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164,045 tools. Last updated 2026-05-31 01:10

"Information about Amazon Q" matching MCP tools:

  • Returns information about safety features on Makuri, including age verification, content filtering, parental controls, and AI safety guardrails. Use when the user asks about child safety, content moderation, or how Makuri protects minors.
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  • Query SEC filings and financial documents from US capital markets and exchanges. This tool searches through 10-K annual reports, 10-Q quarterly reports, 8-K current reports, proxy statements, earnings call transcripts, investor presentations, and other SEC-mandated filings from US companies. Use for questions about US company financials, executive compensation, business operations, or regulatory disclosures. Limited to official SEC filings and related documents only.
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  • Return pricing-tier breakdown and category stats for an Amazon CPG category. Use when a brand is sizing up a shelf — e.g. evaluating whether a new SKU should enter at budget / midmarket / premium tier, benchmarking their retail pricing against Amazon tier structure, or preparing for a retail buyer meeting that will ask "what's the typical shelf price here?". Returns: category (resolved name), product_count (bucketed, e.g. "100+ products"), price_tiers (dict with budget / midmarket / premium dollar bands, rounded to nearest $0.50 for abstraction), median_price, trend_direction, last_refreshed, cta. Args: category: Exact category name — Grocery & Gourmet Food, Health & Beauty, Household, or Pet Supplies. Case-insensitive.
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  • Compare multiple product prices against an Amazon CPG category's peers. Use when a multi-channel CPG brand needs to stack-rank their SKUs — e.g. identifying which SKUs are underpriced relative to Amazon peers, flagging products where the Amazon Buy Box sits materially below the retail MSRP, or building a cross-channel price-audit table for an ops review. Replaces manual store walks and spreadsheet comparisons. Returns: comparisons (list, per product: name, price, percentile_rank, position, vs_median), category, category_trend, sample_size, last_refreshed, cta. Args: products: List of items, each a dict with 'name' (string) and 'price' (number in dollars). Minimum 1 item; 3-20 is the useful range. category: Exact category name — Grocery & Gourmet Food, Health & Beauty, Household, or Pet Supplies. Case-insensitive.
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  • Get answers to frequently asked questions about Savvly. Use when the user has specific questions about how Savvly works, fees, withdrawals, or regulatory status. For richer, audience-specific Q&As (employee / advisor / broker / employer), use `search_savvly_content` instead.
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  • Get full details for a single business (listing) by its slug. Call this when the user asks for more information about a specific business. Use the slug from search_businesses results.
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  • Returns structured information about what the Recursive platform includes: features, AI model details, supported integrations, and what's included at every tier. Use for systematic feature comparison.
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  • Use when someone asks what Jennifer Rebholz thinks about litigation, her philosophy on practice, what drives her work, advice she gives to young attorneys, or her perspective on the legal profession. Returns her own words from a published Q&A.
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  • Percentile-rank a single product price against tracked Amazon competitors in a CPG category. Use when a multi-channel CPG brand asks where their Amazon listing price sits against 100+ tracked products — e.g. checking whether a $4.99 granola is competitively positioned on Amazon, auditing whether a retail MSRP is reasonable against Amazon reality before a buyer meeting, or sanity-checking a wholesale-to-retail markup. Returns: percentile_rank (string, e.g. "72nd percentile"), price_index_label (ratio vs. category median), position (Value / Parity / Premium), category (resolved name), last_refreshed (ISO timestamp), cta (link to full per-SKU report). Args: price: Product price in dollars (e.g. 4.99). Must be > 0 and <= 10000. category: Exact category name — Grocery & Gourmet Food, Health & Beauty, Household, or Pet Supplies. Case-insensitive. Call list_categories first to confirm available names.
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  • Report the 30-day Amazon price-trend direction for a CPG category. Use when a pricing ops lead asks whether category pricing is rising, stable, or falling — e.g. setting retail promo calendar against an Amazon backdrop, deciding whether to raise wholesale prices during inflationary windows, or catching a price war before it spills into their channel. Returns: trend_direction (Rising / Stable / Falling / Insufficient Data), trend_window ("30 days"), confidence (note with product count), category (resolved name), last_refreshed, cta. Args: category: Exact category name — Grocery & Gourmet Food, Health & Beauty, Household, or Pet Supplies. Case-insensitive.
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  • Search the Savvly Q&A Content Library — 50 audience-tagged questions and answers compiled from Savvly's marketing collateral, organized by stakeholder (employee, advisor, broker, employer, universal) and subsection (e.g. 'Tax & Legacy', 'Retention & Talent Strategy', 'Implementation'). Use this when the user asks about Savvly's positioning, value props, audience-specific talking points, or Q&A-style messaging. Each entry carries the verbatim answer plus any disclaimer footnotes attached to it in the source.
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  • Discover curated topics (2,184 entries with aliases). USE WHEN: planning a multi-round quiz, exploring "what is available about X", showing topic browser. Sorted by count DESC, slug ASC. Cursor-paginated. INPUTS: q (substring on label/alias), kind (tag|subcategory), cursor, limit (max 500).
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  • IMPORTANT: Always use this tool FIRST before working with Vaadin. Returns a comprehensive primer document with current (2025+) information about modern Vaadin development. This addresses common AI misconceptions about Vaadin and provides up-to-date information about Java vs React development models, project structure, components, and best practices. Essential reading to avoid outdated assumptions. For legacy versions (7, 8, 14), returns guidance on version-specific resources.
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  • Get detailed information about a specific train connection including all intermediate stops, platforms, and occupancy. Use a trip ID from search_connections results.
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  • Raw tag dump (10k+ entries) with display label and question count. USE WHEN: building a tag picker, searching "is X a tag", running analytics. Curated higher-level groupings → quizbase_topics. INPUTS: q (substring), cursor, limit (max 500).
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  • Get full details for a single business (listing) by its slug. Call this when the user asks for more information about a specific business. Use the slug from search_businesses results.
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  • Get full details for a single broker (agent) by their profile slug. Call this when the user asks for more information about a specific broker. Use the slug from search_brokers results.
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  • Retrieve detailed information about a Baselight user including their profile bio, website, and public datasets. Use this to understand who owns datasets you're interested in.
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  • Get basic information about a Compute Engine instance template, including its name, ID, description, machine type, region, and creation timestamp. Requires project and instance template name as input.
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  • Get information about the authenticated agent, including type, spending limits, approved categories, and configuration. Requires authentication — call 'authenticate' with your sk_buy_* key first.
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