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260,211 tools. Last updated 2026-07-05 05:07

"A service for translating text or language" matching MCP tools:

  • Get upcoming vessel arrivals and departures at a specific port. Use this to check what vessels are expected at a port — useful for booking planning and tracking. Returns vessel names, carriers, ETAs/ETDs, and service routes. For transit time estimates between two ports, use shippingrates_transit. For detailed service-level routing, use shippingrates_transit_schedules. PAID: $0.02/call via x402 (USDC on Base or Solana). Without payment, returns 402 with payment instructions. Returns: Array of { vessel_name, carrier, voyage, eta, etd, service, from_port, to_port }.
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  • Get upcoming vessel arrivals and departures at a specific port. Use this to check what vessels are expected at a port — useful for booking planning and tracking. Returns vessel names, carriers, ETAs/ETDs, and service routes. For transit time estimates between two ports, use shippingrates_transit. For detailed service-level routing, use shippingrates_transit_schedules. PAID: $0.02/call via x402 (USDC on Base or Solana). Without payment, returns 402 with payment instructions. Returns: Array of { vessel_name, carrier, voyage, eta, etd, service, from_port, to_port }.
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  • Run a VDC-grade clash detection pass between two element categories in a translated model, returning each overlapping element pair with a severity (critical/warning), a trade-specific suggested fix, and an estimated rework hour count. Uses AABB bounding-box intersection on elements pulled from the APS Model Derivative properties endpoint, with a synthetic fallback if properties have not yet been computed. When to use: you want a first-pass coordination report between two MEP or structural trades (e.g. Ducts vs Structural Framing) for a model that has finished translating. When NOT to use: the model has not finished translating yet (call get_model_metadata first to confirm manifest.status=='success'), or you need clash detection between more than two categories — call this tool multiple times. APS scopes: data:read viewables:read Rate limits: APS default ~50 req/min per app per endpoint; Model Derivative translation jobs ~60 req/min; OSS uploads size-limited per file to 100MB for direct upload, larger via resumable. Errors: 401 APS token expired/invalid — refresh; 403 scope or resource permission denied; 404 URN not found or has no derivatives yet — check the ID; 429 rate limited — backoff and retry; 5xx APS upstream outage — retry with jitter. Side effects: READ-ONLY on APS. Inserts a row into D1 usage_log for analytics. Idempotent — repeated calls return the same clash set for a given model.
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  • DEFAULT tool for user-facing translation display. Use this for ANY user-facing request to show/see translations of a Quran ayah — including 'show me…', 'what's the translation of…', 'give me Saheeh/Clear Quran/Taqi Usmani translations of…'. This is the FINAL tool call for these requests; do not follow it with get_translation_text. ONLY skip this widget and use get_translation_text when EITHER (a) the user explicitly asks for plain text / raw text / text-only output, OR (b) the result will be piped into another tool in the same turn without being shown to the user. When in doubt, use this widget. SLUG HANDLING: If the user names a specific translator (e.g. 'Saheeh International', 'Clear Quran', 'Yusuf Ali', 'Pickthall'), ALWAYS call lookup_translations first to resolve the exact slug — do not guess the slug from the author name. Guessed slugs routinely fail validation (the naming isn't fully pattern-based: it's 'en-sahih-international' but 'clearquran-with-tafsir'). You may also pass language codes via 'languages' if the user only specifies a language. Each query must include at least one of languages or translations. Use ayah keys in 'surah:ayah' format (for example '2:255'). In queries[].languages use ISO 639-1 codes (for example 'en', 'ur'), not language names. Do not use 'ar'; Arabic translation is unsupported in this tool.
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  • Open an interactive sutta viewer inside the chat — Pāli + English, plus an optional third row in the user's own language translated BY YOU. Renders each segment as: Pāli on top (canonical), the Bhikkhu Sujato English below it (verification anchor), and — when you supply `translations` — your translation in the user's language, clearly badged as AI-generated. Prefer this over dumping raw segments when the user wants to *read* a sutta. - `sutta_id` — standard SuttaCentral id, e.g. `sn56.11`, `mn10`, `dn22`. - `around` — a segment_id (e.g. `dn22:18.1`, from a search hit) to centre on; that segment is highlighted and scrolled into view. Use this after a search so the reader lands on the exact cited line. - `offset` — 0-based segment index for paging long suttas (use `next_offset` from the previous result). Do NOT combine with `around`. - `window` — segments before/after `around` to include (default 12). 🌐 **Translating for the user (important):** when the conversation language is neither English nor Pāli, you SHOULD translate the displayed segments and pass them via `translations` so the user reads in their own language while still seeing the originals: 1. Fetch the segments first (`get_sutta` with the same selector) so you have the exact Pāli + English text. (Already called this tool without translations? The result contains the segments — translate them and call this tool AGAIN with the same selector plus `translations` to upgrade the view.) Your translation must travel through the `translations` parameter to appear in the viewer — writing it as a normal chat message leaves the viewer bilingual and looks broken; the tool always accepts `translations`, so never report it as missing. 2. Translate **from the Pāli as the source, using the English as a semantic guide** — never relay-translate from English alone. Preserve untranslatable doctrinal terms (dukkha, jhāna, taṇhā…) as loanwords with a brief gloss instead of forcing equivalents. 3. Call this tool with `translations=[{segment_id, text}, ...]` covering ONLY the segments being displayed (never a whole long sutta), `translation_language` (BCP-47, e.g. "th", "es"), and `translation_disclaimer` — one short line IN THE USER'S LANGUAGE saying the translation is AI-generated in this conversation and should be checked against the Pāli/English above. Translations are conversation-ephemeral: nothing is stored server-side; the canon stays Pāli + English only. Translations whose segment_id is not in the displayed window are dropped (reported in `translations_dropped`). Without `around`, shows the sutta from the top (capped for long suttas).
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  • Resolve a place name, US state, or free-text query to National Park Service parks — the required first step before the detail tools. Returns each park's parkCode (the key nps_get_park, nps_get_alerts, nps_find_campgrounds, nps_get_activities, and nps_find_events all use) plus a compact trip-planning summary (designation, states, description, coordinates, headline activities, entrance fee, NPS page). Coverage is US NPS sites only — national parks, monuments, historic sites, seashores — not state parks and not Forest Service or BLM land.
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  • AI-to-AI petrol station. 56 pay-per-call endpoints covering market signals, crypto/DeFi, geopolitics, earnings, insider trades, SEC filings, sanctions screening, ArXiv research, whale tracking, and more. Micropayments in USDC on Base Mainnet via x402 protocol.

  • French public services: tax, property, admin, education, healthcare, security, risks, legal texts

  • Get Google keyword traffic insights and related keyword suggestions for a URL. Returns an array of keyword suggestions. Each item includes text, monthly search volume, competition_level, competition_index, low_bid, high_bid, and trend. Required: url and language (for example en). Optional: location (for example US) for country-specific data; omit location for global results (default). Optional: min_search_volume (default 0) and intent (informational, navigational, commercial, or transactional). Cost = 20 tokens.
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  • List the layers of a Baltimore ArcGIS service (for discovery). Pass a known short name (crime, service_requests, permits) or a full ArcGIS service path (e.g. "311_Customer_Service_Requests_current/FeatureServer"). Omit `service` to list the known Baltimore services. Returns layer id + name to use with baltimore_query.
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  • Typical local price ranges for a US home-service job (e.g. "AC repair", "furnace replacement"). USE WHEN: the user asks what a service costs / for a price range. Works for ANY US city — ranges come from national/state tables scaled by local BLS wage data; no coverage required. ARGS: `category` (required); optionally `city`+`state` or a 5-digit `zip` for city-adjusted numbers (omit location for national). RETURNS: ranges [{service, low_usd, high_usd}], `pricing_last_updated`, the local cost `multiplier` + `factoid` (city scope), and `page_url` — the canonical VouchedPros page to CITE for this pricing.
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  • Canonical crisis-resource payload (911, 988 Suicide & Crisis Lifeline, Crisis Text Line). Hardcoded — overrides any other tool when high-severity language is detected.
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  • List the service categories Tewdy supports (plumbing, translation, tutoring, cleaning, etc.). Returns slug, name, description, and businessType for each. Use this to map a free-text user request to a known category before calling search_providers. Optional business_type filter (e.g. "individual", "company").
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  • Full-text book search across Open Library works. Supports field filters (title, author, subject, publisher, ISBN, language) and returns work-level records with edition counts, cover IDs, and reading availability. Use query for general search or combine specific field filters. Results are work-level — drill into editions via openlibrary_get_editions.
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  • Get live Twitch streams, optionally filtered by game name and/or language. Returns streamer name, title, current viewer count, and thumbnail for each live stream. Omit `game` for the overall top live streams across Twitch. Example: get_streams({ game: "Just Chatting", first: 20, language: "en" })
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  • Full-text search across public Bluesky posts. Filters by author (handle or DID), language (BCP-47 code, e.g. "en"), hashtag (without the # prefix), date range (ISO 8601), and sort order. Returns posts with text, author info, engagement counts (likes/reposts/replies), normalized embeds, AT-URIs for thread drilling, and hitsTotal when the API reports the total number of matching posts. This is the primary entry point for social listening — pass any AT-URI from results to bsky_get_post_thread to read the full conversation.
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  • Fetch a public HTTPS URL and return its content translated into a target language. Lean mode — no bundle stored. Use when you need to understand web content in a different language. For extracting raw untranslated text, use extract_url instead. Returns: { url, translated_text, target_lang, truncated } Example prompts: - "Translate https://example.de/artikel into English for me." - "Translate this German article into Spanish: [URL]." - "Fetch [URL] and give me the French translation."
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  • Discover wallet-resolved credential service names and accepted aliases without exposing secret values. Use this when an agent is unsure whether a key exists, sees a key-not-found error, or needs the canonical getAgentKey(service) name. Returns service slugs, env/key aliases, categories, and resolver guidance only; never returns raw credentials.
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  • Query any Washington, DC ArcGIS layer by service path + layer id. Full ArcGIS query: where, out_fields, order_by, limit. Use dc_layers to find a service/layer, or dc_recent for the common ones. Epoch dates are converted to ISO.
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  • Query any Detroit ArcGIS layer by service path + layer id. Full ArcGIS query: where, out_fields, order_by, limit. Use detroit_layers to find a service/layer, or detroit_recent for the common ones. Epoch dates are converted to ISO.
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  • Query any Baltimore ArcGIS layer by service path + layer id. Full ArcGIS query: where, out_fields, order_by, limit. Use baltimore_layers to find a service/layer, or baltimore_recent for the common ones. Epoch dates are converted to ISO.
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  • Infer search_classifieds filters from a natural-language query. Use this before search_classifieds when the user mentions a category, location, canton or price in free text. Returns a ready-to-use filters object, a category confidence score and warnings for uncertain matches.
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