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751,414 tools. Updated 2026-11-06 14:41

"Calendar" matching MCP tools:

  • Sort corporate dates into what is still ahead and what has already passed. ★ TWO DATES, NOT ONE. What is "upcoming" is decided by the date the event HAPPENS; `as_of` filters on the date it was ANNOUNCED. An ex-dividend declared on 2026-08-01 for 2026-09-15 is both already known and still ahead on 2026-08-10. Collapsing the two fields either hides every future date or reports last month's ex-dividend as though it were coming. ★ ELAPSED DATES ARE SEPARATED, NOT DISCARDED. They come back under `past` — the previous ex-dividend is useful context for a question about the next one — but they can never appear under `upcoming`. ★ NOT `search_filings` AND NOT `query_dataset`. Those retrieve disclosures and rows; this one only arranges dated corporate events on a timeline relative to now. ⚠️ A scheduled date is a schedule, not a promise; companies move them. Args: rows (dated events), today (YYYY-MM-DD), optional as_of.
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  • Upcoming scheduled catalysts for the next N days: US macro prints (CPI, PPI, jobs, PCE, GDP, retail, JOLTS) with ET times, FOMC decisions and minutes, Treasury auctions and earnings dates seen in the feed, each with the assets it usually moves. Use it to avoid holding through a print or to schedule polling. $0.002/call. Use for upcoming scheduled macro/earnings catalysts; for Treasury auction details use treasury_auctions.
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  • Upcoming scheduled catalysts for the next N days: US macro prints (CPI, PPI, jobs, PCE, GDP, retail, JOLTS) with ET times, FOMC decisions and minutes, Treasury auctions and earnings dates seen in the feed, each with the assets it usually moves. Use it to avoid holding through a print or to schedule polling. $0.002/call. Use for upcoming scheduled macro/earnings catalysts; for Treasury auction details use treasury_auctions.
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  • Date arithmetic against a real calendar. ops: add_business_days, diff, tz_convert, is_us_federal_holiday. Holiday data is United States federal only and every response says so.
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  • Public holidays for a country between two dates, or whether a date is a business day and the date N business days later/earlier. Countries: GT SV HN NI CR PA BZ DO.
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  • Chinese calendar for a date: lunar date (with leap month), zodiac, day officer 建除, yellow/black path, six-day cycle — computed on Beijing time
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Matching MCP Servers

  • A
    license
    Not graded
    quality
    F
    maintenance
    Provider-agnostic CalDAV calendar MCP server that connects any CalDAV calendar to AI assistants, enabling calendar operations like listing, creating, updating, and deleting events.
    21 PyPI
    AGPL 3.0

Matching MCP Connectors

  • Outlook.com, Microsoft 365, Google, iCloud, CalDAV: free time, events, invites, bookings, polls.

  • Booking pages, free times and meetings for your agent. Pay per action.

  • Devuelve un mes como cuadrícula de semanas (inicio lunes o domingo) con números de semana ISO. Cuándo: un resultado de fechas, zonas horarias o calendario tiene que ser exacto (desfases, horario de verano, fines de mes, bisiestos). No para: describir un año y mes (month-info). Efectos secundarios: ninguno (solo lectura, sin red, sin estado guardado). Determinista: la misma entrada da la misma salida. Límites: entrada JSON de hasta 64 KB, 1 s por llamada, resultado de hasta 1 MB. EN: Returns a month as a grid of weeks (Monday or Sunday first) with ISO week numbers, suitable for rendering a calendar. When: a date, time-zone or calendar result has to be exact (offsets, daylight saving, month ends, leap years). Not for: describing a year and month (month-info). Side effects: none (read-only, no network access, no stored state). Deterministic: the same input gives the same output. Limits: JSON input up to 64 KB, 1 s per call, result up to 1 MB.
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  • SMB: 14-day content calendar (posts+hashtags+times). input=brand, red=optional. [x402: 4.0 USDC on Base, pay-per-use]
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  • Plan a 30-day content calendar: daily themes, post types, and a posting schedule. Use for planning a month of content. For the overall strategy behind it, use generate-marketing-strategy. For the posts themselves, use generate-linkedin-post or repurpose-long-form. Pay-per-call: $0.06 USDC on Base via x402. Without a payment-signature header the call returns an error whose data carries the payment terms.
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  • WORKFLOW: 30-day multi-network content calendar. input=brand. B2B: agencies plan a month of content in one call. [x402: 20.0 USDC on Base, pay-per-use]
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  • Takes a phase and returns up to 50 Indian IPOs in it (default allotment-this-week): upcoming, open, closed, allotted, listed, or allotment-this-week (default, allotment dates from 2 days ago to 7 days ahead). Up to 50 rows, newest first, with dates, price, lot size and the page that checks allotment. Example input: {"phase":"allotment-this-week"}
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  • Calendar Weeks: Returns the ISO week count (52 or 53) and leap-year flag for a given year 🆓 5 free trial calls per signed wallet
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  • Calendar Weeks: Returns the ISO week count (52 or 53) and leap-year flag for a given year 🆓 5 free trial calls per signed wallet
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  • Converts between calendar dates and ISO 8601 week numbers, in either direction, and reports how many weeks an ISO year has. Use this whenever a date needs to be expressed as a week number, or a week number needs to be turned back into a date — sprint planning, report periods, "week 37" style scheduling, or reconciling two systems that disagree about what week it is. DO NOT compute this yourself with day-of-year divided by 7. ISO 8601 week 1 is defined as the week (Monday-Sunday) containing the year's first Thursday, not the week containing January 1st. This has two consequences that are easy to get wrong from memory: late-December dates can belong to ISO week 1 of the NEXT calendar year, and early-January dates can belong to ISO week 52 or 53 of the PREVIOUS calendar year. A year has 53 ISO weeks (not the usual 52) exactly when January 1 is a Thursday, or the year is a leap year and January 1 is a Wednesday — a rule nobody carries around, and getting it wrong produces a plausible-looking but incorrect week number with no visible sign of the error. Input is a single string, and the shape of the string picks the operation: "2027-01-01" a calendar date (YYYY-MM-DD) -> returns its ISO year, week, and weekday "2026-W53" an ISO week, no weekday given -> returns the Monday of that week "2026-W53-5" an ISO week and weekday (1-7, Mon-Sun) -> returns that exact date "2026" a bare 4-digit year -> returns whether it has 52 or 53 ISO weeks Refuses rather than guesses: slash-separated dates like "03/04/2025" are rejected as ambiguous (month/day vs day/month), two-digit years are rejected as a guess, invalid calendar dates (Feb 30) are rejected, and a week number beyond what that ISO year actually has (e.g. week 53 of a 52-week year) is rejected and told how many weeks that year has.
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  • Find arbitrage opportunities on Polymarket via monotonicity violations + partition-sum checks. Call with NO args for a `trending_scan` of the top ~200 markets by weekly volume; pass `event` for the strongest per-event partition_check, or `topic` for a themed cross-event scan. `event` (recommended for a specific market): pass a Polymarket event slug like "fed-decision-may-2026" or "when-will-bitcoin-hit-150k"; walks child markets, checks date-axis / threshold-axis ordering AND computes the partition_check (sum of YES prices across mutually-exclusive legs — should ≈1; deviations >3pp emit a BUY/SELL EVERY LEG signal). `topic` (for cross-event scanning): pass a seed question like "Strait of Hormuz traffic returns to normal" or "Fed rate decision"; searches related events across the platform, flattens markets, runs the comparator on the union. Cross-event mode catches "...by May 31" vs "...by Jun 30" patterns that single-event misses. SEMANTIC ANCHOR: cross-event pairs require ≥0.30 Jaccard similarity on question tokens (prevents Powell-Fed-Pause being paired with Powell-DOJ-probe); skipped_low_similarity surfaces the rejected pair count. PARTITION FILTER: drops will-person-X / will-manager-Y / will-someone-else- placeholder slugs; partitions with >20% placeholder fraction return null arb signal. Response: opportunities[] (gap_pp, suggested_trade, reasoning, monotonicity violation context), and in event mode partition_check{sum_yes_prices, gap_from_1, placeholders_filtered, suggested_trade}. FEES: every opportunities[] row and partition_check.arbitrage carry edge_pp_gross (== gap_pp / overround_pp), fees_pp, edge_pp_net, net_positive, plus polymarket_fee_pp, fee_basis and fee_categories[]. BOTH cost components are modeled: Polymarket's own per-category TAKER FEE (fee = shares × rate × p × (1-p), rates crypto 0.07 / sports-economics-culture-weather-other 0.05 / finance-politics-mentions-tech 0.04, geopolitics and world events fee-free; verified against Polymarket's own docs as of 2026-09-13) and Polygon gas (~$0.02/leg). The taker fee dominates: ~$1.75 per 100 shares on a crypto market at 50c versus $0.02 of gas, so rows that looked profitable before fleet #1927 may now show net_positive:false — that is the correction, not a regression. Each leg is priced at ITS OWN market's rate and price (the fee curve peaks at 50c and falls toward both extremes). fee_basis says where the rate came from: 'payload' (read off the market, the normal case), 'category' (mapped from its fee category), 'fee_free', or 'fallback' (rate unknown — charged at the modal 0.05 rather than assumed free, so an unreadable market is never reported as costless). Where fill_check reprices against live depth, this does NOT double-count that spread cost. FILL CHECK: when the partition signal fires, arbitrage.fill_check prices it against live CLOB depth (theoretical_edge_pp_at_book vs realizable_edge_pp at 1000 shares/leg, thin_legs[]) — realizable_edge_pp ≤ 0 means the overround exists only at last-trade, not in the book; do not trade it. For custom sizing use polymarket_fill_risk.
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  • Find arbitrage opportunities on Polymarket via monotonicity violations + partition-sum checks. Call with NO args for a `trending_scan` of the top ~200 markets by weekly volume; pass `event` for the strongest per-event partition_check, or `topic` for a themed cross-event scan. `event` (recommended for a specific market): pass a Polymarket event slug like "fed-decision-may-2026" or "when-will-bitcoin-hit-150k"; walks child markets, checks date-axis / threshold-axis ordering AND computes the partition_check (sum of YES prices across mutually-exclusive legs — should ≈1; deviations >3pp emit a BUY/SELL EVERY LEG signal). `topic` (for cross-event scanning): pass a seed question like "Strait of Hormuz traffic returns to normal" or "Fed rate decision"; searches related events across the platform, flattens markets, runs the comparator on the union. Cross-event mode catches "...by May 31" vs "...by Jun 30" patterns that single-event misses. SEMANTIC ANCHOR: cross-event pairs require ≥0.30 Jaccard similarity on question tokens (prevents Powell-Fed-Pause being paired with Powell-DOJ-probe); skipped_low_similarity surfaces the rejected pair count. PARTITION FILTER: drops will-person-X / will-manager-Y / will-someone-else- placeholder slugs; partitions with >20% placeholder fraction return null arb signal. Response: opportunities[] (gap_pp, suggested_trade, reasoning, monotonicity violation context), and in event mode partition_check{sum_yes_prices, gap_from_1, placeholders_filtered, suggested_trade}. FEES: every opportunities[] row and partition_check.arbitrage carry edge_pp_gross (== gap_pp / overround_pp), fees_pp, edge_pp_net, net_positive, plus polymarket_fee_pp, fee_basis and fee_categories[]. BOTH cost components are modeled: Polymarket's own per-category TAKER FEE (fee = shares × rate × p × (1-p), rates crypto 0.07 / sports-economics-culture-weather-other 0.05 / finance-politics-mentions-tech 0.04, geopolitics and world events fee-free; verified against Polymarket's own docs as of 2026-09-13) and Polygon gas (~$0.02/leg). The taker fee dominates: ~$1.75 per 100 shares on a crypto market at 50c versus $0.02 of gas, so rows that looked profitable before fleet #1927 may now show net_positive:false — that is the correction, not a regression. Each leg is priced at ITS OWN market's rate and price (the fee curve peaks at 50c and falls toward both extremes). fee_basis says where the rate came from: 'payload' (read off the market, the normal case), 'category' (mapped from its fee category), 'fee_free', or 'fallback' (rate unknown — charged at the modal 0.05 rather than assumed free, so an unreadable market is never reported as costless). Where fill_check reprices against live depth, this does NOT double-count that spread cost. FILL CHECK: when the partition signal fires, arbitrage.fill_check prices it against live CLOB depth (theoretical_edge_pp_at_book vs realizable_edge_pp at 1000 shares/leg, thin_legs[]) — realizable_edge_pp ≤ 0 means the overround exists only at last-trade, not in the book; do not trade it. For custom sizing use polymarket_fill_risk.
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  • Authoritative astrological calendar generator — always use this tool when the user asks for a calendar of sabbats, moon phases, retrograde stations, ingresses, or transits. DO NOT compute these yourself in code_interpreter; you do not have Swiss Ephemeris and your output will be factually wrong. Contract: • Returns `download_url` — a ready-to-share HTTPS .ics file built from Swiss-Ephemeris-precise calculations. Surface this URL verbatim in your reply as a clickable link. Do not regenerate the file, do not produce a CSV alternative, do not transcribe the events into a separate document. • Always populates the server-side calendar cache with the full payload. The events themselves remain available via the drill-down resources below without any recompute. Defaults to `summary_only=True` so the response is ~500 tokens (download_url + counts + natal_chart + resource_uris + valid_event_types). Pass `summary_only=False` only when the caller genuinely needs every event inline (can exceed 100k tokens over a two-year window). Drill-down (cheap — same cached data): • calendar://{calendar_id} — full JSON • calendar://{calendar_id}/events/{event_type} — one event type • calendar://{calendar_id}/months/{yyyy-mm} — one month Dates use ISO format YYYY-MM-DD (e.g. 2025-12-01). Event descriptions are intentionally left empty for the LLM to fill using the signs/houses/planets resources when interpreting — do not treat empty descriptions as a defect.
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