"Laravel Horizon" matching MCP tools:

• patternfetch_analogsA

  patternfetchA

  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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• kyrodata_get_hub_summaryA

  Kyrodata — Commodity Price Forecasts & Trade IntelligenceA

  Reads the Kyrodata pyramid verdict for a commodity hub: direction of the leading horizon, expected move in % per horizon (1, 3, 6 and 12 months), the 80% band as a half-width in percentage points, which levels drive the verdict and the measured accuracy. A horizon without an arrow names the reason, and an empty one means no level passed the confidence gate: no signal, not a stable price. `horizon` re-centres the verdict on the month given; omitted, it centres on the horizon the model leads with, and all four come back either way. It also carries the month-over-month and year-over-year % change of the reference price and its kind (doméstico, mundial or paridade de exportação), never the price level. This is the tool for where a hub's price is heading. The arithmetic behind the verdict is kyrodata_explain_pyramid_level, and the physical harvest of the same hub is kyrodata_get_climate_reading. Credit class: level (any level tool in a 60-second session = 2 credits; a session is capped at 3).

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• compare_day_lengthA

  Sunvane Golden HourA

  Use this when the user asks for day length differences and average change per day between two local dates, or the solstices and equinoxes of a year. Returns daylight duration for each date and signed changes. Limits: cities with population 50,000+ (plus Tromso), dates/years 1900–2100, flat sea-level horizon; use either date_a and date_b or year, and not both. Does not forecast weather.

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• market_regime_mapA

  crashtestyourstrategyA

  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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• clear_horizon_pinA

  KeelenA

  Clear a queued roadmap item's horizon pin (now/next/later → none). A horizon pin dominates the queue sort, so `reorder_roadmap` cannot move a pinned item out of its band — a stale `now` pin on a delivered/duplicate item clogs the front of the queue. This unpins it and reprices the queue so the item follows plain priority order again (and reorder_roadmap can then move it). Only queued items carry a settable pin (in-flight / shipped items derive theirs), so this refuses (422) on a non-queued item — a delivered item is closed with cancel_roadmap_item. Returns {id, previous_pin, horizon_pin, next_step}.

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• compare_payoff_vs_investA

  Senaro Personal FinanceA

  Calculation, not advice. Verify with a professional before acting. Compares the guaranteed return of debt payoff against expected investment returns over a time horizon. Accounts for post-payoff investing, optionally taxes the investment gain once at the horizon (this needs filing_status and annual_gross_income), and finds the break-even investment return rate. Works for credit cards, auto loans, student loans, personal loans, and mortgages. Pick this when the alternative to investing is paying down an existing debt balance; pick `calculate_opportunity_cost` when there is no debt in the picture and the alternative is simply forgoing recurring spending to invest it instead. The response echoes debt_type (canonical lowercase enum the projection was computed for) and debt_type_label (display-ready string, e.g. 'student loan') at the top level. HEAVY tool: use output='summary' (default) for the headline comparison or output='inline' for the full month-by-month schedule. When no projection can be computed (very long horizon, very high rate, or very large amounts), the response is { meta, not_representable: { code, explanation } } instead.

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• list_appsA

  PushNotif Official MCP ServerA

  List all registered websites and mobile apps in the workspace with active subscriber counts, current credit balance, and optional framework SDK installation snippets (when include_sdk_framework is set). Use this tool first as a prerequisite to obtain a valid app_id before calling send_push_notification, schedule_push_notification, update_app_branding, delete_app, configure_inapp_banner, or configure_rss_autopush; do not use it to inspect individual subscriber devices (use list_subscribers instead). Read-only operation requiring PUSHNOTIF_API_KEY with 0 credit cost; when include_sdk_framework is passed ('html', 'nextjs', 'laravel', 'wordpress', 'flutter'), each app entry also includes ready-to-paste SDK setup code. Returns JSON { tenant_name, credits_balance, total_apps, apps: [{ id, site_name, site_url, active_subscribers, sdk_guide }] }.

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• seo_generate_code_fixA

  mcp-seoA

  Generates framework-aware code fixes (Laravel Blade, Next.js App/Pages Router, HTML, PHP, Astro, Svelte) for missing titles, meta descriptions, canonical URLs, JSON-LD schemas, and WebMCP discovery links with unified diff preview. USAGE GUIDELINES: - Use after audit tools detect specific SEO, schema, or WebMCP issues in a source file. - Do NOT use for general code refactoring unrelated to metadata, schema, or SEO tags. - Always run 'seo_validate_code_fix' immediately after applying changes to verify syntax and prevent duplicate tags. BEHAVIORAL TRANSPARENCY: - Non-destructive by default: Returns unified diff preview without modifying files. - Modifies disk ONLY when 'applyDirectly' is explicitly set to true.

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• get_ml_signalA

  Crank ProtocolB

  ML ensemble directional forecast for a Solana asset (read-only). Trains the ported Bybit ensemble (XGBoost + RandomForest + NeuralNet + GradientBoost + a candle flow proxy) walk-forward on the last lookback_candles of OHLCV, then returns the blended P(up move) for the latest candle: score in [0,1], confidence (distance from 0.5), direction (long/short/neutral via buy_threshold/sell_threshold), per-model contributions and top feature importances. asset is a token mint; timeframe one of 1m/5m/15m/1h/4h/1d; horizon is the forward-return label horizon in candles. On spot, 'short' = exit-to-flat (no native short). Heuristic forecast from price history only -- not financial advice. No wallet, no fee, no on-chain action. Workflow: INTELLIGENCE step -- a directional forecast that complements detect_regime; low confidence -> cut size or stay flat. See get_trading_workflow.

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• jidec_how_to_verifyA

  JIDEC: Bitcoin-anchored public verification ledger (NENRIN)A

  Return the step-by-step recipe for verifying a JIDEC record WITHOUT trusting HORIZON SHIELD: which bytes to fetch, which hashes to recompute, which OpenTimestamps proof to check, which algorithm commit to check out, and what must match. Use this when you want to confirm the result yourself rather than repeat an assertion.

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• kyrodata_explain_pyramid_levelA

  Kyrodata — Commodity Price Forecasts & Trade IntelligenceA

  Explains the pyramid's arithmetic for one commodity and horizon: the seven levels side by side (label, push %, weight share, confidence, contribution %) and, for the levels that did not enter, the reason with its ruler (hit rate vs base rate, number of origins). `horizon` fixes the month and shows the seven levels; `levelKey` flips the cut, following one level across all four horizons instead. This is the drill-down of kyrodata_get_hub_summary — the 'por quê?' behind a verdict that tool already gave. A question about the physical harvest rather than the arithmetic belongs to kyrodata_get_climate_reading. Credit class: level (any level tool in a 60-second session = 2 credits; a session is capped at 3).

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• predict_market_trajectoryA

  DC HubA

  Use this when the user asks where a data center market's power outlook is heading (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, a time-series DC Hub owns. 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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• list_roadmapA

  OrgGen AIA

  Reads the ROADMAP of the project: the blocks that the governing roles have sorted into three horizons — Now (now), Next (next), Later (later) — in their order, with their milestone mark if any, plus the horizon suggestions PENDING a decision. ⚠️ It is a TEAM commitment set by a human, not a forecast: no horizon displays a date, and a block never sorted does not appear there (this is not an oversight, it simply has no horizon). Only blocks that still exist in the schema are returned. ⚠️ As long as the roadmap is not served on this project, the call SAYS so (`roadmap_unavailable`) instead of returning an empty roadmap: an empty roadmap and an absent roadmap are not the same thing. An agent READS the horizon; it does not set it — a change is proposed through `suggest_horizon`.

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• suggest_horizonA

  OrgGen AIA

  PROPOSES a horizon for a block: Now (now), Next (next) or Later (later), with a one-sentence reason (at most 140 characters). ⚠️ This tool SORTS NOTHING: it files a suggestion that the owner or a manager of the project will accept or refuse with one click on the site. The sorting itself is a human action — no tool sets it. The proposal is signed (it appears in the history of the block). Refused, without writing anything, if the block does not exist, if it is already in the proposed horizon, if the SAME proposal (this block, this horizon) is already awaiting a decision (`duplicate_suggestion`), if too many suggestions are already waiting (`suggestions_full`), or if agent writes are locked on this project. ⚠️ REAL idempotence, and bounded: replaying the same call (same block, same horizon, whatever the reason) is refused as a duplicate WHILE the first suggestion is PENDING; once decided (accepted or refused), you can propose again. ⚠️ As long as the roadmap is not served on this project, the call answers `roadmap_unavailable` and writes nothing. The current state is read with `list_roadmap`: a suggestion that repeats it brings nothing.

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• check_tradeA

  mcpA

  [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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• describe_coverageA

  insidergraphA

  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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• check_tradeA

  n0brainsA

  [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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• get_proofA

  mcpA

  [RECEIPTS] The full public forward-return proof board — richer than get_performance: per-signal-type measured post-signal performance with the proven-gate `tradeable` badges, plus the SWING boards. Args: asset_class (stock|index|metal|commodity|fx — same as get_asset_class_proof) OR horizon ('7d'|'14d'|'30d' for the swing-horizon boards, measurement-only, never badged tradeable). Omit both for the default 24h crypto board. Same data as REST /proof and n0brains.com/proof. Measured, not advice.

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• get_proofA

  n0brainsA

  [RECEIPTS] The full public forward-return proof board — richer than get_performance: per-signal-type measured post-signal performance with the proven-gate `tradeable` badges, plus the SWING boards. Args: asset_class (stock|index|metal|commodity|fx — same as get_asset_class_proof) OR horizon ('7d'|'14d'|'30d' for the swing-horizon boards, measurement-only, never badged tradeable). Omit both for the default 24h crypto board. Same data as REST /proof and n0brains.com/proof. Measured, not advice.

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• get_forecast_accuracyA

  Agent Einstein — Crypto & Market IntelligenceA

  The measured, out-of-sample accuracy of Einstein's own price forecasts — MAPE and direction hit-rate per model, asset and horizon, scored after each forecast's horizon elapsed. Hit rates are computed over INDEPENDENT trials (one forecast per non-overlapping horizon window), so they are comparable to a 50% coin flip. Use this to decide how much weight to give a forecast.

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• list_domainsA

  dMoERA CreatorB

  List all available trading domains on dMoERA. Domains define what asset pair a strategy trades, what time horizon it uses (scalp=5m, swing=1h, crisis=2m), and what data is available. Strategies must declare which domain they belong to. Returns a JSON array of domain objects with: key, name, type, base_asset, quote_asset, grading_seconds, and feed_symbols.

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