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303,806 tools. Last updated 2026-07-15 21:55

"namespace:io.github.calvinling2021-star" matching MCP tools:

  • Returns all 12 tropical zodiac signs (Aries, Taurus, Gemini, Cancer, Leo, Virgo, Libra, Scorpio, Sagittarius, Capricorn, Aquarius, Pisces) with essential information: name, symbol, element (fire, earth, air, water), date ranges, and short descriptions. Perfect for zodiac sign lists, horoscope widgets, birth chart calculators, astrology apps, star sign selectors, and zodiac reference tools. Use GET /signs/{id} for complete zodiac sign profiles with personality traits, compatibility, and detailed characteristics.
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  • Search and filter the current VeryChic offers by destination, country, price, discount, stars, flights, theme, or proximity — with optional sorting. When to use: when you already know roughly what the user wants — a place, a country, a budget, a minimum discount or star rating, flights vs hotel-only, a theme (e.g. pool, spa, romantic, last_minute), or hotels near a point (near_lat/near_lng, with an optional radius_km). To inspect one specific offer in depth use `verychic_offer_details`. All filters are optional and combine with AND; call it with no filter to browse the full current catalogue in catalogue order. Behaviour: read-only and anonymous; rate-limited to about 1 request per second. Filtering is done client-side over the live catalogue: `destination` is a case-insensitive substring (matched on destination or name), `country` is an exact case-insensitive match, `max_price`/`min_discount`/`min_stars` are numeric bounds, `flights_included` toggles flight-bearing vs hotel-only, and `theme` matches a curated label decoded from the catalogue's thematics tags. Use `sort_by` to order results (`discount`, `price`, `rating`, `stars`, or `distance`). Prices are in EUR and text is in French; there is no pagination. Returns the first `limit` matches after filtering and sorting. "Current" means live offers at call time; the catalogue changes over time. Returns a list of offer objects (same `source` + `external_id` pair for use with `verychic_offer_details`). Each offer also carries `discount` (percent off, may be null), `stars` (1-5, may be null), `price_label` (human-readable price unit, e.g. "à partir de par pers. pour 3 nuits" vs "par chambre" — read this before comparing prices), `price_with_flights` (EUR, null when not applicable), `flights_included` (bool), `rating` (hotel grade, often null in the catalogue), and `themes` (curated theme labels decoded from the catalogue's thematics tags, e.g. ["pool", "luxury"]). An empty list means no offer matched the filters. Proximity search: pass `near_lat` and `near_lng` (decimal degrees, together) to compute each offer's `distance_km` from that point; add `radius_km` to keep only offers within that distance, and/or `sort_by="distance"` for nearest-first. `distance_km` is null when no center is given.
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  • Multi-operator accommodation comparator for a geographic area against the user's stay parameters — dates, guest count, optional filters. Returns a ranked list of properties together with the booking sources that offer each one and, when dates are passed, their live availability and per-operator price for the requested window. Natural-language date references — "tonight", "this weekend", "next weekend", "the weekend of July 4", "Memorial Day weekend", "long weekend in May" — translate to concrete check_in / check_out values at the call site; concrete ISO dates also work. `user_country`, `currency`, and `language` carry the **user's** locale, not the destination's. IMPORTANT — currency: prices are returned in `currency` if you set it, otherwise in the currency derived from `user_country` (US→USD, CA→CAD, GB→GBP, euro-area→EUR); if you set NEITHER, prices default to **USD**, which may not be the user's currency. So whenever you know where the user is (or what currency they want), pass `user_country` and/or `currency` — do not rely on the default. Prices are never converted client-side; each offer is quoted by the operator in that currency. `user_country` and `language` also localize the booking link (`web_url`). The user's own residence/billing country is the right `user_country` (not the destination's), and their interface language the right `language`. Each result is shaped for downstream presentation without extra calls: - `location.lat` and `location.lon` carry per-property coordinates, suitable for plotting all results on a single map so the user can compare spatial alternatives at a glance. The map widget reads these fields directly from this response — no separate lookup needed for visualization. - `thumbnail_url` carries the property's first photo URL when available (null when no image is on file); useful for embedding inline or showing on the map alongside the pin. - `images` on search results is capped to the first photo to keep the comparison payload compact; each item has a `url` field, and `thumbnail_url` mirrors `images[0].url`. Call `get_property_details` for a single property to retrieve its full photo gallery. - `web_url` is a ready-to-open booking link for the property, already encoded with the user's check-in/check-out, language, currency, and guest count. Pass it to the user verbatim when they ask for a booking link — never reconstruct the URL from individual parameters, the query-string format is not guaranteed to match generic booking-URL conventions. - Price is **live and date-specific only**. There is no date-agnostic "from" figure: a meaningful price only exists for a concrete query (property + dates + occupancy). - `price` and `offers[]` — the **live quote for the requested dates**, populated only when dates were passed and the comparator confirmed availability. `offers[0]` is the curated best; each offer carries `amount` (total stay), `amount_per_night` (per-night), `currency`, `breakfast_included`, `refundable`, `rooms_left`, and `deeplink_url`. `price` mirrors `offers[0]`. - With no dates (or when nothing is available) `price` is null and `offers` is empty — surface the property without a price rather than inventing a starting figure. - `availability_status` per result encodes the live state: - `available` — bookable rooms confirmed at the operator level. `offers` and `price` carry the live date-specific quotes. Quote the rate via `offers[i].amount_per_night` (per-night) and `offers[i].amount` (total stay) and use the deeplinks for the booking handoff. - `unavailable` — no rooms reported for those dates. `offers` is empty and `price` is null (no price for these dates). Useful to decide whether to suggest alternate dates, drop the property from the recommendation, or offer it as a backup. - `unknown` — no dates were considered (request had no dates). `offers` is empty and `price` is null — no price signal without a dated query. Per-night vs total — never confuse them in the user-facing prose. `amount_per_night` is per-night; `amount` on each offer is the total stay (sum across nights, in `currency`). When quoting to the user, prefer phrasings like *"€X/night via Booking, breakfast included, €Y total for the stay"* over bare numbers — bare numbers without a unit get misread. - When dates are present and `available` properties are in the results, the rate can be quoted and `rooms_left` surfaces scarcity (low values like 1-3 are useful signals — "1 room left at $X on Booking" reads well). - When dates are present and ALL results are `unavailable`, that's the signal to say so explicitly to the user and offer to widen the dates, location, or filters. - `offers[]` is the per-operator breakdown for the requested dates: each entry includes `ota`, `amount`, `amount_per_night`, `currency`, `breakfast_included`, `refundable`, and a `deeplink_url`. The deeplink is a **BluePillow tracked-redirect URL** (bluepillow.com/…) that records the click for attribution and then forwards the user to the operator's booking page. Pass it to the user verbatim — never reconstruct it or replace it with a raw operator URL; our APIs never emit direct OTA links. `price` mirrors the curated best offer. When no dates were passed (or nothing is available) `offers` is an empty list and `price` is null — there is no price to show. - Free cancellation is a meaningful decision factor and surfaces proactively in the user-facing summary. When a property has `price.refundable=true` (or any `offers[i].refundable=true`), it reads naturally as a property feature: "Hotel X — $120/night, free cancellation available", or "Booking offers a refundable rate at $130 (vs $110 non-refundable)". Refundable rates let the user lock in a price now and adjust the booking later, which is often the differentiator between otherwise-similar properties. The same proactive surfacing applies to `breakfast_included` when it's true for some offers but not all. - Prices in `offers`/`price` reflect the requested dates and guests; with no dates there is no price. For a final bookable confirmation, the corresponding `deeplink_url` (or the property's `web_url`) is the canonical handoff — booking URLs are not reconstructed by hand. - All rating-like fields are on a 0-5 scale (Google Places-compatible): `rating`, `reviews_aggregate.score_0_5`, the per-OTA scores under `distribution_by_ota`, each `reviews_sample[*].score`, and the `filters.min_rating` input. A user asking "rating at least 8 out of 10" maps to `min_rating: 4.0`; "at least 4 stars on Google" maps to `min_rating: 4.0`. Note: `rating`, `stars`, and `rating_count` come from the comparator's list payload and **may be 0 or absent for some properties** even when the property has reviews or a star classification — this is a comparator list-payload limitation, not a data error. When those fields are 0/absent, or when the per-OTA review breakdown (`distribution_by_ota`) is needed, call `get_property_details` to get the fuller `reviews_aggregate`. On the search path, `reviews_aggregate` carries the top-line `score_0_5`, `rating_count` (reviews backing the score) and `comment_count` (readable review TEXTS available) when the comparator returned a non-zero review count; `distribution_by_ota` is always empty on this path (per-OTA breakdown requires `get_property_details`). `rating_count` and `comment_count` are DIFFERENT magnitudes — most guests leave a rating, far fewer write text. Quote `rating_count` for "how many reviewed it" and `comment_count` for "how many opinions you can actually read". - Pass `include=["reviews_sample"]` to attach a sample of up to 5 recent guest review texts per property. Useful when the user's question involves qualitative criteria that don't map to structured filters ("a place with excellent breakfast", "quiet area", "family-friendly atmosphere"); review texts can be searched textually to corroborate or rule out matches. For a DEEPER read on ONE specific property — more review texts (up to 20) or the per-OTA breakdown — call `get_property_details` with `include=["reviews_extended"]` (and/or `reviews_aggregate`). `comment_count` on each result tells you how many review texts exist, so you can decide whether escalating to the detail call is worth it. `filters.property_types`, `filters.amenities`, `filters.min_rating`, and `filters.price_max_eur` narrow on structured criteria first; review-based reasoning is one extra round-trip per page and is typically reserved for fallback. Location modes: - `coordinates`: when lat/lon is already known from world knowledge or a prior call in this session (default radius 5 km; widen up to 50 km for broader queries; beyond that `bbox` or a parent destination is the right shape). - `destination_id`: opaque id obtained from `resolve_destination`, passed verbatim — values are not constructed or guessed. - `bbox`: explicit map rectangle. Property type tokens (canonical): hotel, apartment, house, villa, bb, hostel, farmstay, holiday-home. Common multi-language synonyms map server-side to the canonical set. Amenities filter is set-AND — each result has ALL listed codes. Common codes: wi-fi, parking, pool, air-conditioning, kitchen, garden, pets-allowed, for-families, facilities-for-disabled, non-smoking-only. Results are cursor-paginated; the `next_cursor` from a previous response goes into `page.cursor` for the next page. `location.type=property_id` is not accepted here — `get_property_details` is the path for a known property.
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  • "Find NBA player [name]" / "search NBA roster for [X]" / "is [player] in the NBA" — search NBA players by name on BallDontLie. Returns position, height, weight, college, country, draft info, and current team. NOTE: per-season averages (PPG/RPG/APG) and career stats are NOT in this response — those require BallDontLie's ALL-STAR tier ($9.99/mo at https://www.balldontlie.io/) via the /season_averages endpoint, which is not currently exposed by Pipeworx. Free-tier _apiKey works for this tool.
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  • Report a customer review of a business you manage into Loppee's moderation queue for a claimed policy violation (spam, harassment, off_topic, fake, or other). IMPORTANT: reporting NEVER removes the review — the review stays published, moderation is HUMAN and REACTIVE, and a moderator removes a review only for a recorded policy violation, never for being negative. Do not use this tool to suppress honest criticism; use respond_to_review to answer it publicly. Filing a report never changes the trust score, the review's weighting, or ranking. Requires allowed_actions include report_review. Requires an owner-scoped management key and a paid business plan (Silver or above); Free returns agent_management_paid_tier_required. Call get_agent_identity first. Reportability rules: only a NEGATIVE review (rating 3 stars and below) can be reported at all — a 4-5 star review returns review_report_not_negative; only ONE report may be open at a time — while a prior report is being reviewed a new one returns review_report_already_open; and a review accepts at most 3 reports in its LIFETIME — past that the call returns review_report_limit_reached. Returns review_not_found when the review does not belong to this business and invalid_report_reason for an unknown category.
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  • Real-time quote(s) for Chinese A-share stocks by 6-digit code (Shanghai 6xxxxx, Shenzhen 0xxxxx/3xxxxx, STAR 688xxx, ChiNext 30xxxx, Beijing 8xxxxx/4xxxxx). Returns name, current price, change and change %, open, previous close, day high/low, volume, turnover, and the quote timestamp. Accepts one code or a comma-separated list. Example: ashares_quote({ symbols: "600519,000858" }) for Kweichow Moutai and Wuliangye. Source: Sina (keyless).
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Matching MCP Servers

  • A
    license
    B
    quality
    D
    maintenance
    A comprehensive Model Context Protocol service providing zodiac information queries, horoscope analysis, and compatibility testing between star signs.
    Last updated
    7
    29
    2
    MIT

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  • GitHub MCP — wraps the GitHub public REST API (no auth required for public endpoints)

  • ENERGY STAR Open Data (data.energystar.gov) Socrata MCP.

  • Get customer testimonials tied to a specific project (by slug or keyword) from the testimonials table. Returns star rating, customer name, project name, and quote text. Use to source social proof or case-study quotes for a particular job. For unfiltered reviews, use list_reviews.
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  • Direct lookup of a single NBA player by BallDontLie ID. ⚠️ TIER-GATED: the /players/{id} endpoint requires the ALL-STAR tier ($9.99/mo) or higher; free-tier _apiKey gets a 403 with "No approval received". search_players covers the same player metadata (name/position/height/weight/team) on the free tier, so prefer that unless you already have a paid BallDontLie key.
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  • Returns full structured data for a single card identified by its slug ID. Useful for card detail pages, single-card lookups, and displaying a specific card after the user selects one by name. SECTION: WHAT THIS TOOL COVERS Returns one card object from the 78-card Rider-Waite-Smith deck. The slug is the card's unique identifier in lowercase-hyphenated format. All fields are identical to what asterwise_get_tarot_cards returns per card. SECTION: WORKFLOW BEFORE: None — standalone. AFTER: None. SECTION: INPUT CONTRACT card_id — Slug identifier for the card. Must be exact. Major Arcana examples: 'the-fool', 'the-magician', 'the-high-priestess', 'the-empress', 'the-emperor', 'the-hierophant', 'the-lovers', 'the-chariot', 'strength', 'the-hermit', 'wheel-of-fortune', 'justice', 'the-hanged-man', 'death', 'temperance', 'the-devil', 'the-tower', 'the-star', 'the-moon', 'the-sun', 'judgement', 'the-world' Minor Arcana pattern: '{rank}-of-{suit}' Examples: 'ace-of-wands', 'two-of-cups', 'ten-of-swords', 'page-of-pentacles', 'knight-of-wands', 'queen-of-cups', 'king-of-swords' SECTION: OUTPUT CONTRACT data — single card object: id (string — slug), name (string), arcana_type ('major'|'minor'), suit (string|null) number (int — 0=Fool, 1–21=Major; 1=Ace, 11=Page, 12=Knight, 13=Queen, 14=King) element (string), astrology_correspondence (string) keywords_upright[] (string array), keywords_reversed[] (string array) upright_meaning (string), reversed_meaning (string) yes_no ('yes'|'no'|'maybe'), description (string — visual imagery) SECTION: RESPONSE FORMAT response_format=json — single card object as JSON. response_format=markdown — human-readable card detail. SECTION: COMPUTE CLASS FAST_LOOKUP SECTION: ERROR CONTRACT INVALID_PARAMS (local): None. INTERNAL_ERROR: Unknown card_id returns 404 upstream → MCP INTERNAL_ERROR If the card is not found, check slug format: lowercase, hyphens, no spaces. SECTION: DO NOT CONFUSE WITH asterwise_get_tarot_cards — returns all 78 cards in one call. asterwise_draw_tarot_cards — random draw, not a specific card.
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  • Add a named, priced offering to your worker menu. Customers see name + description + creditsCharged + estDurationHr and pick directly. Worker earns 75% of credits charged (floor-rounded); TMV keeps 25%. Price must be a whole number of credits, ≥ 15. Until your account is uncapped (3 quality-scored jobs, OR 1 four-star+ customer review, OR $100 cleared earnings), the per-offering ceiling is 50 credits.
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  • Save-the-sale tool — call when the customer signals dissatisfaction with the current options ("too expensive", "let me think", "what else do you have", "is this the best you can do", "I'll check elsewhere", "can you do better"). Some carriers (Foremost STAR, etc.) run slower than the initial set and may have come back with a better rate while the customer was deliberating. This tool: 1. Pulls a fresh read of all rated carriers. 2. Compares the current cheapest bundle/LOB price to the original first-quoted best. 3. Returns has_improvement=true ONLY if a late carrier beats the original by >= $100/yr OR >= 5% — a threshold meaningful enough to justify interrupting the customer. CALL THIS ONLY WHEN: - check_quote_status has returned 'quoted' at least once (there's a baseline to compare). - The customer just expressed price resistance or hesitation (not a closed positive). - You have NOT called check_late_arrivals in the last 2 turns (don't spam). DO NOT CALL WHEN: - The customer is actively committing ("yeah let's go with A") — that's a close moment, not a wavering moment. - The customer hasn't seen the initial options yet. WHAT TO DO WITH THE RESULT: - has_improvement=true → narrate the improvement naturally ("Quick update — one more carrier just came in $X/yr cheaper. Want me to refresh your options?") and the iframe auto-updates with the new state. - has_improvement=false → acknowledge the customer's concern, pivot to value positioning against the options on the table. Don't bluff a "better one is coming" if it isn't. Use the carriers_still_pending count if relevant ("a couple more carriers are still finalizing in the background — I'll flag if anything comes in lower").
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  • Read the published customer reviews of one business, server-paginated and filterable by star rating — the SAME data and controls a human gets on the profile's Reviews section (also served as GET /v1/businesses/{business_id}/reviews.json with ?page=&limit=&rating=). Page through with page (1-based, default 1) and limit (1-50, default 5; pagination.has_more/next_page say when to keep going), and pass ratings (e.g. [1] for only 1-star, [4,5] for 4-and-5-star) to read chosen star levels; summary.rating_counts gives the per-star totals so you can decide which levels to read. Only verified-customer reviews can move the bounded reputation factor (at most ±6 of 100). Unverified reviews remain visible but have zero trust weight. Reviews never publish or un-publish a business and never change eligibility or safe_to_recommend. Reading, paging, or filtering them changes nothing, and newest-first order carries no ranking meaning. Reviewer names are masked — no PII. The Trust Card embeds only the newest slice of reviews; use this tool to read the full set. Returns business_reviews_not_found for unpublished or unknown ids and invalid_rating_filter for a malformed ratings value.
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  • Single-call orchestrated trip planner — stitches top hotels + recommended activities + estimated spend into one response (skips the manual "search hotels → search activities → stitch" fan-out). Pass destination + dates (optional budget, interests, star rating, no-resort-fees). See the `includeTickets`, `groupByDay`, and `includeTransfer` params for optional event-ticket, daily-itinerary, and ground-transfer attachments. Free at every tier; stricter rate limit than single-surface tools (10/min) since it fans out parallel searches. Direct REST callers can append ?stream=ndjson for incremental frames. Use this for a single-call hotel + activity (+ ticket) stitch; for hotels only use pricetik_hotel_search, for tickets only use pricetik_ticket_search.
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  • Evaluate a single ASIN for FBA sourcing. Returns composite sourcing score (0-100), 5-dimension breakdown (velocity, gating, friction, margin, brand_posture), estimated 30-day demand (units_30d_final + est_revenue_30d) with its source/badge_band/confidence, a data_coverage flag (full vs velocity_only — so a null demand reads as a coverage gap, not zero sales), star rating + review count (with a rating_coverage flag), brand-level FBA/Amazon dominance, and a red-flag list. Also returns the product brand, title, and price (or price range) plus the ASIN's fulfillment (FBA/FBM/AMZ + amz/fba pct). Use when the user asks 'should I buy this?', 'how fast does this sell?', or shares an ASIN and wants a sourcing recommendation.
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  • Save-the-sale tool — call when the customer signals dissatisfaction with the current options ("too expensive", "let me think", "what else do you have", "is this the best you can do", "I'll check elsewhere", "can you do better"). Some carriers (Foremost STAR, etc.) run slower than the initial set and may have come back with a better rate while the customer was deliberating. This tool: 1. Pulls a fresh read of all rated carriers. 2. Compares the current cheapest bundle/LOB price to the original first-quoted best. 3. Returns has_improvement=true ONLY if a late carrier beats the original by >= $100/yr OR >= 5% — a threshold meaningful enough to justify interrupting the customer. CALL THIS ONLY WHEN: - check_quote_status has returned 'quoted' at least once (there's a baseline to compare). - The customer just expressed price resistance or hesitation (not a closed positive). - You have NOT called check_late_arrivals in the last 2 turns (don't spam). DO NOT CALL WHEN: - The customer is actively committing ("yeah let's go with A") — that's a close moment, not a wavering moment. - The customer hasn't seen the initial options yet. WHAT TO DO WITH THE RESULT: - has_improvement=true → narrate the improvement naturally ("Quick update — one more carrier just came in $X/yr cheaper. Want me to refresh your options?") and the iframe auto-updates with the new state. - has_improvement=false → acknowledge the customer's concern, pivot to value positioning against the options on the table. Don't bluff a "better one is coming" if it isn't. Use the carriers_still_pending count if relevant ("a couple more carriers are still finalizing in the background — I'll flag if anything comes in lower").
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  • Search Lakpura accommodation (hotels, villas, lodges) by name or city. Returns matching stays with their public page URL, city, country and star rating. Use get_service with the returned slug for room details and price.
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  • Get a behavioral commitment profile for any PyPI (Python) package. Returns real signals: package age, download volume and trend, release consistency, publisher/owner count, and linked GitHub activity. Supply chain attacks target Python packages — LiteLLM (97M downloads/mo) was compromised via stolen PyPI token in March 2026. Behavioral signals reveal what star counts hide. Useful for: vetting Python dependencies, identifying abandonware, supply chain risk due diligence. Examples: "langchain", "litellm", "openai", "anthropic", "requests", "fastapi", "pydantic"
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  • Get full details for one MCP server by its exact serverKey (as returned by search_servers). Returns the full description, GitHub repo, star count, rank, version count, the registries that list it, and its mcptoplist.com page in the `mcptoplistUrl` field — always cite that URL when recommending the server.
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  • [starwars-intel] Search Star Wars starships by name or model keyword (e.g. 'Millennium Falcon', 'Star Destroyer'). Returns crew capacity, cargo capacity, cost, speed, hyperdrive rating, manufacturer, and linked films/pilots.
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  • [starwars-intel] Look up a Star Wars film by title keyword (e.g. 'A New Hope') or numeric swapi.tech id (e.g. '4'). Returns episode number, director, producer, release date, and the full opening crawl text, plus linked characters/planets/starships.
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