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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).

List every macroeconomic indicator FXMacroData publishes for a currency, with units, frequency, and coverage/freshness metadata. ALWAYS call this first when the user asks about a country's macro data — it returns the exact `indicator` slug strings to pass to indicator_query, release_calendar, and indicator_visual_artifact. Check `coverage` before calling indicator_query; stale, partial, or unavailable rows are not suitable for real-time carry or inflation analysis. Supported currencies (lowercase 3-letter codes): AUD, BRL, CAD, CHF, CNH, CNY, DKK, EUR, GBP, ILS, JPY, NGN, NOK, NZD, PEN, SEK, THB, USD.

Get upcoming scheduled macroeconomic release timestamps for a currency. Use this when the user asks 'when is the next CPI/GDP/payrolls/policy decision', or to plan a trade around a known release. Returns ISO-8601 announcement_datetime values in UTC plus market-local timestamps. Pass `timezone` for an additional `announcement_datetime_requested_timezone` field. Each row has a `release` string with the indicator name and a `currency` code. Unbounded calls return future releases only; do not show stale past rows unless the user explicitly asks for historical/past calendar data. Consumer-facing clients should present the returned markdown agenda or render the Release Calendar App resource; do not summarize this tool as only a row count. Pass an optional `indicator` filter to narrow to a single series. Pass optional `start_date` and `end_date` bounds when the user mentions a month, week, day, or explicit date range. Supported currencies: AED, ARS, AUD, BOB, BRL, CAD, CHF, CLP, CNH, CNY, COMM, COP, CZK, DKK, DZD, EGP, EUR, GBP, HKD, HUF, IDR, ILS, INR, JPY, KRW, MAD, MXN, MYR, NGN, NOK, NZD, PEN, PHP, PKR, PLN, RUB, SAR, SEK, SGD, THB, TRY, TWD, USD, UYU, VND, ZAR. Supported indicators: average_hourly_earnings, average_hourly_earnings_mom, balance_on_goods, balance_on_services, breakeven_inflation_rate, building_approvals, building_permits, business_confidence, capital_account_balance, cb_assets, commodity_price_energy, commodity_price_ex_energy, commodity_price_index, commodity_prices, consumer_confidence, core_inflation, core_inflation_median, core_inflation_mom, core_inflation_trim, core_pce, core_pce_mom, credit_growth, crude_oil_inventories, current_account_balance, dairy_exports, deposit_rates, durable_goods_orders, employment, exports, financial_account_balance, foreign_reserves, full_time_employment, gdp, gdp_growth_q4_yoy, gdp_growth_qoq_saar, gdp_quarterly, gold_reserves, gov_bond_10y, gov_bond_1y, gov_bond_20y, gov_bond_2y, gov_bond_30y, gov_bond_3y, gov_bond_40y, gov_bond_4y, gov_bond_5y, gov_bond_7y, government_debt, house_price_index, household_credit, housing_starts, imports, inflation, inflation_linked_bond, inflation_mom, initial_jobless_claims, international_assets, international_liabilities, job_openings, m1, m2, m3, monthly_cpi, nairu, natural_gas_storage, net_foreign_asset_position, non_farm_payrolls, non_farm_payrolls_change, part_time_employment, participation_rate, pce, pce_mom, policy_rate, policy_rate_midpoint, policy_rate_mlf, policy_rate_mro, policy_rate_target_lower, ppi, ppi_mom, primary_income_balance, retail_sales, retail_sales_control_group, retail_sales_ex_autos, retail_sales_ex_autos_and_gas, risk_free_rate, secondary_income_balance, sight_deposits, terms_of_trade, trade_balance, trade_weighted_index, trimmed_mean_inflation, unemployment, wage_price_index, wages.

Same payload as release_calendar, but named as an explicit visual artifact tool so compatible MCP Apps clients render the interactive Release Calendar App inline. Prefer this by default when the user asks to show, display, visualize, or render a macro release calendar, especially for prompts like 'show me the AUD release calendar'. Only prefer plain release_calendar when the user explicitly asks for a raw table, JSON, exact rows, or text-only output. Pass optional `indicator`, `start_date`, and `end_date` filters when the user names a specific series, month, week, day, or date range. Pass `timezone` when the user asks for local times in a specific city or region. Supported currencies: AED, ARS, AUD, BOB, BRL, CAD, CHF, CLP, CNH, CNY, COMM, COP, CZK, DKK, DZD, EGP, EUR, GBP, HKD, HUF, IDR, ILS, INR, JPY, KRW, MAD, MXN, MYR, NGN, NOK, NZD, PEN, PHP, PKR, PLN, RUB, SAR, SEK, SGD, THB, TRY, TWD, USD, UYU, VND, ZAR. Supported indicators: average_hourly_earnings, average_hourly_earnings_mom, balance_on_goods, balance_on_services, breakeven_inflation_rate, building_approvals, building_permits, business_confidence, capital_account_balance, cb_assets, commodity_price_energy, commodity_price_ex_energy, commodity_price_index, commodity_prices, consumer_confidence, core_inflation, core_inflation_median, core_inflation_mom, core_inflation_trim, core_pce, core_pce_mom, credit_growth, crude_oil_inventories, current_account_balance, dairy_exports, deposit_rates, durable_goods_orders, employment, exports, financial_account_balance, foreign_reserves, full_time_employment, gdp, gdp_growth_q4_yoy, gdp_growth_qoq_saar, gdp_quarterly, gold_reserves, gov_bond_10y, gov_bond_1y, gov_bond_20y, gov_bond_2y, gov_bond_30y, gov_bond_3y, gov_bond_40y, gov_bond_4y, gov_bond_5y, gov_bond_7y, government_debt, house_price_index, household_credit, housing_starts, imports, inflation, inflation_linked_bond, inflation_mom, initial_jobless_claims, international_assets, international_liabilities, job_openings, m1, m2, m3, monthly_cpi, nairu, natural_gas_storage, net_foreign_asset_position, non_farm_payrolls, non_farm_payrolls_change, part_time_employment, participation_rate, pce, pce_mom, policy_rate, policy_rate_midpoint, policy_rate_mlf, policy_rate_mro, policy_rate_target_lower, ppi, ppi_mom, primary_income_balance, retail_sales, retail_sales_control_group, retail_sales_ex_autos, retail_sales_ex_autos_and_gas, risk_free_rate, secondary_income_balance, sight_deposits, terms_of_trade, trade_balance, trade_weighted_index, trimmed_mean_inflation, unemployment, wage_price_index, wages.

Return stored forecasts, consensus-style predictions, central-bank projections, survey forecasts, IMF forecasts, nowcasts, or FXMacroData blended predictions for macro announcements. Use this with release_calendar and indicator_query when a report needs actual-vs-consensus, prior-vs-forecast, or event-surprise context. Rows are keyed by announcement_id/date/indicator and include prediction source metadata. Supported currencies: AUD, BRL, CAD, CHF, CNH, CNY, DKK, EUR, GBP, ILS, JPY, NGN, NOK, NZD, PEN, SEK, THB, USD. Supported indicators: average_hourly_earnings, average_hourly_earnings_mom, balance_on_goods, balance_on_services, breakeven_inflation_rate, building_approvals, building_permits, business_confidence, capital_account_balance, cb_assets, commodity_price_energy, commodity_price_ex_energy, commodity_price_index, commodity_prices, consumer_confidence, core_inflation, core_inflation_median, core_inflation_mom, core_inflation_trim, core_pce, core_pce_mom, credit_growth, crude_oil_inventories, current_account_balance, dairy_exports, deposit_rates, durable_goods_orders, employment, exports, financial_account_balance, foreign_reserves, full_time_employment, gdp, gdp_growth_q4_yoy, gdp_growth_qoq_saar, gdp_quarterly, gold_reserves, gov_bond_10y, gov_bond_1y, gov_bond_20y, gov_bond_2y, gov_bond_30y, gov_bond_3y, gov_bond_40y, gov_bond_4y, gov_bond_5y, gov_bond_7y, government_debt, house_price_index, household_credit, housing_starts, imports, inflation, inflation_linked_bond, inflation_mom, initial_jobless_claims, international_assets, international_liabilities, job_openings, m1, m2, m3, monthly_cpi, nairu, natural_gas_storage, net_foreign_asset_position, non_farm_payrolls, non_farm_payrolls_change, part_time_employment, participation_rate, pce, pce_mom, policy_rate, policy_rate_midpoint, policy_rate_mlf, policy_rate_mro, policy_rate_target_lower, ppi, ppi_mom, primary_income_balance, retail_sales, retail_sales_control_group, retail_sales_ex_autos, retail_sales_ex_autos_and_gas, risk_free_rate, secondary_income_balance, sight_deposits, terms_of_trade, trade_balance, trade_weighted_index, trimmed_mean_inflation, unemployment, wage_price_index, wages.

Build a compact macro briefing for a currency by combining catalogue, key macro series, release-calendar, prediction, news, risk-sentiment, COT, seasonality, and FX technical context. Supports MCP Tasks for async execution when clients send a task-augmented request.

Score upcoming releases for a currency pair using release-calendar proximity and indicator-level heuristics. Supports MCP Tasks for async execution when clients send task-augmented requests.

Converts a Gregorian (civil) date to a Hebrew date (Jewish calendar)

Calculates the Yahrzeit, the anniversary of the day of death of a loved one, according to the Hebrew calendar for a specified date

Get a rate calendar showing prices across a date range for a hotel. Use this when a user has flexible dates and wants to find the cheapest time to stay. Shows cash rates, points rates, and value percentiles for each available check-in date. Args: hotel_id: The hotel's Vervotech property ID (from search results). start_date: Start of date range in YYYY-MM-DD format. end_date: End of date range in YYYY-MM-DD format. nights: Number of nights per stay (default: 1). Returns: Rate calendar with pricing for each available date.

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.

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, and China A-shares. Tickers are US bare (AAPL), Japan `.T` (6758.T), Hong Kong `.HK` (00700.HK), and A-shares `.SH`/`.SZ` (600519.SH, 300750.SZ). financial_statements, company_snapshot, and price_volume_history span all four. Specialized tables may be US-only or US+Japan — 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=[...])

Use to convert between fiscal year/quarter and calendar months for a ticker before filtering period_end columns. Coverage warning: fiscal-year configuration is primarily US, with sparse JP/HK entries and no China A-share coverage in the verified dataset. Do not assume this tool supports a ticker merely because the core equity tables do. Forward: ticker + fiscal_year + fiscal_quarter → period_start/period_end. Reverse: ticker + yyyy_mm → fiscal_year/fiscal_quarter.

GET /calendar — Get your iCalendar feed URL + settings Returns your iCalendar feed URLs and the toggles that control which event categories the feed includes. **Three URLs are returned:** - `httpsURL` — paste into any calendar app that accepts an HTTPS subscription - `webcalURL` — same URL with the `webcal://` scheme; macOS / iOS Calendar opens it directly - `googleURL` — one-click Google Calendar subscribe link The feed includes events you have tickets to, virtual calls, your trips, chapter events, and flagship events — exactly what each `include*` toggle below controls. Tokens are deterministic, so the URLs never change for a given member.

PATCH /calendar — Update calendar feed settings Update any subset of your calendar feed toggles. Send only the toggles you want to change — omitted fields are left untouched. Returns `{ updated: true }` on success; re-fetch `GET /calendar` if you need the full toggle set + feed URLs (the URLs themselves are stable and don't change when toggles update). ⚠️ WRITE operation: this mutates your DC account data.

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

Create ONE slide 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. FORM MENU: agenda_list: an ordered list of sections/topics to walk through bar_rank_chart: bars comparing magnitudes across categories calendar_grid: events on a real calendar - a week planner (day columns x hour axis) or a month grid with release/event chips (data.events) card_grid: several equal, unordered peer blocks (features, options, pillars) 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 in contrast (before/after, problem/solution) 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: a cover (typographic/image-led/exec-metadata), a from->to or thesis-quote transition, or a contact or next-steps closing hub_spoke: one central element with several elements connected around it kpi_metrics: a board of headline metric cards; add data.sections (Highlights/Risks/Asks) for a one-slide exec summary / board update / 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 slide: big section number + title; blocks = agenda progress chips (emphasis=primary marks the current section) 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: nodes connected by directed arrows that carry the message (data/requests move) takeaway_stack: a few bold conclusions, each with one line of support; 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 (how value is created; 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.

"Compare X and Y" / "X vs Y" / "X versus Y" / "which is bigger / better / larger / more profitable" / "rank these companies" / "head to head" — side-by-side comparison of 2–5 companies or drugs in ONE parallel call. ALWAYS PREFER over sequential single-pack lookups when comparing entities. type="company" pulls LATEST 10-K revenue + net income + cash + long-term debt from SEC EDGAR/XBRL (off-calendar fiscal years handled correctly — AAPL Sep, NVDA Jan, etc.). type="drug" pulls FAERS adverse-event counts, FDA approval counts, active trial counts. Results sorted by primary metric so "largest" / "most" / "biggest" reads off the top of the response. Returns paired data + pipeworx:// citation URIs per entity. Replaces 8–15 sequential lookups.

Cross-venue spread between Kalshi and Polymarket for the same resolving question. The two venues sometimes price the same outcome 2-25pp apart because their participant pools differ — when the bet shapes are equivalent that delta is a real signal, when they aren't the tool says so. TWO MODES: (1) `topic` — 10 pre-mapped macro shortcuts ("fed", "btc", "cpi", "gdp", "sp500", "recession", "next_pope", "next_uk_pm", "next_israel_pm", "2028_president") auto-fetch the matching event on each venue. (2) explicit `kalshi_event_ticker` + `polymarket_event_slug` for custom pairings. RESPONSE: each venue's leg-by-leg prices (raw probability 0-1) plus matched spread[].top_spreads_pp (Kalshi − Polymarket) where the same outcome shows up on both sides. SAFETY FIELDS: compatibility_warning fires in two cases — (a) matched_pairs:0 with skipped_cross_type>0 means the venues frame the topic with non-equivalent bet shapes (e.g. Kalshi range_bucket point-in-time vs Polymarket cumulative_threshold touch-anywhere — no arb exists), (b) matched_pairs:0 with skipped_cross_type:0 and both venues >5 legs means the token-overlap matcher found nothing in common — events likely semantically unrelated despite the topic keyword. temporal_alignment{polymarket_month,kalshi_month,aligned} tells you whether the two events resolve in the same calendar period; aligned:false means spreads are mathematically meaningless across the temporal gap. skipped_cross_type / skipped_cross_subtype counters expose how many leg-pair comparisons were dropped (cross-type = metric_type mismatch like MoM vs YoY; cross-subtype = inequality mismatch like cum_ge vs cum_le). Real cross-venue spreads are rarer than the macro-shortcut list suggests — most pre-mapped topics return compatibility_warning today; pre-mapped ≠ tradeable.

Search thousands of MCP servers by use case (e.g., 'database', 'email', 'calendar'). Returns community and hosted servers. Use to find tools beyond Pipeworx.

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.

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, or etf_flows. Returns points oldest-first with an explicit downsampling flag when the raw series exceeded max_points. etf_flows is filing-cadence (one point per SEC filing refresh), NOT per calendar day, so even a wide window yields a handful of points. Times are UTC. Costs 1 unit per call. Args: metric: One of price / macro_series / etf_flows. entity: Entity dict from resolve_entity ({"namespace": ..., "ids": ...}). granularity: Requested point granularity (default "1d"). max_points: Hard cap on returned points (default 500).

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.

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 a company's valuation multiples over time — EV/Revenue, EV/EBIT and P/E recomputed at each past quarter's filing date, one row per quarter. Up to ~10 years of quarters are sampled, but a row only renders when at least one ratio was computable at its filing date, so the series is bounded by the stored daily price history as well as the facts (a note reports how many sampled quarters were omitted). Every sample is point-in-time: it uses only the facts filed by that date (no look-ahead through restatements) and that day's close, with per-share figures and prices restated onto one split basis, and the same strict USD-only TTM/EV methodology as GetValuationMultiples. Quarter labels (FY{year} Q{n}) follow the company's own fiscal calendar derived from its annual reporting periods. A quarter missing an input has a dash for that ratio, never an estimate.

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 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 / GetInvestorEventSpeakers.

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.

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.

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.

Use this when the user asks what fruit is in season in a given month or which month is best for strawberries, grapes, peaches, apples, and similar picking trips. Returns the fruit season calendar, peak months, best regions, and notes for 14 fruits. Call fruit_farms next if the user needs actual farm listings, map coordinates, or booking links.

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.

Get upcoming and recent earnings releases between two dates. Optionally restrict to a list of tickers. Returns ticker, date, time (BMO/AMC), EPS estimate, and revenue estimate when available. Supports market cap filtering to focus on large-cap or small-cap earnings only.

Get scheduled macro/economic events (CPI, FOMC, jobs reports, GDP, etc.) between two dates. Optionally filter to a single country (ISO-3166 alpha-2, e.g. "US"). Defaults to US when omitted.

Get the forward-looking 10-K / 10-Q SEC filing-deadline calendar within a date window. Optionally restrict to a universe (sp500/ndx/dji/all) and/or a list of form types (default both 10-K and 10-Q).

Get stocks that moved significantly after earnings reports on a given date. Returns pre-computed price changes with earnings surprise data in a single call — no need to chain get_earnings_calendar + get_historical_prices + get_quote per ticker. Includes preEarningsClose, currentPrice, changePct, EPS/revenue actuals vs estimates, and surprise percentages. Filter by minimum absolute % change threshold.

Find companies projected to run out of cash within a date window. Similar to lockup expiration calendars but for cash depletion events. Returns companies sorted by urgency (lowest runway first). Runway is an estimate based on current burn rate — actual depletion depends on future capital raises and operational changes. Default window is today to 90 days out.

Forward-looking legislative catalyst calendar: upcoming House/Senate floor votes (bills and Senate cloture motions) filtered to items that can move tickers. Each item includes the predicted vote window (start/end/granularity/confidence/provenance), marketRelevance (low/medium/high), significance (1-5), affected sectors with direction + mechanism, verified affected tickers with evidence quotes, pass outlook, considerationProcedure (suspension-calendar bills pass ~98% of the time), a conflictBadge when the sponsor traded a verified affected ticker, and tweet/plain summaries. An EMPTY calendar is a normal state — it means nothing market-relevant is scheduled in the window, not an error. Defaults: from=today, to=+14 days, minRelevance=low. IMPORTANT: affectedTickers contains VERIFIED rows only — every ticker carries a verbatim evidenceQuote substring-verified against the actual bill text (no hallucinated tickers). sponsorTradeFacts are restatements of public STOCK Act disclosures with verbatim amount brackets and BOTH transactionDate AND disclosureDate — always cite both dates together (disclosures lag trades by up to 45 days), and never present a fact as evidence of wrongdoing. Vote windows are predictions: check window.provenance for trust level ('uc_explicit' is exact; 'rule_xxii_computed' is a medium-confidence estimate) and window.granularity for how precise the window is (exact time vs day vs week).

HarvestPulse: Global farm-to-table and agricultural intelligence API. USDA + ERS data synthesis. Local food finder (farmers markets, CSAs, on-farm markets), seasonal produce calendars, organic certification lookup, Coverage: Global Endpoints: • find ($0.05): Local Farm & Market Finder • season ($0.05): Seasonal Produce Calendar • labels ($0.08): Food Label Decoder • organic ($0.08): Certified Organic Farm Finder • dirty-dozen ($0.05): Dirty Dozen & Clean Fifteen • food-hub ($0.08): Regional Food Hub Finder • regenerative ($0.10): Regenerative Agriculture Guide • designations ($0.10): Global Food Designations • agritourism ($0.05): Agritourism & U-Pick Finder • csa ($0.10): CSA Evaluation Guide • cost ($0.10): Local vs. Conventional Cost Analysis • roadmap ($0.15): Farm-to-Table Lifestyle Roadmap • food-preservation ($0.10): Food preservation guide • foraging-intel ($0.10): Foraging intelligence • livestock-basics ($0.10): Backyard livestock guide

HomePulse: Global home intelligence API. AI-synthesized home maintenance checklists, improvement ROI analysis, neighborhood research, smart home integration, energy efficiency guidance, contractor task briefings Coverage: Global Endpoints: • value ($0.10): Home value estimate • neighborhood ($0.10): Neighborhood analysis • improve ($0.10): Home improvement ROI analysis • maintain ($0.08): Seasonal maintenance checklist • rent ($0.08): Rental market analysis • contractor ($0.10): Contractor vetting guide • energy ($0.10): Home energy efficiency • maintenance ($0.08): Personalized home maintenance calendar • roi ($0.10): Home improvement resale ROI • smart ($0.08): Smart home ecosystem advisor

MacroPulse: Real-time macro intelligence for forex and CFD traders. All endpoints require x402 payment (USDC on Base mainnet) via the PAYMENT-SIGNATURE header. Coverage: Global Endpoints: • session-brief ($0.10): Forex session brief • event-pulse ($0.20): Economic event deep-dive • crypto-pulse ($0.05): Crypto market context • commodities-pulse ($0.10): Commodities brief • calendar ($0.10): Weekly economic calendar • cot ($0.02): CFTC Commitments of Traders positioning — 21 markets, deterministic • bls-series ($0.02): US labor statistics by BLS series id — deterministic, computed YoY • eia-inventory ($0.10): Weekly EIA petroleum inventory intelligence for energy and macro agents — crude, gasoline and distillate builds and draws versus expectations, with the oil-price and CAD/NOK implications. • intermarket ($0.15): Cross-asset intermarket synthesis for macro agents — bond yields, equities, commodities and FX read together to surface the dominant regime and the divergences that tend to lead price. • rates-differential ($0.10): Interest-rate differential and carry intelligence for FX agents — G10 policy rates, yield spreads and the carry-trade map that drives durable currency trends. • regime ($0.10): Macro regime classifier for multi-asset agents — labels the current environment (risk-on/off, reflation, stagflation, tightening) and its directional implications for FX, rates and equities. • convert ($0.005): Currency conversion at the official ECB reference rate • is-open ($0.005): Is the stock market open right now? Exchange status, trading hours and holiday calendar • us ($0.01): Official US macro indicators read from Chainlink contracts (GDP, PCE, SOFR) • us-revisions ($0.02): The revision trail of a US macro series, from immutable on-chain round history • sentiment ($0.05): Real-time directional sentiment for any forex pair or gold — retail crowd positioning, COT institutional alignment, and a clear contrarian bias call. Built for FX trading and advisor agents.

PolicyPulse: PolicyPulse — global legislative intelligence: US Congress, EU (EUR-Lex), UK Parliament, India, Brazil, Australia, and 50+ jurisdictions. Bill summaries, sector impact, passage probability, treaty ana Coverage: Global Endpoints: • register ($0.02): Federal Register search — rules, proposed rules, notices, open comment periods • legislation ($0.15): Legislation — plain English translation of any bill globally • impact ($0.15): Impact — who is affected and what they must do • scenario ($0.20): Scenarios — if/then sector impact modeling • monitor ($0.10): Monitor — weekly/monthly legislative activity brief • state ($0.10): State — legislation across all 50 US states via Open States • compliance ($0.15): Compliance — what to do after a law passes • regulation ($0.15): Federal regulation — agency rules via Federal Register • compare ($0.15): Compare — cross-jurisdiction policy comparison • calendar ($0.10): Calendar — upcoming regulatory deadlines and effective dates • translate ($0.08): Translate — decode any legal or regulatory text into plain English • court ($0.15): Court decision intelligence • treaty ($0.10): International treaty and trade-agreement intelligence

Use this when the user asks what is on in a city tonight. Returns evening-appropriate experiences currently on sale, with seasonal products filtered out and evening-led options ranked first. Top results carry start_time (venue-local) when the live supplier calendar confirms a performance in the evening window (late afternoon onward), and timed rows sort soonest-first; rows without start_time have no confirmed evening time. Confirm the selected experience with get_availability before stating it is bookable tonight.

Use this when the user wants ideas for the coming week in a city. Returns a ranked list of currently on-sale experiences (search rows), not a day-by-day calendar. Assemble any weekly structure yourself and verify specific dates with get_availability.

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. 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.

Complete temporal context for a location: local time, timezone, 14-day calendar with day names and Today/Tomorrow offsets, sunrise/sunset/solar times (from the weather pipeline's astro product), and moon phase. Use whenever you need to reason about dates, times, or daylight for a location -- including "what time is sunset?", "is it dark there now?", or "what day of the week is the 4th-day forecast?". Accepts a place name directly. Example: {"location": "Seattle"}.

"Compare X and Y" / "X vs Y" / "X versus Y" / "which is bigger / better / larger / more profitable" / "rank these companies" / "head to head" — side-by-side comparison of 2–5 companies or drugs in ONE parallel call. ALWAYS PREFER over sequential single-pack lookups when comparing entities. type="company" pulls LATEST 10-K revenue + net income + cash + long-term debt from SEC EDGAR/XBRL (off-calendar fiscal years handled correctly — AAPL Sep, NVDA Jan, etc.). type="drug" pulls FAERS adverse-event counts, FDA approval counts, active trial counts. Results sorted by primary metric so "largest" / "most" / "biggest" reads off the top of the response. Returns paired data + pipeworx:// citation URIs per entity. Replaces 8–15 sequential lookups.

Cross-venue spread between Kalshi and Polymarket for the same resolving question. The two venues sometimes price the same outcome 2-25pp apart because their participant pools differ — when the bet shapes are equivalent that delta is a real signal, when they aren't the tool says so. TWO MODES: (1) `topic` — 10 pre-mapped macro shortcuts ("fed", "btc", "cpi", "gdp", "sp500", "recession", "next_pope", "next_uk_pm", "next_israel_pm", "2028_president") auto-fetch the matching event on each venue. (2) explicit `kalshi_event_ticker` + `polymarket_event_slug` for custom pairings. RESPONSE: each venue's leg-by-leg prices (raw probability 0-1) plus matched spread[].top_spreads_pp (Kalshi − Polymarket) where the same outcome shows up on both sides. SAFETY FIELDS: compatibility_warning fires in two cases — (a) matched_pairs:0 with skipped_cross_type>0 means the venues frame the topic with non-equivalent bet shapes (e.g. Kalshi range_bucket point-in-time vs Polymarket cumulative_threshold touch-anywhere — no arb exists), (b) matched_pairs:0 with skipped_cross_type:0 and both venues >5 legs means the token-overlap matcher found nothing in common — events likely semantically unrelated despite the topic keyword. temporal_alignment{polymarket_month,kalshi_month,aligned} tells you whether the two events resolve in the same calendar period; aligned:false means spreads are mathematically meaningless across the temporal gap. skipped_cross_type / skipped_cross_subtype counters expose how many leg-pair comparisons were dropped (cross-type = metric_type mismatch like MoM vs YoY; cross-subtype = inequality mismatch like cum_ge vs cum_le). Real cross-venue spreads are rarer than the macro-shortcut list suggests — most pre-mapped topics return compatibility_warning today; pre-mapped ≠ tradeable.

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.

"Compare X and Y" / "X vs Y" / "X versus Y" / "which is bigger / better / larger / more profitable" / "rank these companies" / "head to head" — side-by-side comparison of 2–5 companies or drugs in ONE parallel call. ALWAYS PREFER over sequential single-pack lookups when comparing entities. type="company" pulls LATEST 10-K revenue + net income + cash + long-term debt from SEC EDGAR/XBRL (off-calendar fiscal years handled correctly — AAPL Sep, NVDA Jan, etc.). type="drug" pulls FAERS adverse-event counts, FDA approval counts, active trial counts. Results sorted by primary metric so "largest" / "most" / "biggest" reads off the top of the response. Returns paired data + pipeworx:// citation URIs per entity. Replaces 8–15 sequential lookups.

Cross-venue spread between Kalshi and Polymarket for the same resolving question. The two venues sometimes price the same outcome 2-25pp apart because their participant pools differ — when the bet shapes are equivalent that delta is a real signal, when they aren't the tool says so. TWO MODES: (1) `topic` — 10 pre-mapped macro shortcuts ("fed", "btc", "cpi", "gdp", "sp500", "recession", "next_pope", "next_uk_pm", "next_israel_pm", "2028_president") auto-fetch the matching event on each venue. (2) explicit `kalshi_event_ticker` + `polymarket_event_slug` for custom pairings. RESPONSE: each venue's leg-by-leg prices (raw probability 0-1) plus matched spread[].top_spreads_pp (Kalshi − Polymarket) where the same outcome shows up on both sides. SAFETY FIELDS: compatibility_warning fires in two cases — (a) matched_pairs:0 with skipped_cross_type>0 means the venues frame the topic with non-equivalent bet shapes (e.g. Kalshi range_bucket point-in-time vs Polymarket cumulative_threshold touch-anywhere — no arb exists), (b) matched_pairs:0 with skipped_cross_type:0 and both venues >5 legs means the token-overlap matcher found nothing in common — events likely semantically unrelated despite the topic keyword. temporal_alignment{polymarket_month,kalshi_month,aligned} tells you whether the two events resolve in the same calendar period; aligned:false means spreads are mathematically meaningless across the temporal gap. skipped_cross_type / skipped_cross_subtype counters expose how many leg-pair comparisons were dropped (cross-type = metric_type mismatch like MoM vs YoY; cross-subtype = inequality mismatch like cum_ge vs cum_le). Real cross-venue spreads are rarer than the macro-shortcut list suggests — most pre-mapped topics return compatibility_warning today; pre-mapped ≠ tradeable.

Given agent-supplied facts, decide whether a standup is due. Triggers in priority order: a deliverable gate reached → 'gate'; else a dependency intersection → 'intersection'; else more than five working days since the last standup → 'weekly'; else 'none'. Working days are an input (the working week varies by team), never computed from a calendar. Returns { due, reason, detail }.

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).

"Compare X and Y" / "X vs Y" / "X versus Y" / "which is bigger / better / larger / more profitable" / "rank these companies" / "head to head" — side-by-side comparison of 2–5 companies or drugs in ONE parallel call. ALWAYS PREFER over sequential single-pack lookups when comparing entities. type="company" pulls LATEST 10-K revenue + net income + cash + long-term debt from SEC EDGAR/XBRL (off-calendar fiscal years handled correctly — AAPL Sep, NVDA Jan, etc.). type="drug" pulls FAERS adverse-event counts, FDA approval counts, active trial counts. Results sorted by primary metric so "largest" / "most" / "biggest" reads off the top of the response. Returns paired data + pipeworx:// citation URIs per entity. Replaces 8–15 sequential lookups.

Cross-venue spread between Kalshi and Polymarket for the same resolving question. The two venues sometimes price the same outcome 2-25pp apart because their participant pools differ — when the bet shapes are equivalent that delta is a real signal, when they aren't the tool says so. TWO MODES: (1) `topic` — 10 pre-mapped macro shortcuts ("fed", "btc", "cpi", "gdp", "sp500", "recession", "next_pope", "next_uk_pm", "next_israel_pm", "2028_president") auto-fetch the matching event on each venue. (2) explicit `kalshi_event_ticker` + `polymarket_event_slug` for custom pairings. RESPONSE: each venue's leg-by-leg prices (raw probability 0-1) plus matched spread[].top_spreads_pp (Kalshi − Polymarket) where the same outcome shows up on both sides. SAFETY FIELDS: compatibility_warning fires in two cases — (a) matched_pairs:0 with skipped_cross_type>0 means the venues frame the topic with non-equivalent bet shapes (e.g. Kalshi range_bucket point-in-time vs Polymarket cumulative_threshold touch-anywhere — no arb exists), (b) matched_pairs:0 with skipped_cross_type:0 and both venues >5 legs means the token-overlap matcher found nothing in common — events likely semantically unrelated despite the topic keyword. temporal_alignment{polymarket_month,kalshi_month,aligned} tells you whether the two events resolve in the same calendar period; aligned:false means spreads are mathematically meaningless across the temporal gap. skipped_cross_type / skipped_cross_subtype counters expose how many leg-pair comparisons were dropped (cross-type = metric_type mismatch like MoM vs YoY; cross-subtype = inequality mismatch like cum_ge vs cum_le). Real cross-venue spreads are rarer than the macro-shortcut list suggests — most pre-mapped topics return compatibility_warning today; pre-mapped ≠ tradeable.

"Compare X and Y" / "X vs Y" / "X versus Y" / "which is bigger / better / larger / more profitable" / "rank these companies" / "head to head" — side-by-side comparison of 2–5 companies or drugs in ONE parallel call. ALWAYS PREFER over sequential single-pack lookups when comparing entities. type="company" pulls LATEST 10-K revenue + net income + cash + long-term debt from SEC EDGAR/XBRL (off-calendar fiscal years handled correctly — AAPL Sep, NVDA Jan, etc.). type="drug" pulls FAERS adverse-event counts, FDA approval counts, active trial counts. Results sorted by primary metric so "largest" / "most" / "biggest" reads off the top of the response. Returns paired data + pipeworx:// citation URIs per entity. Replaces 8–15 sequential lookups.

Cross-venue spread between Kalshi and Polymarket for the same resolving question. The two venues sometimes price the same outcome 2-25pp apart because their participant pools differ — when the bet shapes are equivalent that delta is a real signal, when they aren't the tool says so. TWO MODES: (1) `topic` — 10 pre-mapped macro shortcuts ("fed", "btc", "cpi", "gdp", "sp500", "recession", "next_pope", "next_uk_pm", "next_israel_pm", "2028_president") auto-fetch the matching event on each venue. (2) explicit `kalshi_event_ticker` + `polymarket_event_slug` for custom pairings. RESPONSE: each venue's leg-by-leg prices (raw probability 0-1) plus matched spread[].top_spreads_pp (Kalshi − Polymarket) where the same outcome shows up on both sides. SAFETY FIELDS: compatibility_warning fires in two cases — (a) matched_pairs:0 with skipped_cross_type>0 means the venues frame the topic with non-equivalent bet shapes (e.g. Kalshi range_bucket point-in-time vs Polymarket cumulative_threshold touch-anywhere — no arb exists), (b) matched_pairs:0 with skipped_cross_type:0 and both venues >5 legs means the token-overlap matcher found nothing in common — events likely semantically unrelated despite the topic keyword. temporal_alignment{polymarket_month,kalshi_month,aligned} tells you whether the two events resolve in the same calendar period; aligned:false means spreads are mathematically meaningless across the temporal gap. skipped_cross_type / skipped_cross_subtype counters expose how many leg-pair comparisons were dropped (cross-type = metric_type mismatch like MoM vs YoY; cross-subtype = inequality mismatch like cum_ge vs cum_le). Real cross-venue spreads are rarer than the macro-shortcut list suggests — most pre-mapped topics return compatibility_warning today; pre-mapped ≠ tradeable.