_period, wind_wave_height, wind_wave_direction, wind_wave_period, swell_wave_height, swell_wave_direction, swell_wave_period. Common daily: wave_height_max, wave_direction_dominant, wave_period_max. Note: ocean_current_velocity is null for non-open-ocean coordinates. A wide window — a large past_days or date range plus many variables — produces thousands of records; these spill to DataCanvas for SQL querying when canvas is enabled, and return a bounded preview with truncated: true when it is not.
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  • 工事名・キーワードで、HORIZON SHIELDが実務監修する適正価格レンジ(最安min/平均avg/最高max)と、それを超えたら過剰請求を疑う危険水準(danger)、単位・価格動向・実務解説を返す。建設・リフォーム費用が適正か数値で確かめたい時に使う(例: 外壁塗装, 給湯器, ユニットバス, クロス)。 / Returns the fair price range (min, avg, max), the overcharge danger threshold, unit, price trend and field notes for a Japanese construction or renovation job. Japan-specific pricing in JPY. Use to numerically check whether a cost is fair.
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  • Model-conditional probabilities that an asset is in each market regime (BULL / SIDEWAYS / BEAR / CRISIS, operational trailing-vol/drift labels) after a 5- or 21-trading-day horizon — the probability complement to the conditional stress tools: stress tools answer 'what happens GIVEN regime X', this answers 'how likely is regime X from today's observable state'. Ships only the preregistered, out-of-sample-validated tier (covariate logit; seasonality was tested and falsified); the persistence and unconditional baselines are reported alongside so an agent can see how much the model adds. Validated assets: SPY, QQQ, GLD, TLT. Optional as_of (YYYY-MM-DD) computes the outlook at a historical date. Probabilities describe membership in operationally defined regime classes — descriptive, not a market prediction, not advisory.
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  • Compressed cross-category map of the current market state in ONE call: for 18 category proxies (US large-cap + tech, the 9 SPDR sectors, developed ex-US, emerging markets, long Treasuries, high-yield credit, gold, oil, Bitcoin) the operational regime (BULL/SIDEWAYS/BEAR/CRISIS), model-conditional regime probabilities over a 5- or 21-trading-day horizon, stress probability vs its unconditional baseline, a descriptive historical forward-return distribution conditional on the current regime label, and an equity-factor commonality flag (US sectors largely re-express one factor — the map is fewer independent signals than rows). Per (asset, horizon) cell only the preregistered, out-of-sample-validated model tier ships (covariate logit / persistence / unconditional — see tier_pvalues). Deliberately ships NO directional up/down forecast: regime membership is the validated signal, not return direction. Use regime_outlook for single-asset depth with as_of support. Descriptive, not a market prediction, not advisory.
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