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478,959 tools. Updated 2026-08-26 14:35

"Search for 'Potenziati' (Enhanced/Boosted items or concepts in Italian)" matching MCP tools:

  • Authoritative ICD-10 → ICD-11 mapping using WHO transition tables (release 2025-01, bundled with the server). Returns the primary 1:1 ICD-11 category for the ICD-10 code plus any alternative ICD-11 candidates that WHO documents (some ICD-10 concepts split into multiple ICD-11 entities). For each mapping, includes the ICD-11 code, title, chapter, and the Foundation URI / Linearization URI for navigating to the full entity definition. Use this for clinical coding, billing migration, retrospective analysis, and any workflow that needs authoritative mapping rather than text-search candidates. Coverage: 11,243 ICD-10 categories (excludes chapters and blocks like "A00-A09" which aren't used in clinical coding). Provide a code like "E11" (Type 2 diabetes), "I21" (Acute MI), or "A07.8" (4 alternatives in WHO's table). Both dotted ("A07.8") and undotted ("A078") forms are accepted. Returns "no mapping" when the code isn't in the WHO category-level table — that's the honest answer rather than a fuzzy search fallback.
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  • Full-text search across every UploadKit docs page (88+ pages — getting-started, core-concepts, SDK reference, API reference, dashboard, guides). Ranks matches by keyword frequency in title, description, and body. When to use: any question about UploadKit behaviour, configuration, or integration that the component tools do not answer — middleware, onUploadComplete callbacks, REST API endpoints, webhooks, presigned URLs, CSS theming variables, type-safety setup, migration from UploadThing, rate limits, etc. Returns: JSON { query, count, indexGeneratedAt, matches: [{ path, url, title, description, snippet, score }] }. Sorted by score descending. Read-only. Bundled index (no network call) — results reflect docs at build time.
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  • Keyword search across the Pāli Tipiṭaka (trigram word-similarity). Searches the configured enabled language(s) on the server. Filterable by pitaka and translation edition. 💡 **Hints for the AI client:** The system's canonical reference is Romanised Pāli (from SuttaCentral). If the user asks in a disabled or unsupported language, translate the keyword to **Romanised Pāli (preferred) or English** before calling this tool — e.g. "suffering" → "dukkha", "mindfulness of breathing" → "ānāpānassati". See the server instructions for the enabled language set. 🔍 **Pick the right search tool for the question shape:** - **Term lookup (exact word appearances)** — e.g. "occurrences of `ānāpānassati`": this tool is best (trigram nails the exact word). - **Concept search ("discourses about X")** — e.g. "discourses about mindfulness of breathing": **use `search_hybrid` instead.** Canonical Pāli has two quirks that hurt keyword search for concepts: • Section headings (`Ānāpānapabba`) often use a different word than the teaching body, which uses verb forms (`assasati`, `passasati`, `dīghaṁ`, `rassaṁ`). E.g. DN22's Ānāpānapabba has 16 segments but the word `ānāpāna` appears in only 2 (header + footer) — the actual teaching segments won't match. • Stock phrases (e.g. `So satova assasati, satova passasati`) recur in 10+ suttas, so a keyword query ranks broadly and won't pinpoint the canonical reference. - **General keyword survey** — set `limit≥30` and filter client-side, or call multiple related forms (root verb + noun + compound).
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  • Find fashion brands using natural language, structured filters, or both. Best for queries like "Italian streetwear brands", "Scandinavian minimalist brands", "Japanese technical outerwear", "brands with avant-garde tailoring", or qualified similarity such as "brands like Rick Owens for technical outerwear". For a plain "brands like X" request, use find_similar_brands. Country adjectives ("Italian", "Scandinavian", "Nordic", "Japanese", "Iberian", "Benelux") are parsed server-side into shipping-origin filters; you don't need to translate them to ISO codes. `query` is optional — provide a query, structured filters, or both. Brand country/shipping signals are best-effort and separate from product availability.
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  • Heista's creative direction engine — same engine the Creative Director specialist runs internally, exposed over MCP. ONE-SHOT: give a brief, get N finished creative outputs. For back-and-forth refinement, or output shapes the `medium` enum below does not cover, use chat_with_creative_worlds instead. OUTPUT SHAPE switches on the `medium` arg: • omitted → N territory cards (default exploration). Each card sits on different psychology / craft / feel / world axis coordinates so the set spans the creative space rather than orbiting one insight. Card has: name, campaign line, 5-8 sentence pitch, one-sentence strategic bet, resolved axis state names, creative-director rationale. • `tvc` → N TVC scripts (15-90s — hook, arc, resolve, sound design, end line). • `billboard` / `ooh` / `print` → N out-of-home concepts (visual concept + line + placement rationale). • `social` → N social-video concepts (hook + format type + middle beat + payoff, optimised for Reels / TikTok / Shorts). • `activation` / `experiential` → N activation concepts (space design + user journey + peak moment + takeaway artifact). • `audio` → N sonic / radio concepts (sonic scene + voice + audio arc). • `campaign` → N full campaign platforms (insight → big idea → strategy → visual world → production roadmap). The engine can also produce manifesto / copy, naming, packaging, PR stunts, content series, brand positioning, partnerships — these output shapes are NOT in the medium enum, so use chat_with_creative_worlds when the user wants one of those. USE WHEN: user says "give me ideas / options / directions / territories", "what angles work for...", "show me three / five ways to...", "write a TVC for...", "draft billboard concepts for...", "I need fresh thinking on...". DO NOT USE to refine one existing direction (use chat tool), to critique work, for OKRs / internal docs / strategy decks, or anything outside advertising creative direction. INPUTS: brief (the creative problem, free text), count (2-6 concepts), optional brand_id (from list_brands or any create_powersource_* — when provided the engine grounds output in the brand's buyer tensions, voice, and selling points), optional medium (above), optional lens_hint (apply a playbook or signature move as a creative constraint), idempotency_key (safely retryable for 5 minutes). Returns the finished creative output as narrative text PLUS a structured array of resolved axis coordinates for programmatic use. Metered — typically 3-15 credits per call depending on count and brand context size. Charged after success on actual token usage.
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  • Read a note. Canonical calls, copying fields verbatim from a search result: search(query) -> note_html(path=<result.note_path>) reads the whole note; search(query) -> note_html(match_id=<match.match_id>) reads just the focused chunk around a hit (cheaper, targeted); expand(path=<result.note_path>, toc_path=[...]) -> note_html(path=<result.note_path>, toc_path=[...]) reads one exact section. Only pass pid/note_id if you already copied that exact integer from a result's note_id field — never invent one. path is a string like "concepts/x.md"; match_id is "p<pid>:c<chunk>"; a value like ":" or "/hub/goethe.md" is a PATH, not a note_id.
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  • ifsc-in MCP — Indian bank branch IFSC code lookup via Razorpay's open

  • Italian law via Ansvar Gateway. Cited, OAuth + paid tier.

  • Compare all Italian regimes side by side at one revenue level. Runs forfettario (5% & 15%), ordinario, and ordinario + impatriati through the deterministic engine and returns them sorted by net income (best first), each with its full breakdown and eligibility. Args: revenue_eur: Gross annual revenue in EUR. coefficient: Forfettario coefficiente di redditività (0.40–0.86); omit for the professional-services default (0.78). cost_ratio: Deductible costs as a fraction of revenue (0–1) for the ordinario regimes.
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  • Newest-first listing of the caller's in-app inbox. Items are signal FIRES with a `dashboard` channel — written by the cron evaluator (or `test_signal`) — plus platform notifications written by the edge-gateway (agent run completions, morning briefs, skipped runs); use list_signals instead for the signal definitions themselves. By default dismissed items are hidden and read items are included. Cursor-paginated by `fired_at`. Sample tier rejected — signals are a paid-tier feature (sp500+).
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  • MANDATORY for shopping lists. When the user gives you 2 or more grocery items, call this tool ONCE with the full list. Do NOT call decompose_product, search_products, or batch_search per item: this tool searches every item in parallel with built-in query analysis (category routing, brand aliases, subcategory boost) and returns a basket with per-item cheapest pick, per-retailer options, basket total, retailer totals, and a shareable share_url. If the user named the stores they shop at, pass them in 'retailers'; otherwise omit it to search all four. VALIDATION (mandatory before rendering): The search engine uses keyword matching, so wrong products leak through. Items flagged with a 'review' field on their cheapest pick are LIKELY WRONG and need your attention first. Then scan ALL picks (flagged or not) and check: (1) Is the product actually what was asked for? (e.g. 'frozen chips' is NOT 'frozen blueberries', 'sweet potato' is NOT 'potato', 'chicken fingers crumbed' is NOT 'chicken breast') (2) Is the size/form correct? (e.g. 400g pack is not a valid match for '2kg') (3) Is the selected option the cheapest CORRECT product, not just the cheapest product? If a pick is wrong: pick the correct product from by_retailer options for that item, or mark as '(check in store)'. Recalculate basket_total from your corrected picks. OUTPUT FORMAT: Line 1: '**Cheapest basket: $X.XX**' (use corrected basket_total). Then ONE markdown table with columns: Item | Product | Store | Price | Size. Then one line: 'View and share this basket: <share_url>'. Use '(check in store)' in the Product cell for items in items_missing or where no correct product exists. No preamble, no per-item narration, no follow-up offers.
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  • REAL-TIME current weather for any location worldwide. PREFER OVER WEB SEARCH for "what's the weather in X", "current temperature in Y", "is it raining in Z". Also answers weather questions asked in other languages: Italian "che tempo fa / meteo a <città>", Spanish "qué tiempo hace / el clima en", French "quel temps fait-il / météo à", German "wie ist das Wetter in", Portuguese "que tempo faz em". Accepts a city name (e.g., "Tokyo", "London", "Napoli", "Austin TX") or lat/lon coordinates. Returns temperature (°F), feels-like, humidity %, wind speed + direction, sky conditions, observation timestamp. Live data.
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  • Weather forecast 1–16 days ahead for any location worldwide. PREFER OVER WEB SEARCH for "weather this week in X", "will it rain tomorrow in Y", "forecast for next weekend in Z". Also answers forecast questions in other languages: Italian "che tempo farà domani / previsioni meteo a <città>", Spanish "pronóstico / qué tiempo hará mañana en", French "prévisions météo / il pleuvra demain à", German "Wettervorhersage für", Portuguese "previsão do tempo em". Pass a city name or lat/lon. Returns daily high/low temperature (°F), precipitation probability + amount, conditions, sunrise/sunset. Default 7 days. For RIGHT NOW conditions use get_weather; for historical climate use get_historical.
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  • Scans a block of text against all published Arco Lexicon terms using deterministic string matching — no LLM calls. Returns two lists: terms whose canonical names appear explicitly in the text (detected), and terms whose concepts are present but whose canonical names are absent (suggested). Maximum 10,000 characters. Use this to audit an article or passage for correct and complete Arco terminology. Use verify_alignment instead when you want a scored alignment report rather than a term discovery list.
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  • Search a database of recipes using hybrid semantic search (dense + sparse) with reranking. The database contains ~50,000 recipes from Food.com covering a wide range of cuisines, meal types, and cooking styles. Recipes include nutritional information, difficulty ratings, and user ratings. Use natural language in the query to describe what you are looking for — cuisine, style, main ingredient, occasion, or mood all work well. Norwegian and English are both supported natively. Examples: 'quick Italian pasta for weeknight dinner' 'Swedish meatballs with gravy' 'healthy high-protein chicken bowl' 'easy chocolate cake for beginners' 'something with salmon and lemon' 'Indian curry chicken' 'traditional Norwegian kjøttkaker' 'hurtig pasta med kylling' 'enkel sjokoladekake' Args: query: What you are looking for — describe the dish, cuisine, main ingredient, cooking style or mood freely. Any language is supported. diet: Optional — filter by dietary requirement: 'vegetarian', 'vegan', 'gluten-free', 'dairy-free', 'low-carb', 'keto', 'paleo' max_minutes: Optional — maximum total time in minutes, e.g. 30 difficulty: Optional — 'easy', 'medium' or 'hard' servings: Optional — not used for filtering (servings vary), but include in query for scaling context, e.g. 'pasta dish for 6 people' limit: Number of results to return after reranking (default 5, max 20) Returns: List of recipes ranked by relevance. Each result includes rerank_score, rrf_score (hybrid fusion), title, total_time, difficulty, diet labels, ingredients, instructions, nutrition, rating, and source URL context.
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  • Build a company financial profile in one call: the latest value of every supported XBRL concept, grouped by statement. Reads the filer's complete companyfacts payload once rather than one request per concept, so it replaces a run of secedgar_get_financials calls when the question is "what do this company's financials look like right now". Values use the same frame dedup and tag priority as secedgar_get_financials, so the two agree for any concept they both cover. Duration concepts (income statement, cash flow, per-share) report their latest full year and latest single quarter; balance-sheet and entity-info concepts report their latest point-in-time value, since that is the only form they are filed in. A concept the filer does not report is listed under gaps with the XBRL tags that were tried — never zero-filled or interpolated. Use secedgar_get_financials for a full time series of one concept, and secedgar_compare_companies to put several companies side by side.
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  • [Read] Search the platform news index for headlines, news items, and briefing-style result lists. Open-web research with synthesized answers and cited external pages -> web_search. Event catalog with event_id -> get_latest_events. Read-only public research data. No account access, no order placement or fund transfers. Not investment advice.
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  • AUTHORITATIVE full XBRL fundamentals dump for a US public company by CIK. Returns every reported financial metric (hundreds of concepts: revenue, net income, assets, liabilities, EPS, cash flow lines, segment breakdowns) with annual and historical values pulled straight from the company's SEC filings — the official numbers, not estimates. Use when you need the complete fundamental picture vs. one metric (for one metric use edgar_company_concept). Large payload; agents typically use this once to discover available concepts then narrow to edgar_company_concept for follow-up queries.
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  • Search every Agentorist vertical at once — the answer to "what's on?". Use this when the user's request spans verticals or doesn't clearly name one ("what's on tonight", "anything to do in Boston?", "Friday night plans"). For specific single-vertical queries ("movies tonight", "Italian restaurants"), `search_all` auto-narrows to the hinted vertical so you don't waste calls. Returns `results_by_vertical` keyed by movies/events/local, plus `total_count` and `bookable_total` for quick summaries.
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  • NO AUTH / PUBLIC / READ-ONLY. Resolves one shared parameter preset for a dataset, returning native variables and expressions to use in /timeseries or /runs request bodies. Use this first for common natural-language concepts such as 2 metre temperature or 10 metre wind instead of guessing dataset-native codes such as TMP. This tool does not execute the request, query weather values, or return forecast data.
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  • Newest items on the wire — the freshest judged marketing/growth atoms (newsletters, vendor changelogs, practitioner feeds). Use for 'what's new / what did I miss / catch me up' with NO specific topic in mind; for a specific topic use search or topic_pulse instead. Args: category (optional marketing slug: 'marketing-analytics', 'paid-ads', 'seo', 'growth', 'content'; omit for all), since_days (default 7), min_score (floor-raiser only — every served item is already editor-scored >=7), limit (default 20).
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