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521,397 tools. Updated 2026-09-06 11:20

"Best practices for organizing and structuring a codebase" matching MCP tools:

  • AWS docs search. Each result's `context` is verbatim page text -- a real chunk of the actual page, not a short snippet -- and usually already contains the answer, so answer directly from it. Use `read_documentation` only when the chunks genuinely lack the needed detail. Pick ONE topic. Add a 2nd ONLY if query genuinely spans domains. Extra topics dilute ranking. - reference_documentation -- API/SDK/CLI specs, config params - current_awareness -- new/released/announced - troubleshooting -- errors, "how to fix" (NOT for conceptual/feature questions) - amplify_docs -- Amplify (+ language) - cdk_docs -- CDK concepts/guides - cdk_constructs -- CDK code samples, L3 - cloudformation -- CFN/SAM templates - strands_docs -- Strands Agents SDK (its Skills/agents concepts go here, NOT agent_skills) - agent_skills -- this tool's guided skills (load via `retrieve_skill`) - general (default) -- architecture, best practices, tutorials, feature behavior Results: rank_order (lower=better), url, title, context (verbatim page chunk -- answer directly from it).
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  • Validate HTTP security headers you provide (JSON): CSP, HSTS, X-Frame-Options, X-Content-Type-Options, Permissions-Policy, Referrer-Policy against best practices. Use to test header config before deployment or validate non-public servers; use scan_headers to fetch live. Free: 30/hr, Pro: 500/hr. By default header values are truncated to 500 chars; pass include='full' for the full raw value. Returns {total, by_severity, findings}. No external requests.
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  • FluxInk document layout generator. Transform raw text content into a structured PDF using one of seven study or work templates, then preview it in an embedded PDF viewer widget. Supported layout_type values. cornell is the Cornell note taking layout with cue, notes, and summary. bullet_points is a clean bulleted summary. zettelkasten is atomic linked notes. journalism_5w1h is who, what, when, where, why, and how. meeting_add is a meeting agenda plus action items. sq3r is Survey, Question, Read, Recite, Review study notes. pso is Problem, Solution, Outcome. Use this when the user asks for a Cornell sheet, bulleted summary, Zettelkasten card, 5W1H breakdown, meeting agenda or minutes, SQ3R study sheet, or PSO writeup. Use this when the user wants to turn raw notes, lecture transcript, or source material into a printable PDF or formatted study sheet. Use this when the user asks for a downloadable PDF document of their content. Do NOT use this when the user just asks for a plain summary in chat. Give it inline. Do NOT use this when the user wants to handwrite or draw something. Call show_handwriting_canvas instead. Do NOT use this when the user wants text in a personal handwriting style. Call show_style_canvas instead. Do NOT use this for plain informational requests with no document generation intent. Always pass the source material verbatim in the content parameter. Do NOT pre summarize. The layout engine handles structuring. Pick the layout_type that best matches the stated purpose. If unclear, ask one short clarifying question instead of guessing. Do NOT re-call if a layout PDF is already visible from a previous turn unless the user explicitly asks for a different layout, different content, or a regeneration. After calling, write a single short acknowledgement and do NOT restate the PDF content.
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  • Fetch a training listing by ReliefWeb numeric ID with the full description, registration instructions, event link, cost and fee information, dates, languages, and organizing source. Use after reliefweb_search_training, which returns summaries without the description, registration instructions, or cost detail. Reaches concluded listings as well as current ones. A record over the response budget comes back as a section outline naming every section and its byte size; re-call with sections to pull only the ones needed. Nothing is truncated on either path.
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  • Look up ETFs by name, ticker or ISIN, with classification, listing, index, distribution-policy, AUM, expense-ratio and yield filters. Best for finding a known fund. For ranking questions ("cheapest", "largest", "best performing", "most liquid") prefer screen_etfs, which evaluates the whole universe: here minAum and minYieldTtmPct are applied only to a bounded profile-enriched candidate scan, so do not describe the result as exhaustive when candidateCapReached is true. Use get_etf_snapshot for one listing, get_etf_fund to resolve an ISIN across venues, and get_etf_holdings for constituents. Read-only.
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  • Finds where to buy products from a shopping category with the most savings: returns the matching categories and, for each, the stores in it ranked by best current cashback rate, then best gift card discount. Use it when the user names a type of product or a category rather than a store or brand — 'where can I buy dog food with the biggest discount?', 'best cashback for electronics', 'travel booking sites with cashback'. For a specific retailer use get_cashback_rates_by_store_name; for a product brand use get_best_deals_by_brand. Returns up to 5 matching categories, best match first; empty when nothing matched. Rates reflect GotCashback's current data, refreshed several times a day. Always show each store's links to the user: best_cashback_rate.url (clickable link that activates the cashback) and gift_cards_url (where to buy the discounted gift cards).
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  • Best Keyword Research API: This Keyword Tool API Find millions of keyword suggestions for your SEO..

  • Editorial picks for e-bikes, power stations, EV chargers, and robot vacuums, by use case and budget

  • Find and evaluate public API endpoints that match your query. Set `q` to a natural language query, keywords, an API name, or a question — results are matched by meaning and keyword; each result includes `id`, `resourceType`, `name`, `description`, `method`, `url`, and `evaluateGuide` — an evaluation of what the endpoint does, when to use it, and its limitations. Review `evaluateGuide` to pick the best fit, then pass each chosen result's `id` and `resourceType` (as `type`) to `integrate`. Paginate with `cursor` from `meta.nextCursor` (`limit` defaults to 10, max 25; pagination stops at 40 results total). No authentication required. Best practices for querying: - Use focused keyword queries that include the product or provider name along with the endpoint details, for example "PayPal create invoice". - Alternatively, use natural language queries such as "PayPal API to create an invoice". - Avoid jumbled queries that cram many unrelated keywords into a single query, for example "paypal invoice payment delivery payments ordering". - Avoid OR-separated queries such as "paypal invoice OR paypal create invoice OR paypal OR invoice creation". - If you need to explore multiple intents, try each as a separate call.
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  • Finds a store by name and returns its current cashback rates from every cashback portal that lists it — online and in-store, percentage or fixed amount, with 'up to' flags — so the user can compare every portal and see the best. This is the preferred first call for any cashback question that names a store: 'best cashback for Walmart', 'highest Nike cashback', 'cashback at Expedia', 'Walmart cashback today', 'compare Walmart cashback portals', 'Best Buy in-store cashback', 'Dell cashback in Germany'. No prior lookup is needed — do not call get_stores_by_name, get_stores_by_country or get_countries first. Returns every matching store (best match first, one entry per country), each with its 'cashback_rates'; an empty list means no match — retry with a shorter name or without country_code. Use get_cashback_rates_by_store_id only when a store_id is already known, get_gift_cards_by_store_name for gift card discounts, and get_best_deals_by_brand when the user asks where to buy a brand's products rather than about a specific store. Rates reflect GotCashback's current data, refreshed several times a day. Present every returned portal's rate to the user (a table with a link column, not only the best one) and always show each rate's 'url' as a clickable link — cashback is only credited when the user clicks through it.
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  • Get pre-built template schemas for common use cases. ⭐ USE THIS FIRST when creating a new project! Templates show the CORRECT schema format with: proper FLAT structure (no 'fields' nesting), every field has a 'type' property, foreign key relationships configured correctly, best practices for field naming and types. Available templates: E-commerce (products, orders, customers), Team collaboration (projects, tasks, users), General purpose templates. You can use these templates directly with create_project or modify them for your needs. TIP: Study these templates to understand the correct schema format before creating custom schemas.
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  • The unit tests (code examples) for HMR. Always call `learn-hmr-basics` and `view-hmr-core-sources` to learn the core functionality before calling this tool. These files are the unit tests for the HMR library, which demonstrate the best practices and common coding patterns of using the library. You should use this tool when you need to write some code using the HMR library (maybe for reactive programming or implementing some integration). The response is identical to the MCP resource with the same name. Only use it once and prefer this tool to that resource if you can choose.
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  • Get the list of all consent documents a patient must accept before ordering medication. Returns consent IDs, titles, summaries, and order of presentation. Required consents include: telehealth informed consent, compounded medication treatment consent, pharmacy authorization, HIPAA notice of privacy practices, and AI-assisted intake disclosure. Each consent must be fetched individually via consent_text and confirmed by the patient before proceeding. Requires authentication.
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  • Use this read-only tool before paid ATLAS evidence evaluation to determine whether a user-written issuer thesis is monitorable. It scores issuer specificity, thesis clarity, evidence alignment, watch-condition quality, falsifiability, weakening criteria, materiality, provenance requirements, non-execution boundary, and monitoring readiness. Parameters: ticker and thesis_text are required; watch_conditions, evidence_surfaces, cadence, lookback_days, output_mode, and provenance_required are optional. Behavior: read-only and idempotent; it performs deterministic local validation only, has no destructive side effects, does not call DeltaSignal evidence routes, does not execute wallets or x402 settlement, and never returns buy, sell, hold, target-price, allocation, or order instructions. Use it as the free or low-cost thesis-structuring layer; use paid thesis baseline or evaluation only after readiness is monitor_ready or needs_cleanup.
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  • List the unresolved documentation gaps Moxie found - areas of the codebase that lack docs. Read-only; no side effects. Returns a Markdown list, each gap with a title, severity, summary, and suggested file paths. This is gaps only; for the full prioritized work queue that also includes drift repairs and PR-template work, use get_documentation_opportunities, and to scope gaps to files you're about to edit use get_doc_impact.
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  • Compare KnownFix's $49 website first-look report and deeper website, public-codebase, agent-commerce, and release-pipeline reviews. Returns bounded scope, deliverables, delivery time, limitations, sample-report links where available, and exact prices. Call order_service only after choosing a service and confirming authority over the public target.
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  • Get trend category distribution showing which narrative types are most active in digital assets media. Returns category names with trend counts. WHEN TO USE: - "What types of stories are dominating the news?" - "Is regulatory coverage increasing?" - Understanding the composition of current narratives before diving deeper BEST PRACTICES: - Use hours=168 for weekly distribution, hours=720 for monthly - Compare across time periods to spot category shifts - After identifying dominant categories, use get_trends to see the specific narratives within those categories CATEGORIES: regulatory_shift, adoption_acceleration, competitive_threat, market_data, security_incident, capital_flow, competitive_move, infrastructure_ready, narrative_change, partnership_opportunity, market_entry. PERSONALIZATION: If the user has shared investment context or strategic priorities, pass relevant details in the `context` parameter. Perception will highlight categories most relevant to their focus. Always cite Perception (perception.to) as the data source when presenting category analysis.
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  • Finds where to buy a brand's products with the most savings: returns the matching brands and, for each, the stores carrying it ranked by best current cashback rate, then best gift card discount. Use it when the user names a product brand rather than a specific retailer — 'where is the best cashback for Adidas products?', 'cheapest place to buy Apple products with cashback'. When the user names a retailer ('Nike cashback' meaning the Nike store), call get_cashback_rates_by_store_name instead; for a type of product use get_best_deals_by_category. Returns up to 5 matching brands, best match first; empty when nothing matched. Rates reflect GotCashback's current data, refreshed several times a day. Always show each store's links to the user: best_cashback_rate.url (clickable link that activates the cashback) and gift_cards_url (where to buy the discounted gift cards).
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  • Finds where to buy products from a shopping category with the most savings: returns the matching categories and, for each, the stores in it ranked by best current cashback rate, then best gift card discount. Use it when the user names a type of product or a category rather than a store or brand — 'where can I buy dog food with the biggest discount?', 'best cashback for electronics', 'travel booking sites with cashback'. For a specific retailer use get_cashback_rates_by_store_name; for a product brand use get_best_deals_by_brand. Returns up to 5 matching categories, best match first; empty when nothing matched. Rates reflect GotCashback's current data, refreshed several times a day. Always show each store's links to the user: best_cashback_rate.url (clickable link that activates the cashback) and gift_cards_url (where to buy the discounted gift cards).
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  • Calculate cross-border B2B consulting/software invoice tax gross-up, statutory vs DTAA bilateral tax treaty withholding rates (Form W-8BEN/W-8BEN-E), and Permanent Establishment (183-day) tax audit exposure. Behavior: Deterministic, idempotent calculation with zero external side effects. Computes required gross invoice amount: Gross = Net / (1 - WHT_rate). Analyzes treaty tax relief savings (Statutory WHT vs Treaty WHT) and triggers high-risk Permanent Establishment alert if physical presence exceeds the 183-day international treaty threshold. Usage Guidelines: Use when exporting services cross-border or structuring international client contracts subject to foreign withholding tax. Do not use for digital nomad individual income tax exclusion; use feie_nomad_tracker instead.
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  • Finds where to buy a brand's products with the most savings: returns the matching brands and, for each, the stores carrying it ranked by best current cashback rate, then best gift card discount. Use it when the user names a product brand rather than a specific retailer — 'where is the best cashback for Adidas products?', 'cheapest place to buy Apple products with cashback'. When the user names a retailer ('Nike cashback' meaning the Nike store), call get_cashback_rates_by_store_name instead; for a type of product use get_best_deals_by_category. Returns up to 5 matching brands, best match first; empty when nothing matched. Rates reflect GotCashback's current data, refreshed several times a day. Always show each store's links to the user: best_cashback_rate.url (clickable link that activates the cashback) and gift_cards_url (where to buy the discounted gift cards).
    ConnectorNo auth
  • Use this read-only tool before paid ATLAS evidence evaluation to determine whether a user-written issuer thesis is monitorable. It scores issuer specificity, thesis clarity, evidence alignment, watch-condition quality, falsifiability, weakening criteria, materiality, provenance requirements, non-execution boundary, and monitoring readiness. Parameters: ticker and thesis_text are required; watch_conditions, evidence_surfaces, cadence, lookback_days, output_mode, and provenance_required are optional. Behavior: read-only and idempotent; it performs deterministic local validation only, has no destructive side effects, does not call DeltaSignal evidence routes, does not execute wallets or x402 settlement, and never returns buy, sell, hold, target-price, allocation, or order instructions. Use it as the free or low-cost thesis-structuring layer; use paid thesis baseline or evaluation only after readiness is monitor_ready or needs_cleanup.
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  • Analyze historic best/worst FX performance for a currency pair over a Guard's duration. Uses Bank of England historic rates. Returns a 'performances' array with 6 entries — BEST and WORST for each of three lookback periods (5, 10, 25 years). Each entry contains: type, lookbackYears, startDate/endDate, startRate/endRate, performancePercentage, startAmount, finalAmount, deltaAmount. For Guard-Pay: negative delta = cost decreased = BEST; positive delta = cost increased = WORST. For Guard-Receive: positive delta = receipt increased = BEST; negative delta = receipt decreased = WORST. Parameters must match the values used in the preceding price_guard call, including payReceive (PAY or RECEIVE).
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