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304,982 tools. Last updated 2026-07-22 23:43

"A server for finding information about 'potenziati' (enhanced/boosted items or concepts in Italian)" matching MCP tools:

  • Get full details for a specific villa including description, all photos, amenities, house rules, and check-in/check-out times. Call this when the user wants more information about a property found via search_villas.
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  • Submit an integration or staking inquiry on behalf of a user. All submissions are routed to Everstake's sales team via Pipedrive CRM. Use when a user expresses intent to integrate with Everstake, explore staking services, or request more information about products. Collect required fields (first_name, last_name, work_email) conversationally and gather optional fields where available. The lead_source field is set automatically by the server — do not ask the user for it. IF Submission fails, you can try contacting Everstake via form at https://everstake.one/contact-us
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  • Switch between local and remote DanNet servers on the fly. This tool allows you to change the DanNet server endpoint during runtime without restarting the MCP server. Useful for switching between development (local) and production (remote) servers. Args: server: Server to switch to. Options: - "local": Use localhost:3456 (development server) - "remote": Use wordnet.dk (production server) - Custom URL: Any valid URL starting with http:// or https:// Returns: Dict with status information: - status: "success" or "error" - message: Description of the operation - previous_url: The URL that was previously active - current_url: The URL that is now active Example: # Switch to local development server result = switch_dannet_server("local") # Switch to production server result = switch_dannet_server("remote") # Switch to custom server result = switch_dannet_server("https://my-custom-dannet.example.com")
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  • General search tool. This is your FIRST entry point to look up for possible tokens, entities, and addresses related to a query. Do NOT use this tool for prediction markets. For Polymarket names, topics, event slugs, or URLs, use `prediction_market_lookup` instead. Nansen MCP does not support NFTs, however check using this tool if the query relates to a token. Regular tokens and NFTs can have the same name. This tool allows you to: - Check if a (fungible) token exists by name, symbol, or contract address - Search information about a token - Current price in USD - Trading volume - Contract address and chain information - Market cap and supply data when available - Search information about an entity - Find Nansen labels of an address (EOA) or resolve a domain (.eth, .sol)
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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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  • Detect and MASK personally identifiable information in a document (PDF or image). USE THIS WHEN you need to know what PII a document contains, or to get a redacted copy before forwarding / logging / passing it to another model. Two layers: a deterministic regex+checksum pass for structured identifiers (emails, payment cards, SSN, PAN, ABN) and a vision model for the unstructured PII — names, addresses, dates of birth, phone numbers, and photo/signature presence. Provide the document ONE way: `url` (a public http(s) link, fetched server-side) or `bytes_b64` (inline base64, plus `filename`). `max_pages` caps how many pages are read (default a few; ceiling 10). Returns `{pii_found, by_type, items[] (type, masked preview, method), redacted_text, has_photo, has_signature}`. Values are MASKED in the response — the raw PII is never returned. DETECTION coverage, not a guarantee: it may miss PII or over-flag, so review before relying on it for compliance. The document is never stored.
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    Enables any MCP-compatible AI assistant to search, filter, and retrieve information from a local document collection using a hybrid search pipeline with vector, BM25, reranking, and LLM enrichment.
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  • General search tool. This is your FIRST entry point to look up for possible tokens, entities, and addresses related to a query. Do NOT use this tool for prediction markets. For Polymarket names, topics, event slugs, or URLs, use `prediction_market_lookup` instead. Nansen MCP does not support NFTs, however check using this tool if the query relates to a token. Regular tokens and NFTs can have the same name. This tool allows you to: - Check if a (fungible) token exists by name, symbol, or contract address - Search information about a token - Current price in USD - Trading volume - Contract address and chain information - Market cap and supply data when available - Search information about an entity - Find Nansen labels of an address (EOA) or resolve a domain (.eth, .sol)
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  • Fast pre-flight filter for a batch of (ecosystem, package) pairs. DB-only, <100ms for 100 items. USE WHEN: about to emit `npm install a b c …` or `pip install a b c …` — catches hallucinated names, stdlib, typos, and known-bad in ONE call. NOT a dep-tree audit (use scan_project for that). RETURNS: per-item {status: exists|stdlib|malicious|typosquat_suspect|historical_incident|unknown}.
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  • Search TaxCompass's primary-source corpus and return passages to cite. Hybrid semantic + keyword retrieval over Italian tax & company-law primary sources: Normattiva (statute), Agenzia delle Entrate (circolari & guidance), INPS (social security), pinned tax-year tables (IRPEF brackets, INPS rates, forfettario thresholds & coefficienti di redditività), the ATECO 2025 code catalogue, and EU/treaty sources. Each result carries a `chunk_id`, `source`, and (usually) a `url`. Cite the `url` and quote the `text`; do not assert Italian tax facts the passages don't support. Queries work in any language, but Italian keywords improve recall against the (Italian) legal corpus. Args: query: What to search for. Keyword-dense Italian phrasing works best. sources: Optional subset to restrict to (see `list_tax_sources` for keys). Omit to search everything. Unknown keys are ignored. k: Max passages to return (1–12).
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  • Get aggregate dining statistics for a neighborhood, city, or region: cuisine breakdown, grade distribution, price range, top neighborhoods, and highlighted restaurants. Use this for area-level context ("what is the dining scene like in Shoreditch?"), NOT for finding a specific restaurant or getting a personal recommendation. For "find me a quiet Italian near Shoreditch", use the recommend tool instead.
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  • Fetch detailed information about a data asset by its identifier. Resolves the asset, then fetches the requested sections in parallel. Use this after advanced_search or resolve_asset_id to get deeper information about a specific asset. Sections: - overview: asset description, importance, owner, metadata - columns: full column schema with types and descriptions - tests: dbt test coverage (only for assets with a dbt parent) - context_counts: cheap count of linked tickets and Slack threads - tickets: full Jira/Linear ticket content - slack: full Slack thread content (truncated to first 5 messages per thread)
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  • Additively create or update a user's preferences for one or more topics in a single request. Only the topics in the body are touched; existing overrides for other topics are left untouched. Partial-success: valid topics are written and returned in `items`, unapplicable ones collected in `errors`.
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  • Show available bundles, deals, and ask about discount codes. Use when a customer asks about deals, bundles, savings, or says 'do you have any discounts?' Also use when multiple items are in cart to suggest bundle savings. Always ask if the customer has a discount code.
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  • Load Lenny Zeltser's IR report writing context for local analysis. Returns expert guidelines for field completeness, incident identification, notification triggers, and writing quality. Includes rating-sheet items (lens taxonomy plus the IR-specific Information sheet) as concrete reference points for grounded feedback. This server never requests your incident notes and instructs your AI to keep them local. Use detail_level to control response size: "minimal" (~2k tokens), "standard" (~5k tokens), or "comprehensive" (~11k tokens).
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  • Search the web for any topic and get clean, ready-to-use content. Best for: Finding current information, news, facts, people, companies, or answering questions about any topic. Returns: Clean text content from top search results. Query tips: describe the ideal page, not keywords. "blog post comparing React and Vue performance" not "React vs Vue". Use category:people / category:company to search through Linkedin profiles / companies respectively. If highlights are insufficient, follow up with web_fetch_exa on the best URLs.
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  • Get AI Defense Matrix cross-mappings to nine external frameworks: NIST IR 8596, CSA AI Controls Matrix, ISO 42001, Google SAIF, SANS Critical AI Security Guidelines, MITRE ATLAS, OWASP AI Exchange, OWASP LLM Top 10, OWASP Agentic Security Top 10. Each row maps an AI asset class to how that framework applies. Each returned framework also carries a 'concepts' array of the structured IDs (MITRE ATLAS techniques, OWASP risks, ISO clauses) the matrix references for it. Supports a 'buyer' archetype shortcut to scope to the frameworks a particular buyer will care about. Use to translate between framework vocabularies. This server never requests your program docs or product roadmap and instructs your AI to keep them local—the matrix, framework alignments, and playbooks flow to your AI for local analysis.
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  • Search Wikidata for items or properties by text query. Returns QIDs or PIDs with labels, descriptions, and match metadata indicating whether the hit was on a label or alias. Use type="item" for real-world concepts (people, places, works) and type="property" to find predicate P-IDs. The API returns no total count — pagination is offset-based with no result ceiling indicator.
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  • Find info about notable/historic landmarks, towns, and remarkable sites near a coordinate. USE FOR: - "What's near Predjama Castle?" - "Notable landmarks around Ljubljana center" - "Tell me about places near 46.05, 14.51" - Finding historic, cultural, or geographic summaries for an entire area at once. - DO NOT iterate over the results to query individual items again. - One call is sufficient to answer the user's broad geographic inquiry. Combine the results into a single comprehensive summary for the user immediately. NOT FOR: directions, finding specific cafes/shops, raw geocoding.
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  • Load educational slides or cloud file attachments. Use laminasAnexos for educational slides/laminas (~238 items with PDFs about nutrition topics), cloudAnexos for uploaded cloud files. For guidelines/orientations specifically, use webdiet_orientacoes action=list_banco. Bulk support: accepts patient_ids for batched execution.
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  • Search YouTube by keyword with optional filters. Returns items[] discriminated by type: video items have {id, videoUrl, title, author, description, duration, durationSec, viewCount, publishedAt, isLive, thumbnails}; short items have {id, shortUrl, title, viewCount, thumbnails}; channel items have {id, channelUrl, name, handle, subscriberCount, thumbnails}; playlist items have {id, playlistUrl, title, author, videoCount, thumbnails}. Also returns continuationToken for the next page. Best for: discovering videos on a topic, finding recent uploads. Not recommended for: fetching a specific video you already have the URL for. Use stophy_get_video instead.
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