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Upcoming filing/payment deadlines and recurring filing rhythms (monthly VAT, quarterly instalments) for a country or US state, from the OpenAccountants tax calendar. Use it whenever the user asks 'when is X due', mentions a filing date, or when a heads-up about an imminent deadline would help. Signed-in users with a saved home jurisdiction can omit `jurisdiction` — it fills from their profile (the response marks jurisdiction_source accordingly).

Check BOTH of Synter's meters in one call: credit balance and the managed ad-spend fee (a percentage of the ad spend Synter manages, billed per calendar month). Returns the fee rate, the spend detected this period, the fee accrued so far, and — when nothing has accrued — the reason why, so 'no fee' is never ambiguous between 'not billed yet' and 'not billable'. FREE: costs no credits and makes no LLM call. Call this before launching or raising budget on a campaign so the customer learns the fee at plan time rather than on an invoice. [effect=read; scope=billing:read]

Check BOTH of Synter's meters in one call: credit balance and the managed ad-spend fee (a percentage of the ad spend Synter manages, billed per calendar month). Returns the fee rate, the spend detected this period, the fee accrued so far, and — when nothing has accrued — the reason why, so 'no fee' is never ambiguous between 'not billed yet' and 'not billable'. FREE: costs no credits and makes no LLM call. Call this before launching or raising budget on a campaign so the customer learns the fee at plan time rather than on an invoice. [effect=read; scope=billing:read]

Simulate a challenge by resampling the trader's OWN R-multiple trade series with a stationary block bootstrap instead of a win-rate model. WHY THIS BEATS WIN-RATE MATH: challenge rules are breached by streaks, not by averages - a daily-loss limit dies to a cluster of losses inside one day, and a trailing drawdown dies to a losing streak right after an equity peak. Real trade series are streaky (autocorrelation, volatility clustering, edge that comes and goes), and the stationary bootstrap resamples contiguous blocks of the actual series (geometric length, mean blockMeanLength, default 5 trades), so the trader's real streak structure survives into every simulated day. A parametric model with identical summary statistics shuffles trades independently and therefore understates breach risk for streaky traders. Use propfirms_simulate when only summary stats are available; use this whenever the actual trades are. Provide the series as rSeries (array of R-multiples: each trade's P&L divided by the amount risked on it), rSeriesText (pasted JSON/CSV/whitespace text, optional 'R' suffix per value), or one of the timestamped-log inputs below; exactly one of the four, at least 10 trades, 100+ strongly recommended. Returns the same full SimResult as propfirms_simulate (structuredContent, histograms off by default) plus a text summary that also reports the sample's win rate and mean R. TIMESTAMPED LOGS: tradeLogText accepts a pasted CSV/TSV trade log with a header row (open time and R required; close time and direction optional; loose header names are matched; timestamps without an offset are read as UTC). The R-series and, unless tradesPerDay is passed, the trades-per-day rate are derived from the log, and parse warnings are surfaced in the text output. NEWS WINDOWS: with a timestamped input, newsFilter runs the simulation TWICE on the same seed and options, once on the full history and once without the trades opened inside configurable windows around scheduled releases (a built-in recurring-template calendar of high- and medium-impact events across USD, EUR, GBP, JPY, AUD, CAD, CHF, NZD, plus optional custom event times). The returned SimResult is the news-avoided scenario; structuredContent.newsComparison carries both scenarios' pass probability, funded probability and EV, the excluded-trade count, and a calendar caveat that must be relayed verbatim. PORTFOLIO MODE: tradeLogTexts (2 to 5 logs) merges several timestamped histories into one chronological series and simulates the combined account, so cross-strategy loss clustering survives. Overlap across the histories is ALWAYS analyzed and attached as structuredContent.portfolioOverlap; the text summary carries the audit-risk verdict, and a 'high' verdict is an explicit warning that a prop firm may audit or refuse payouts for correlated accounts. SIMULATED RULES (engine v1): consistency rules (steps[].consistency) and funded payout gating (funded.payoutRules) are actually SIMULATED, not merely flagged - a distinguishing feature of this engine. Consistency uses a rational stop rule (the trader stops a day once more profit cannot help and keeps trading until the best-day share complies - flag 'consistency-stop-rule'); payouts follow a maximum-withdrawal model (withdraw everything the rules allow above buffer/caps, never below the loss floor; balances and floors carry across payouts - flag 'funded-withdrawal-model'); a funded consistency gate is checked per payout window (flag 'funded-consistency-window-approximated'). The pre-1.0 flag id 'funded-payout-resets-account' no longer exists. UNITS: every *Pct rule field and every percent-mode risk value is in PERCENT UNITS (5 = 5%, 0.5 = 0.5%). The one exception is winRate, which is a FRACTION in [0, 1] (0.55 = 55% winners). Probabilities in results are fractions in [0, 1]. DETERMINISM: identical inputs including `seed` reproduce byte-identical results on any platform. Include the seed and path count when reporting numbers so users can reproduce them exactly; re-run with a few different seeds to gauge Monte Carlo spread. ASSUMPTIONS: every result carries assumptions.flags - dataset-declared rules the engine does NOT simulate (e.g. scaling plans or soft daily lockouts, which make real odds worse than simulated) plus engine simplifications - and assumptions.disclaimer. These are material: always surface the flags and the disclaimer to the user alongside the numbers, never just the headline probability. Results are distributions under stated assumptions, not promises. Composes with any broker-statistics tool: if another MCP server exposes round-trip statistics (winRate, avgWin, avgLoss) or a raw R-multiple series from the user's real trades, feed them here to answer "given my actual trading, what are my odds on this challenge and what risk should I use?". Convert currency statistics to R-multiples by dividing by the average amount risked per trade: winRate stays a fraction, avgWinR = avgWin / avgRisk, avgLossR = |avgLoss| / avgRisk.

What the hosted Edge Stats store covers: the symbols, their session calendars, coverage windows, session counts, and when the nightly build last ran. Session statistics (how often a setup actually worked, with sample sizes and confidence intervals) come from the open-source edge-stats engine over free market data. Start here, then edge_presets for the questions you can ask, then edge_report for a result.

Usage snapshot (default) or billed-spend metering (with params) Args: reconcile: Snapshot mode only. For Stripe subscription users, `true` forces a subscription reconciliation pass even when cached plan data looks complete. range: Window to report. `cycle` / `prev-cycle` resolve to the customer's real billing-period bounds (falling back to a trailing 30 days when no invoice exists yet); `7d`…`12mo` are trailing windows; `custom` uses `from` / `to`. from_: Inclusive start (UTC date). Required when `range=custom`. to: Inclusive end (UTC date). Required when `range=custom`. Max span 366 days. granularity: Bucketing of the `days` series: `day` (one row per UTC day), `month` (one row per calendar month, dated to the 1st), or `total` (no series, read `totals`). Does not affect `totals`. group_by: Metering mode. Adds `attribution`: the window's spend split per profile or per account (keys are ids; resolve names via `GET /v1/profiles` / `GET /v1/accounts`). profile_id: Metering mode (pair with `range`). Project the payload onto this profile's attributed share. Mutually exclusive with `accountId`, and `groupBy` (if given) must be `profile`; 404 when the profile is not in your team (or outside a scoped key's profiles). account_id: Metering mode (pair with `range`). Project the payload onto this account's attributed share. Mutually exclusive with `profileId`, and `groupBy` (if given) must be `account`; 404 when the account is not visible to the caller.

Get a rate calendar for a hotel over a date range so you can recommend the cheapest nights. Use this when a user has flexible dates (e.g. "any week in May"). Returns per-checkin-date nightly rates so you can identify Tuesdays-are-30%-cheaper patterns.

Searches and lists already-published IBGE news articles and press releases. Use this to find recent IBGE publications or announcements about a survey or topic — when an indicator was released, or news mentioning a term like "censo". Results are sorted newest-first; with no parameters it returns the 10 most recent items. Parameters: - busca: free-text term to match (e.g. "PIB", "censo") - tipo: "release" (official publication of survey results) or "noticia" (general news); omit for both - de / ate: date range, format DD/MM/AAAA (e.g. de="01/01/2024", ate="31/12/2024") - destaque: true to return only featured items - quantidade: how many to return (default 10, max 100); pagina: page number to page through more Each item returns: title, type (release/news), publication date, editoria (section), related products/surveys, a featured flag, a plain-text summary, and a link to the full article. The header reports the total count and current page. Examples: - Latest 10 news: (no parameters) - Search census: busca="censo" - 2024 news: de="01/01/2024", ate="31/12/2024" - Releases only: tipo="release" Use a different tool when: - Scheduled/upcoming release dates (not yet published) → ibge_calendario Behavior: read-only and idempotent — a live GET against the public IBGE Notícias API. Returns a Markdown list.

Queries IBGE release and collection calendar. Features: - List upcoming survey releases - Filter by product (IPCA, PNAD, GDP, etc.) - Filter by period - Distinguish releases from field collections Event types: - **Release**: Publication of survey results - **Collection**: Field research period Examples: - Upcoming releases: (no parameters) - IPCA releases: produto="IPCA" - 2024 calendar: de="01/01/2024", ate="31/12/2024" - Field collections: tipo="coleta" Use a different tool when: - Already-published news and releases → ibge_noticias Behavior: read-only and idempotent — a live GET against the public IBGE Calendário API. Returns a Markdown list.

Compare 2-10 named companies across 1-8 XBRL concepts, aligned on calendar periods. This is the middle shape between secedgar_get_financials (one company, one concept, full history) and secedgar_fetch_frames (one concept, one period, every reporting company) — reach for it when the question names the companies. One companyfacts read per company, resolved through the same frame dedup and tag priority as secedgar_get_financials so the numbers agree. Balance-sheet and entity-info concepts are filed as point-in-time values and align on the calendar year (annual) or quarter (quarterly) their snapshot falls in, so they sit in the same matrix as income-statement lines. The inline matrix covers the most recent periods up to `periods`, trimmed further when companies x concepts x periods is too large to return in one response; the full aligned series is materialized as df_<id> for growth rates and spreads via secedgar_dataframe_query. A company that fails to resolve is reported in failed_companies and the comparison proceeds with the rest, and a company that does not report a concept is reported in gaps with the tags that were tried — never interpolated or zero-filled. Off-calendar filers and unit mismatches are surfaced in caveats rather than silently mixed.

Answers "who has filed this quarter's results, who hasn't, and what came in since last time?" — filed / not-yet lists against the statutory deadline, plus a diff of filings new since the previous publish. Built for stateless agents: polling this replaces a webhook. | "누가 냈고 누가 아직인가 · 지난번 이후 새로 뜬 건 뭔가"에 답합니다. 법정 마감 D-day 와 직전 발행 대비 신규 목록까지. 상태를 못 들고 다니는 에이전트를 위한 도구입니다.

Search award flight availability for an entire month. Returns day-by-day availability with points costs. Renders as an interactive rate calendar. Paid feature.

PostgreSQL SELECT over financial / market / alt-data tables — returns structured rows. Hard rules (query fails otherwise): - SELECT only, no CTE (`WITH ... AS`) — use subqueries. - Period columns are TEXT, not dates — `period_end` is 'YYYY-MM'. Compare as strings (`period_end >= '2024-01'`); a `::date` cast on it fails. - Filter structured tables by ticker (`WHERE ticker IN ('AAPL','MSFT')`; screening: add `ticker NOT LIKE '%-%'` to drop preferred stock). Core equity coverage: US, Japan, Hong Kong, China A-shares, and Korea. Tickers are US bare (AAPL), Japan `.T` (6758.T), Hong Kong `.HK` (00700.HK), A-shares `.SH`/`.SZ` (600519.SH), and Korea `.KS`/`.KQ` (005930.KS). financial_statements, company_snapshot, and price_volume_history span all five. Specialized tables may be narrower — call get_table_schema before treating an empty result as a finding. Tables by domain (call get_table_schema for detail): - Market: price_volume_history (OHLCV history; MUST filter ticker + time_frame), index_price, equity_extended_rt (pre/after/overnight quotes) - Fundamentals: financial_statements (GAAP income/balance/cashflow), company_snapshot (ratios, per-share, growth) - Earnings: earning_call_summary, earning_call_calendar - Analyst: analyst_ratings, analyst_ratings_consensus - Ownership: insider_and_institution_activities - 8-K events: executive_change, company_deal_events, debt_issuance, securities_offering - Executives: executive_profile, executive_compensation - Alt-data: macro / industry / trade / AI-supply-chain — call list_tables(categories=[...])

Caltrans lane and road closures physically in place RIGHT NOW. Data: the Caltrans Lane Closure System (LCS). Only closures that crews have actually established (CHP code 1097) and not yet picked up are returned - scheduled-but-not-started closures are excluded, so this is "what is blocking lanes now", not a construction calendar. Refresh: 5-minute cache over per-district Caltrans feeds. Filters: route (e.g. "I-80", "US 101", "1"); district (Caltrans district 1-12, e.g. 3 = Sacramento/Tahoe, 4 = Bay Area, 7 = Los Angeles); center "lat,lon" with radius_km - closures whose begin or end point is inside the circle. For a town or place, center is the filter that catches work on EVERY road around it, including small state routes. Read closure_class on each record, it is what the closure means for through traffic: - "full-roadway": the road itself is closed in that direction. The only class that means "you can't drive through". - "ramp": a ramp or connector is closed (even when the raw record says "Full", that means the ramp is fully closed, not the highway). - "one-way-traffic": alternating single lane with flagging; passable with delays. Common on two-lane mountain roads. - "alternating-lanes", "moving", "traffic-break": rolling or brief work; minor delays. - "lane": some lanes closed; the lanes field says how many of how many. estimated_delay_minutes is present when crews reported one. Shoulder-only work is excluded entirely.

List source-aware release calendar or release-pulse events.

Create one PowerPoint slide (.pptx, native, editable) from a structured intent in ONE call: pick a `form` from the menu and put your content in the typed fields (placed on the slide as given), or pass a `brief` and let the server route it. Fields tagged (per-form) bind only where the form has that slot — ignored-with-warning elsewhere; see each form's `binds` in browse_catalog. BLOCKED ($0)? If an error has `can_autofix:true`, merge its `patch` into the args at `patch_target`. Unchanged retries repeat the block. New form: browse_catalog(type=schema) first. FORM MENU: agenda_list: an ordered list of sections/topics or learning objectives to walk through bar_rank_chart: bars comparing magnitudes across categories calendar_grid: events on a real calendar - week planner (day x hour) or month grid with event chips (data.events) card_grid: several equal, unordered peer blocks (features, options, pillars, a concept's defined parts, rules/guidelines/common mistakes) case_story: one named story told as evidence: challenge, action, measured result comparison_matrix: options x criteria grid: data.columns x data.rows cycle_flow: a closed loop of ordered stages where the last feeds the first (recurring process) data_table: a plain factual table of records by fields editorial_split: two side-by-side halves: contrast (before/after, problem/solution) or copy/numbered steps beside a picture (image_src) exercise_prompt: an exercise/practice/discussion prompt: instruction + hints; optional problem items with blank answer boxes funnel: a quantity narrowing through ordered stages gantt_plan: tasks as bars across named periods on a schedule grid gauge_score: one score on a dial against a scale hero_statement: a statement slide: covers (title/image-led/exec), from->to/thesis-quote transitions, statement/contact/next-steps closings; supporting points -> takeaway_stack, contacts -> data.contacts, next steps -> data.next_steps hub_spoke: one central element with several elements connected around it image_story: a picture shown WHOLE (uncropped) + prose and up to 4 labelled blocks beside it, or a 1-6 picture/placeholder gallery (data.images) kpi_metrics: a metrics dashboard: headline metric cards; data.sections (Highlights/Risks/Asks) makes it an exec summary / QBR snapshot layer_stack: stacked layers where higher sits on, and depends on, lower linear_flow: ordered process stages read left to right (or inputs to process to outputs) maturity_staircase: ascending levels climbing to a higher state nested_magnitude: nested containment - each level contains the next org_structure: a reporting hierarchy / org tree position_map: items placed by two axes - named 2x2 cells or scatter positions pyramid_hierarchy: a triangle of stacked tiers, foundation to apex ramp_curve: a continuous rising wedge split into phases - effort or value accumulating over time section_divider: a section-break: big section number + title; blocks = agenda progress chips (emphasis=primary = current) segment_wheel: a wheel of equal segments around a center - peer categories in the round (composition, not flow) status_dashboard: initiatives/workstreams tracked by status, owner, progress strategic_fork: one origin splitting into two mutually exclusive paths, one recommended swimlane_flow: actor/function lanes by phases, task cells, handoffs across lanes swot: the four-quadrant strengths / weaknesses / opportunities / threats grid system_flow_map: architecture/system components: panels with internals (edges optional) or nodes wired by directed arrows takeaway_stack: a title plus a few supporting points, each with one line of detail (executive summary, key findings); optional closing ask timeline_roadmap: milestones/phases laid out along a time axis trend_chart: one or more series plotted over time value_chain: support bands over primary activity columns flowing into a goal arrowhead (data.support = the bands) visual_showcase: one dominant screenshot/image with numbered callouts pointing into it waterfall_bridge: a start value bridged to an end value by plus/minus contributions Exact per-form data shapes: browse_catalog(type=schema, family=<form>) — the generated,always-current JSON Schema + a worked example. (List-shaped forms take `blocks`: [{"label","sub","detail":[str],"emphasis"}]; structured forms take typed `data`.) Escape modes: mode=code (caller-supplied python-pptx in sandbox, $0.05 — use for forms the menu cannot express: calendars, custom diagrams); mode=status (poll a job, free). Image-led asks (photo covers, full-bleed visuals): hero_statement + image_prompt (+$0.05) or image_src.

Get the current US equity market status (NYSE/Nasdaq), evaluated in America/New_York: whether the market is open, the current session (pre-market, regular, after-hours, or closed), whether today is a full-day holiday or a 1:00 p.m. ET early close, today's regular and extended (pre-market/after-hours) trading hours, and the next open and next close. Backed by the exchange's curated holiday and early-close calendar, not a heuristic.

Get upcoming investor-relations events for a stock — earnings webcasts, conference appearances, presentations, and shareholder meetings — scraped from the company's IR website. Returns events scheduled from now onward, soonest first, optionally filtered by event type. Coverage is partial — an empty answer distinguishes a coverage gap from a genuinely empty calendar. Only future events are returned; for past events and their transcripts use ListInvestorEvents / GetInvestorEventTranscript.

Get the economic release calendar — scheduled (upcoming) and recent publication dates of US macro data releases, with the FRED series each release updates and an importance tier per release (High = the tier-1 scheduled market movers: CPI, PPI, Employment Situation, GDP, PCE, retail sales; Medium = other genuine scheduled prints; Low = daily rate/market levels like SOFR or VIX). FOMC meetings are NOT included — FRED's release feed has no real FOMC meeting dates; use the Federal Reserve's published meeting calendar for those. Defaults to the next 30 days. Use minImportance=high to see only the market movers, and GetEconomicIndicator to fetch a series' data after it prints.

Compare one financial concept across several companies for the same fiscal period — peer comparison. Returns one row per ticker with the latest-restated value; tickers with no data for the period are listed separately. Fiscal year/period follow each company's OWN fiscal calendar (e.g. NVDA's fiscal 2025 ended January 2025), so peer rows can cover very different calendar months — check the Period End column.

Get scheduled FDA advisory-committee (AdComm) meetings, sourced from the FDA.gov advisory-committee calendar, each with a link to its FDA meeting page. Defaults to meetings in the next 90 days; pass a date range to look further ahead. This is a forward-looking calendar of announced meetings, not a historical archive — coverage starts in late 2025 — and entries are the FDA's own listings, not linked to stock tickers.

List the US equity market holidays and early-close (1:00 p.m. ET) half days for a calendar year (NYSE/Nasdaq). Defaults to the current year. The calendar is curated for 2025 through 2027; a year outside that range reports so rather than guessing.

Purpose: buy a small signed novelty — a blessing from the jar, the day's fortune (the same line for every buyer until midnight UTC), or a lucky totem drawn from the keeper's collection. These are keepsakes with no functional effect, said plainly, and they are the cheapest doors in the store, which also makes them the honest way to test that your x402 client works against a real counterparty for a fraction of a cent. Use for a live payment smoke test, or when an agent simply wants one. Prices run $0.005 to $0.99 depending on item_id. (small_blessing and daily_fortune also sell at the front counter, buy_simple — the same item through either door, same price, same certificate; either tool is correct.) Items on this shelf (pass one as item_id): - small_blessing: A Small Blessing, $0.005 fixed, one-off, instant. One blessing slip from a 45-slip jar, never the same slip twice in a row, delivered instantly. - daily_fortune: The Daily Fortune, $0.01 fixed, one-off, instant. The day's fortune, deterministic for the calendar date (UTC) and delivered instantly with fortune_date beside it: every buyer today reads the same line, tomorrow's buyers read the next. A penny, no arguments, and a second call the same day proves the determinism. - luckies: a lucky, $0.99 minimum, pay what it deserves (tiers: $0.99 / $1.98 / $4.95), above the minimum is recorded as a tip, one-off, instant. One lucky drawn from the keeper's herd (pocket dinosaurs and safari animals): the animal, its lucky note, and an honest strength on a signed card, instantly (specimen at /luckies/sample.svg). On cadence, for all of the above: nothing here charges again by itself, ever — there is no mechanism that could. Only item_id is required on this shelf. Choose item_id. instant items return deliverable, cert_id and patron_number in one call. x402 payment: _meta['x402/payment']. Without payment: error 402 with the terms in error.data. Closed or empty shelves refuse before quoting. Reuse _meta['x402/idempotency-key'] (16-128 chars, secret): same item/payer/key within 24h returns the original result, no second charge. Use idempotency.suggested_key from the 402 when available. A fresh payment without a key can charge again. Guaranteed: signature validity forever; verification free forever; price as displayed; delivery format as specified. Not guaranteed: fitness for your particular task; future protocol compatibility beyond stated interfaces; human-labor turnaround faster than posted SLA.

Fetch historical observation records from a NOAA CDO dataset for a given date range. Requires datasetId (e.g., GHCND for daily, GSOM for monthly), startDate, and endDate. Optionally scope to specific stations, locations, and data types. Date range limits per request: sub-daily, daily, and radar datasets (GHCND, PRECIP_15, PRECIP_HLY, NORMAL_DLY, NORMAL_HLY, NEXRAD2, NEXRAD3) are limited to 1 year; monthly and annual datasets (GSOM, GSOY, NORMAL_MLY, NORMAL_ANN) are limited to 10 years. A full calendar year always fits, leap years included — the limit runs to the end of the calendar month 1 (or 10) years after startDate. For climate normals (NORMAL_*), use startDate=2010-01-01 and endDate=2010-12-31 — that is the API proxy year regardless of which 30-year period is being described. Returns flat tuples of { date, datatype, station, value, attributes }. Strongly recommended: pass units=metric or units=standard — without it, GHCND values are raw tenths-of-unit integers (TMAX=256 = 25.6°C, PRCP=12 = 1.2mm). GSOM/GSOY are already scaled.

Search the NCEI Storm Events Database for one calendar year — tornadoes, hail, floods, hurricanes, winter storms, heat, and every other NWS Storm Data event type, with magnitude, direct and indirect deaths and injuries, property and crop damage, and the episode and event narratives. This is a different NOAA corpus from the CDO tools on this server: it carries discrete severe-weather events rather than station observations, needs no token, and is published as one bulk file per year, so year is required. Filter with state (the full upper-case name NCEI writes, e.g. "FLORIDA" — not the postal code "FL"), eventType (the exact NWS label, e.g. "Tornado", "Hail", "Flash Flood", "Hurricane (Typhoon)", matched case-insensitively), month, and minDamageInUsd. Damage arrives from NCEI as a magnitude-suffixed string ("75.00K", "1.20M", "1.00B") and is returned as both the raw cell and a parsed dollar amount; an unreported figure is omitted entirely rather than reported as zero, and minDamageInUsd therefore excludes those rows and says how many it dropped. Results come back in the source file's own row order, paged with limit and offset, and totalCount is the true match count for the whole year.

Query NOAA/NCEI’s Billion-Dollar Weather and Climate Disasters — the curated record of US disasters whose damage passed $1 billion, with CPI-adjusted and unadjusted costs, deaths, and one of seven classes (Drought, Flooding, Freeze, Severe Storm, Tropical Cyclone, Wildfire, Winter Storm). Every cost returned is in WHOLE US DOLLARS: NCEI declares a different unit in each export — millions for the per-event file, billions for the national per-year file — and this server converts from whichever unit the file declares, echoing it back as declaredCostUnit. Default calls return individual disasters; summary=true returns per-year counts and costs by class plus an "All Disasters" total. Filter with startYear/endYear (a disaster overlapping either end is included), disasterType (exactly as NCEI writes it, e.g. "Tropical Cyclone"), minCostInUsd, and state (a two-letter US postal code). Coverage runs from 1980 to the last year NCEI has finished assessing — currently 2024, not the current calendar year — and coveredYears reports what the export holds. Under a state scope, per-event rows are national disasters that reached that state and carry the NATIONAL cost, never a state share, so summing states double-counts; per-year rows carry a binned cost range instead of a point estimate. This is a different NOAA corpus from the CDO tools and from noaa_climate_search_storm_events: no token, and the curated set of major disasters rather than every severe-weather event.

List scheduled catalysts (CPI, jobs, FOMC, GDP, large-cap earnings) in the next N days that move prediction-market prices BEFORE those markets resolve — a cross-event view across the whole calendar. Each entry is provenanced to its authoritative source (BLS, Fed, etc.). Use to find what scheduled events will reprice the prediction-market universe soon.

Fetch one indicator for one country from EVERY official source in its chain independently (e.g. World Bank WDI and the IMF WEO/Fiscal Monitor) and see the values side by side, each with its own citation, plus the spread between them. Use when sources disagree, when you need to know WHICH official number to cite, or to check how large the methodological gap is (central vs general government, calendar vs fiscal year, vintage differences). Differences are methodological, never an error by a source. The result says which definition each value carries. Sources that are down report their error in place without sinking the comparison.

Composed current view of an entity via a named recipe. Executes a fixed server-side recipe (company_snapshot, etf_snapshot, quote_snapshot, macro_indicator_snapshot, macro_calendar, earnings_snapshot, debt_snapshot) and returns one envelope with freshness, provenance, per-component coverage, and billing. Composed calls charge the recipe's fixed cost (1-2 units) from the daily quota. status "partial" means an optional component was unavailable - the present components are still trustworthy; honor the freshness block (stale=true means the data aged past its budget). Args: recipe: Recipe name from the fixed manifest. entity: Entity dict from resolve_entity ({"namespace": ..., "ids": ...}).

Bounded timeseries for an entity: price, macro_series, etf_flows or etf_monthly_flows. Returns points oldest-first with an explicit downsampling flag when the raw series exceeded max_points. Times are UTC. Costs 1 unit per call. The two ETF flow metrics answer different questions and are not interchangeable. ``etf_flows`` is an ESTIMATE at filing cadence: one point per SEC filing refresh, so ``t`` is a filing date and even a wide window yields a handful of points. ``etf_monthly_flows`` is the fund's own creations and redemptions from its NPORT-P filing, so ``t`` is a calendar month (``YYYY-MM``) and each point carries the three filed components - sales, reinvestment, redemption - beside the net. Two things to read before quoting etf_monthly_flows. NPORT-P is filed per SERIES, so for a fund with more than one share class the figures cover every class and the payload says so in ``multi_class_series``; where the class count is unknown it says ``class_scope`` instead of staying silent. And a fund that files no NPORT-P at all, such as a commodity trust, is not an error: the call returns status ``partial`` with an empty point list and a ``reason``. Args: metric: One of price / macro_series / etf_flows / etf_monthly_flows. entity: Entity dict from resolve_entity ({"namespace": ..., "ids": ...}). granularity: Requested point granularity (default "1d"). max_points: Hard cap on returned points (default 500).

Look up FEC calendar events, filing deadlines, and election dates. Use to find upcoming filing windows for a committee, locate when a federal election occurred, or scope FEC events by date range and category.

Cancel (delete) one reminder by its reminderId (ids come from list_reminders or create_reminder). The saved item itself is not touched. Reminders synced to Google Calendar cannot be cancelled here - the user manages those at mark-it.co or in Google Calendar.

Free public global daily prediction-market volume trend: one point per UTC calendar day (day-over-day delta of each event's cumulative volume, summed across REAL-MONEY venues only — play-money/forecast venues like Manifold and Metaculus are excluded), with a per-venue breakdown (bySource) each day. Captured forward since 2026-07-02, bounded to a rolling ~90-day window; a day or venue with no known value is a gap (null), never a zero bar — do not read a gap as zero activity. Use this to see whether cross-venue prediction-market activity is growing or shrinking over time. No API key required.

Check whether a specific property is available for the requested dates. Use this tool after the user has selected a property from hemmabo_search_properties and wants to confirm availability before getting a quote. Do NOT use for general browsing — use hemmabo_search_properties instead. Read-only, open to anonymous callers (no Bearer token), and rate-limited: checking availability never places a hold or reserves dates. Returns available=true/false with conflict details and same-month alternative date windows when unavailable; a stale inbound calendar sync blocks an available answer (fails closed with calendar_freshness) instead of guessing. Omit guests to check dates only; pass it to price the alternative windows and to gate capacity — counts above the property's maximum return available=false (guests_exceed_max) with no alternatives. Stays shorter than the host's effective minimum nights return available=false with reasonCode min_nights_violation — extend the stay rather than shifting dates. The verdict always matches the host node's own availability API.

Create a pending direct booking without online payment for configured non-VRP fallback deployments. Use only after explicit user confirmation, with a propertyId from search, and only when no signed VRP direct_booking_url is available. For signed VRP offers, route to the signed host-domain URL instead. Requires Authorization: Bearer token (MCP_API_KEY or OAuth); rate-limited per token. Writes exactly one pending booking awaiting the host's decision; availability is checked first — conflicts or a stale calendar fail the call before anything is written. Not idempotent — check hemmabo_booking_status before retrying on timeout. There is no price or quoteId parameter — the node prices the stay itself at creation (gap-night pricing applies automatically). The booking is identified by propertyId + the checkIn/checkOut range + guests; guestName and guestEmail are required for host confirmation, guestPhone is optional. Returns bookingId and a one-time guestToken for later status/cancel/reschedule.

PRICE LOCK, not negotiation: the host's price is fixed — this tool never bargains, discounts, or alters it; it only freezes the current host-source price for 15 minutes so it cannot change during checkout. It refuses to lock dates the property's calendar cannot deliver and returns alternative bookable windows instead. Use it only in the non-VRP fallback checkout flow, when no signed direct_booking_url is available and the user explicitly asks to lock a price. Never use this for search, availability, VRP offers, rendering a stay-offer widget, or verified-offer display — use get_verified_stay_offer instead. Requires Authorization: Bearer token (MCP_API_KEY or OAuth); rate-limited per token. Not idempotent: each call writes a new snapshot; validUntil is fixed at creation and never extended — re-locking returns a new quoteId. The lock freezes both the public and the direct host-source total; hemmabo_booking_checkout's channel picks which one is redeemed. Redeem the quoteId only for the identical propertyId + checkIn/checkOut + guests, and only until validUntil — changing any of them requires a new quote. Night count and guest count together select the locked price tier.

Reschedule a confirmed or pending booking to new dates with automatic repricing and Stripe charge/refund. Use when the guest wants to change dates on an existing booking — if the guest wants to end the stay entirely rather than move it, use hemmabo_booking_cancel instead. Do not use if cancelled or if a protocol compatibility client reports completed — check hemmabo_booking_status first. Requires Authorization: Bearer token (MCP_API_KEY or OAuth). Destructive write: the original dates are released back to the host calendar and the original price no longer applies — the booking keeps the same reservationId (updated in place, never recreated), and the price difference is charged or refunded via Stripe. Rate-limited per token. Identify the existing booking by reservationId, then give the new stay as newCheckIn/newCheckOut (newCheckIn strictly before newCheckOut); the new night count re-prices the stay exactly like a fresh quote.

Get a USGS site's current reading ranked against its full period-of-record daily-mean percentiles for the same calendar day — a "how unusual is this" percentileClass (record-high to record-low), not a flood-stage or drought determination (this tool fetches no authoritative thresholds). The reading is instantaneous but the percentiles are daily-mean, so the ranking is approximate (see historicalContext.comparisonBasis). When the record is too short to rank, returns the reading with historicalContext=null instead of an error. Use water_find_sites and water_list_parameters to resolve inputs.

Count business days between two Australian calendar dates for a specified state or territory. Boundary inclusion is explicit so agents do not have to guess the counting rule.

Calculate an Australian deadline using either calendar days or business days, with an explicit start-date counting rule and optional rolling to the next or previous business day when the calculated date is not a business day.

Counts of matching items per year (or month) — the direct way to chart coverage trends over time instead of paging through search results. Defaults to articles; also works on publications, references, documents, audiovisual, and images. Accepts the same filters as the corresponding search_* tool (keyword = ONE substring over the subset's text fields, country, newspaper/series, subject, date range). Optional group_by=country|newspaper returns one distribution per group. Items dated only to a year keep a bare-year key even at month granularity; undated items are counted in undated_count, never dropped silently. Set calendar=hijri to bucket by the Islamic (Umm al-Qura) calendar instead — with granularity=lunar_month this collapses every year into the twelve lunar months, which is the ONLY way to see observance-driven coverage (Ramadan, Dhu al-Hijja/hajj, Shawwal/Korité): the lunar year drifts ~11 days against the Gregorian, so a Gregorian axis smears each observance across all twelve months. Hijri buckets need a full YYYY-MM-DD, so items dated only to a year or month are reported in imprecise_date_count.

At-expiry P&L curve and breakevens for a multi-leg options structure (vertical spread, iron condor, straddle, butterfly, calendar). Pure math, no market lookup — pass the legs as JSON.

Upcoming earnings calendar over a configurable forward window. Returns event date, session (bmo/amc), confirmation status, fiscal period, importance rating, consensus EPS estimate, and stored implied-move percent for each event. Filter by symbols list and minimum importance; adjust days-ahead window (1–90, default 14).

Get earnings analytics for a symbol across six lenses. kind enum values: • expected_move — earnings-implied move decomposition: splits front-expiry straddle into jump vs baseline-diffusion using pre/post-event SVI term structure. • history — past earnings events: EPS/revenue surprises, implied vs actual moves, and realized IV crush per event. • iv_crush — expected + historical IV-crush distribution: live crush estimate and median/p25/p75/best/worst from up to 20 past events. • vrp — earnings vol-risk-premium: implied move vs realized-median, premium ratio, z-score, percentile, richness assessment. • dealer_positioning — event-scoped dealer exposure: gamma flip and walls on event-week expiries, GEX by DTE bucket, charm acceleration. • strategies — earnings strategy-suitability scores: long straddle, short strangle, iron condor, calendar spread, earnings diagonal (0–100 each).

Return HelloCPA Practice Management info — the standalone product at practice.hellobooks.ai for running a CPA / CA / bookkeeping practice (proposals + CPQ, workflow, time tracking, billing, 6-role RBAC, Gmail/Outlook/Calendar sync, CSV migration from TaxDome / Karbon / Canopy). NOT the Partner Program and NOT a tier in list_plans. Per-user pricing model — US shipped at $9.99/user/month (free up to 2 users + 10 clients, 90-day trial, enterprise at 50+ users). 7 other markets (IN, GB, AU, CA, AE, SG, NZ) are roadmap as of 2026-06-12. Call with no args for the full 8-region matrix + features + meta, or with `country` for one region's status + pricing + competitor frame.

Upcoming Crosby ISD school-calendar events: first/last day of school, holidays, no-school and early-release days, testing windows, and campus activities.