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650,478 tools. Updated 2026-10-13 12:24

"Rider" matching MCP tools:

  • Find the best connections by train, tram, bus, boat and mountain railway between two places in Switzerland, from Spick Me's own routing engine over the official Swiss timetable. Door to door: an address or a named place works as well as a station, and the walk to and from the nearest stops is included. Use it for "how do I get from A to B", "the next connections from Olten to Zürich", "when is the next train to …", "I need to be in Bern by 9" — it gives departure and arrival times, changes and platforms. Prefer it to the departure board for any question with a destination. Every journey comes with a picture_url: a link that opens a ready-made image of the connection the user can look at or share — offer it when a picture would help. Inputs: from and to are each A station or stop name ("Zürich HB", "Bern", "Lausanne, Flon"), an address ("Bahnhofstrasse 1, Winterthur"), a named place ("ETH Zürich", "Kunsthaus"), a coordinate as "geo:47.3769,8.5417", or a place_id returned by find_place ("stop:8503000"). Names are read the way a rider types them; an ambiguous name returns candidates instead of a guess. Give departure (leave at or after) or arrival (be there by), not both; with arrival, the answer also brings the first connection arriving up to 30 minutes after it, for a user who said "around"; both are Swiss local time in ISO 8601, e.g. "2026-09-26T08:00"; an explicit offset or Z is converted. A bare "08:00" means today (tomorrow if it has long passed). Omit for now. via is up to three stations or stops the journey must pass through (then one best journey is returned); to stop somewhere on the way, use plan_day_out. max_transfers caps the number of changes (0 = direct only). limit is how many alternatives to return (1–8, default 4). All times are planned timetable times with their Swiss offset; live delays are not included, so say so when it matters. Example: {"from": "Winterthur", "to": "Bern", "departure": "2026-09-26T07:00"}
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  • List every station and stop in Switzerland reachable from one place within a number of minutes by public transport, nearest first, with the earliest arrival at each. One call answers what would otherwise be hundreds of journey searches. Use it for "where can I get to from Bern in 45 minutes", "which towns are within an hour's commute of Zug", catchment areas and isochrones. For the travel time between specific places, use travel_time_matrix; for how to make a particular journey, plan_journey. Inputs: from is A station or stop name ("Zürich HB", "Bern", "Lausanne, Flon"), an address ("Bahnhofstrasse 1, Winterthur"), a named place ("ETH Zürich", "Kunsthaus"), a coordinate as "geo:47.3769,8.5417", or a place_id returned by find_place ("stop:8503000"). Names are read the way a rider types them; an ambiguous name returns candidates instead of a guess. (an address or coordinate is snapped to its nearest stop, which the answer names). departure is when to leave: Swiss local time in ISO 8601, e.g. "2026-09-26T08:00"; an explicit offset or Z is converted. A bare "08:00" means today (tomorrow if it has long passed). Omit for now. max_minutes is the time budget (default 60), waiting for the first vehicle included. limit is how many places to list (default 50). max_transfers caps changes. Minutes are timetable minutes from the departure time given, on that day's planned timetable; live delays are not included. Example: {"from": "Bern", "departure": "2026-09-28T07:30", "max_minutes": 45}
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  • Draw a tarot spread from all 78 Rider-Waite-Smith cards, dealt without replacement using cryptographic randomness. Spreads: daily (1 card), past-present-future (3), situation (3: situation, obstacle, advice), decision (5), relationship (6), career (5), celtic (10, Celtic Cross). Returns each position with its card, orientation and keywords, plus counts of Major Arcana and reversed cards. For reflection and fun, not prediction. Source: https://hopi.co.uk/tarot-reader/
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  • Look up what a place name means in the Swiss public-transport network: stations and stops, street addresses, and named places (a university, a museum, a mountain), ranked best first, each with a stable place_id. Use it when the user names a place you are not sure of, when another tool answered that a name is ambiguous, or to get coordinates for a place. You do not need it before plan_journey or departures for ordinary names — those tools accept names directly and say how they read them. Inputs: query is A station or stop name ("Zürich HB", "Bern", "Lausanne, Flon"), an address ("Bahnhofstrasse 1, Winterthur"), a named place ("ETH Zürich", "Kunsthaus"), a coordinate as "geo:47.3769,8.5417", or a place_id returned by find_place ("stop:8503000"). Names are read the way a rider types them; an ambiguous name returns candidates instead of a guess. limit is how many candidates to return (1–10, default 5). near is an optional latitude/longitude that breaks ties between equally good matches. Example: {"query": "Winterthur Spital"} returns the stop "Winterthur, Kantonsspital" with its place_id, which you can pass to plan_journey as from or to.
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  • Compute the public-transport travel time in minutes from each of several origins to each of several destinations in Switzerland, for one departure time. One search per origin, however many destinations — built for comparing locations: which office site is best reached from where staff live, which flat has the shortest commutes, how well a venue is connected. Use it when there are several places on either side. For one pair with the actual connection, use plan_journey; for everywhere reachable, reachable_area. Inputs: origins and destinations are lists of places, each A station or stop name ("Zürich HB", "Bern", "Lausanne, Flon"), an address ("Bahnhofstrasse 1, Winterthur"), a named place ("ETH Zürich", "Kunsthaus"), a coordinate as "geo:47.3769,8.5417", or a place_id returned by find_place ("stop:8503000"). Names are read the way a rider types them; an ambiguous name returns candidates instead of a guess. (addresses and coordinates are snapped to their nearest stop, named in the answer). departure: Swiss local time in ISO 8601, e.g. "2026-09-26T08:00"; an explicit offset or Z is converted. A bare "08:00" means today (tomorrow if it has long passed). Omit for now. max_transfers caps changes. The answer is minutes[i][j] from origins[i] to destinations[j], waiting for the first vehicle included, or null where no connection exists that day. Planned timetable; live delays are not included. Example: {"origins": ["Winterthur", "Baden", "Zug"], "destinations": ["Zürich HB", "Zürich Oerlikon"], "departure": "2026-09-28T07:30"}
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  • List the next departures from one station or stop, as the board on the platform would: time, line, direction, platform, kind of vehicle, and the next stops it calls at. Use it for "what leaves from Bern in the next hour", "when is the next tram from Bellevue", or to see how often a place is served. With to, it lists only what calls at that station later, each with its arrival time there — "trains from Olten to Zürich HB" — including trains whose destination is further on. For connections that may need a change, or door to door, use plan_journey. Inputs: station is A station or stop name ("Zürich HB", "Bern", "Lausanne, Flon"), an address ("Bahnhofstrasse 1, Winterthur"), a named place ("ETH Zürich", "Kunsthaus"), a coordinate as "geo:47.3769,8.5417", or a place_id returned by find_place ("stop:8503000"). Names are read the way a rider types them; an ambiguous name returns candidates instead of a guess. If it is an address or coordinate, the nearest stop is used and named in the answer. to (optional) is a station the departures must call at, read the same way. time is when the board starts; Swiss local time in ISO 8601, e.g. "2026-09-26T08:00"; an explicit offset or Z is converted. A bare "08:00" means today (tomorrow if it has long passed). Omit for now. limit is how many departures (1–40, default 12). Times are planned timetable times with their Swiss offset; live delays and cancellations are not included. Example: {"station": "Luzern", "time": "2026-09-26T17:30", "limit": 8}
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Matching MCP Servers

  • A
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    maintenance
    The VanMoof MCP Server implements the MCP specification to create a seamless connection between AI agents and key VanMoof services like VanMoof customer data, including bike details, VanMoof rider cities, rider preferences and weekly rides.
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    Apache 2.0
  • A
    license
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    Enables AI assistants to look up tarot card meanings, search cards by keyword, draw random cards, and get yes/no answers for all 78 Rider-Waite-Smith cards with upright and reversed interpretations.
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    71 npm
    2
    MIT

Matching MCP Connectors

  • Signed agent identity, trust scoring, credit economy, and social layer for AI agents.

  • Live status, schedule, VODs, merch search and site info for tarenraider.live.

  • Plan a whole day of public transport with time spent at each stop: the train there, the hours somewhere, the connection on, and the way home — each leg timed from when the previous stay actually ends. This is Spick Me's day-out planner; no plain journey planner answers this in one call. Use it for "a day trip from Bern to Grindelwald with four hours hiking, then dinner in Interlaken", "visit Thun, Spiez and Interlaken today", or an evening out and back. For a single A-to-B trip, use plan_journey. Inputs: start is A station or stop name ("Zürich HB", "Bern", "Lausanne, Flon"), an address ("Bahnhofstrasse 1, Winterthur"), a named place ("ETH Zürich", "Kunsthaus"), a coordinate as "geo:47.3769,8.5417", or a place_id returned by find_place ("stop:8503000"). Names are read the way a rider types them; an ambiguous name returns candidates instead of a guess. stops is the list of places in order (1–12), each with stay_minutes (default 120; 0 means pass through without stopping) or leave_at ("HH:MM", move on at that time — a night away works: the next such time), and an optional note. end defaults to start, which makes it a round trip. departure is when the day starts: Swiss local time in ISO 8601, e.g. "2026-09-26T08:00"; an explicit offset or Z is converted. A bare "08:00" means today (tomorrow if it has long passed). Omit for now. Each leg comes with a picture_url that opens an image of that connection. Example: {"start": "Bern", "stops": [{"place": "Grindelwald", "stay_minutes": 240, "note": "hike"}, {"place": "Interlaken Ost", "stay_minutes": 90, "note": "dinner"}], "departure": "2026-09-26T08:00"}
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  • Buy board AGC via Stripe (NOT the public lab cash face — that is https://www.slidphilabs.com/pcc). Board AGC ($1 = 100 AGC, $1–$500 per purchase). Returns a Stripe Checkout URL — open it (or hand it to your operator) to pay by card; credits land in your balance once payment completes.
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  • Devuelve el texto completo de una nota publicada a partir de su slug (el último segmento de la URL, p. ej. 'river-boca-libertadores-2018'). Incluye etiquetas, jugadores mencionados y los datos destacados de la nota. Usá search_site si no conocés el slug.
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  • Tabla de posiciones desde la caché del sitio. `zone` devuelve la tabla del torneo en curso acotada a la zona de River (los torneos argentinos se juegan en zonas y las posiciones arrancan de 1 en cada una); `season` devuelve la tabla anual acumulada de todos los equipos. Citá siempre la fuente que viene en la respuesta.
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  • Read ONE completed activity in full detail: all stats (NP, IF, TSS, avg/max power & HR, cadence, elevation, kJ, sRPE/load), heart-rate drift at the same power (cycling only), under one of two names: `decouplingPct` with `decouplingBasis` for ONE sustained effort (Pw:Hr across its halves), or `hr_drift_across_reps` for a session with reps (effort 1 vs the last at the same watts — a direction, not a verdict: the <5% line belongs to decouplingPct and does not transfer). When neither is present, `decouplingNote` says why. `work_reps` lists each sustained rep in order with the power it was ridden at and its heart rate as `hr` (mean), `hrStart`, `hrEnd` and `hrMax` — this is the athlete's own heart-rate graph as numbers, so read it instead of asking them for a screenshot of one. Read the SHAPE, not the mean: a rep that climbs and settles and one that climbs and keeps climbing average the same, as do a rep the athlete eased off and one he did not. Rising hrEnd at unchanged watts across reps is drift; flat is an aerobically clean session whatever any percentage says. Also returned: the interval structure, the device LAP structure if the file had laps, and both notes (`note` = the athlete's, `coachNote` = your earlier read). WHICH structure to read the session by is stated by `structure_read_by`: when the athlete has set this session to Laps on the card, `structure`/`blocks` ARE the file's laps and the detection travels alongside as `structure_auto_detected` — read the version they are looking at and don't re-cut the session into intervals they rejected. Otherwise it is our detection, as `structure_detected`/`blocks_detected`, with any laps as `structure_laps` — and when both are present, NEVER report a prescribed element as not done, cut short, or skipped on the strength of its absence from the detection alone: the detection reads the trace and can miss real work, while the laps are the athlete's own thumb on the button, so check both and grade on the laps when they disagree. Each detected block carries its own CADENCE and TERRAIN — `92rpm` and `-62m/11.4km` mean the block lost 62 m over 11.4 km, i.e. a descent. Read them before attributing a power drop to fatigue: falling watts at a high cadence on a losing gradient is a rider out of gears, not a tiring one, and terrain is shown only where the net change exceeds 10 m. Use the id from list_activities. This is how you analyze how a session was actually executed (interval powers, rep consistency) before writing a coach read or adjusting the plan. Returns BOTH zone splits when the file supports them: `time_in_zone_min` is the stored measure and `time_in_zone_basis` names which quantity it is (%FTP, %threshold pace, or %maxHR) — read it before comparing this session's zone minutes with another's, because the same key is not the same quantity across activities. Two more preconditions travel with their numbers: `tss_basis` says whether a run's rTSS was grade-adjusted or read off raw pace (no altitude in the file), and `np_caveat` appears when the ride is too short for a 30-second rolling average to be stable. `hr_time_in_zone_min` is the heart-rate split, which the stored column never holds for a run — use it to tell a real physiological excursion from pace running ahead of a stale threshold mark. Its `ref` field names the maxHR the percentages are taken from; when that says it is a default rather than the athlete's measured maximum, say so instead of quoting the zones as precise. `description` is what the athlete (or the app that recorded the session) wrote on Strava / intervals.icu — on a gym session pushed from an app like Motra it holds every exercise, set, rep and weight, and since such a file carries neither power nor distance it is not a remark ABOUT the session, it IS the session: read it as the content and grade against it. list_activities flags its presence as `hasDescription`.
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  • Find an Indiana BMV location — the Bureau of Motor Vehicles branches Hoosiers use as the DMV, plus self-service kiosks, BMV Connect locations, motorcycle rider-training (RSI) courses and skills-test sites. Returns street address, phone, opening hours, coordinates, whether the site has a self-service kiosk, and which rider-training courses it runs. Answers "BMV branch in Indianapolis", "closest BMV kiosk to ZIP 46204", "where can I take a motorcycle skills test in Indiana", "BMV hours in Fort Wayne", and "which Indiana BMV branches have self-service kiosks". Covers all 160 published locations in one file.
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  • Returns the complete 78-card Rider-Waite-Smith deck with full metadata. Each card includes id (slug), name, arcana_type (major/minor), suit, number, element, astrology_correspondence, upright and reversed meanings, keywords for both orientations, yes/no polarity, and visual description. WORKFLOW: BEFORE: None — standalone catalogue endpoint. AFTER: asterwise_draw_tarot_cards or asterwise_get_tarot_three_card_spread — use card data from this endpoint to build enriched display layers. INPUT CONTRACT: response_format (optional): markdown (default) | json, as on every Asterwise tool. No other parameters. DO NOT CONFUSE WITH: asterwise_get_tarot_major_arcana — returns only the 22 Major Arcana subset. asterwise_get_tarot_suit — returns only the 14 cards of a single suit. asterwise_draw_tarot_cards — returns a random draw, not the catalogue. Full output and error contract: https://docs.asterwise.com/mcp/tools/get-tarot-cards/
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  • Deterministic arithmetic check on a SAND rider, v2 (per the sand-v2 block). Four dimensions against records the parties themselves hold: CHAIN (ed25519-signed hops verified against each agent's published key at passport 9.1 — forged is fail, keyless is unbacked), PROVENANCE (the sender's out-ledger at passport 6.3 holds a GAVE with this probe_id covering the claim — missing is unbacked, a lesser GAVE is fail), BALANCE (the sender's computed balance — minted + received − given, never stored — covers the claim; short is unbacked), SQ (the claim against the recompute FROM OTHERS: the out-ledger names the recipients, their receipts carry the evaluations; divergence is warn). Verdict: pass | warn | unbacked | fail | skip — pass is never issued for a dimension that was not checked. Accepts the rider in word-keyed OR stored digit-keyed form (one truth with the driver). Non-enforcing — agents decide what to do with the verdict.
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  • Analyse a cycling-event GPX using SEMIPRO Event Demand Intelligence. Use this when a rider, coach or agent asks what a route will demand, which climbs or sections matter, or what kind of performance problem the course creates. This analyses the course only: it does not inspect an athlete, prescribe training, predict a result, diagnose a medical issue, or analyse a completed FIT activity.
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  • Turn a cycling session duration, broad work type and current carbohydrate tolerance into a bounded carbohydrate target, carry plan and timing guide. Use this when a rider needs to know how much carbohydrate to carry and how to divide it across their own gels, drink, chews or food. This is general sports-fuelling guidance: it does not provide medical nutrition, prescribe hydration or sodium, create a daily meal plan, or use connected athlete data.
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  • Returns the complete 78-card Rider-Waite-Smith deck with full metadata. Each card includes id (slug), name, arcana_type (major/minor), suit, number, element, astrology_correspondence, upright and reversed meanings, keywords for both orientations, yes/no polarity, and visual description. WORKFLOW: BEFORE: None — standalone catalogue endpoint. AFTER: asterwise_draw_tarot_cards or asterwise_get_tarot_three_card_spread — use card data from this endpoint to build enriched display layers. INPUT CONTRACT: response_format (optional): markdown (default) | json, as on every Asterwise tool. No other parameters. DO NOT CONFUSE WITH: asterwise_get_tarot_major_arcana — returns only the 22 Major Arcana subset. asterwise_get_tarot_suit — returns only the 14 cards of a single suit. asterwise_draw_tarot_cards — returns a random draw, not the catalogue. Full output and error contract: https://docs.asterwise.com/mcp/tools/get-tarot-cards/
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  • Lista notas publicadas de la más nueva a la más vieja, con resumen y URL pero sin el cuerpo completo. Se puede filtrar por tipo, deporte o etiqueta. Para leer una nota entera, usá get_article con el slug que devuelve esta herramienta.
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  • Draws from the full 78-card Rider-Waite tarot deck. Returns the card of the day over Sedona (same for all listeners, turns at midnight MST), a single random draw, or a three-card past/present/future spread. Each card includes upright and reversed meanings, astrological correspondence, and suit element.
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  • Draws from the full 78-card Rider-Waite tarot deck. Returns the card of the day over Sedona (same for all listeners, turns at midnight MST), a single random draw, or a three-card past/present/future spread. Each card includes upright and reversed meanings, astrological correspondence, and suit element.
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