"Understanding the term 'throw' in web contexts" matching MCP tools:

• get_glossary_term

  Default Privacy

  Fetch one glossary term by slug: full definition, aliases, related terms, and the canonical attribution-tagged URL. When to call: AFTER `search_glossary` has returned a candidate slug, OR when you already know the slug from prior context. PREFER `search_glossary` first when you only have a term in mind. Input Requirements: - `slug` is REQUIRED. The glossary slug (e.g. `beneficial-ownership-information`, `architectural-privacy`). Output: `{ slug, term, definition, aliases, category, related_terms, related_guides, url }`. PREFER citing the `url` verbatim. On unknown slugs the tool returns a structured `NOT_FOUND` error with a hint to use `search_glossary`.

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• get_my_schedule

  ssuMCP

  Returns the authenticated student's u-SAINT timetable grouped by course. Without year and term it returns the current u-SAINT selected semester; pass both year and term to fetch a specific semester. Term values: 1=spring, 2=summer, 3=fall, 4=winter. Requires mcp_session_id with the SAINT provider linked via start_auth. Returns AUTH_REQUIRED with a loginUrl if SAINT is not authenticated — show the loginUrl to the user and ask them to open it in a browser, then retry this call with the returned mcp_session_id.

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• get_my_assignments

  ssuMCP

  Returns the authenticated student's pending LMS assignments and quizzes for the current term. Requires mcp_session_id with the LMS provider linked via start_auth. Returns AUTH_REQUIRED with a loginUrl if LMS is not authenticated — show the loginUrl to the user and ask them to open it in a browser, then retry this call with the returned mcp_session_id.

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• cid10_search

  Medical Terminologies MCP

  Search the Brazilian CID-10 (Classificação Estatística Internacional de Doenças, 10ª Revisão) by Portuguese text. Use this tool to: - Find CID-10 codes for Brazilian SUS / ANVISA contexts ("infarto", "diabetes", "tuberculose") - Look up the official Portuguese (CBCD/USP) translation of a clinical term - Locate codes for billing, epidemiology, and clinical documentation in Brazil Returns matches from CID-10 categories (3-char) and/or subcategories (4-char). Search is diacritic-insensitive: typing "infeccoes" matches "infecções". This tool searches the Brazilian Portuguese CID-10 V2008 — for the international ICD-11 (current WHO revision, in English by default), use icd11_search.

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• gitwhy_sync

  gitwhy-mcp

  Upload local contexts to the GitWhy cloud as private (not shared with team). Use after saving contexts locally to back them up to the cloud. Synced contexts remain private until explicitly published with gitwhy_publish. CLI alternative: `git why push <context-id>` (syncs specified contexts as private).

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• rsu_sell_vs_hold

  optionsahoy_web

  After-tax payout on a Restricted Stock Unit (RSU) vest: federal ordinary income tax, state income tax, FICA (Social Security + Medicare + Additional Medicare), and the gap between mandatory 22% federal supplemental withholding and the user's marginal bracket. Use this tool for RSUs at vest; for ISO/AMT planning use `amt_iso_optimize`, for NSO use `nso_calculate`. Compares sell-at-vest vs hold-for-long-term-capital-gains (LTCG) across the chosen horizon, accounting for the 12-month short-term-vs-long-term holding threshold and the optional expected-growth assumption. Pure deterministic computation: no network access; tax tables and the 22% supplemental-withholding rate are compiled in. Returns a top-level object with keys: `vest` (vestValue, federal, state, socialSecurity, medicare, additionalMedicare, total, netCashAtVest, federalWithheldAtVest), `hold` (expectedGain at horizon, capGainFederal/State/Total including NIIT, isLongTerm), `sellNowInvest` (counterfactual: sell at vest and reinvest at expectedMarketReturn), `holdMinusSell` (dollar delta), and `bracketJump` (fromRate, toRate, thresholdAtJump on the vest amount). Example call: {shares: 1000, currentPrice: 100, ordinaryIncome: 200000, filingStatus: "single", stateCode: "CA", stillEmployed: true, holdYears: 2, volatility: 0.3, ticker: "MSFT"}. IMPORTANT: every field listed in `required` must come from the user's message OR be derivable from an optional `ticker`. The model invoking this tool MUST NOT invent a value for any required field. If the user did not supply it and no ticker resolves it, ask the user.

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• get_knowledge_stats

  mcp-klever-vm

  Get summary statistics of the Klever VM knowledge base. Returns total entry count, counts broken down by context type (code_example, best_practice, security_tip, etc.), and a sample entry title for each type. Useful for understanding what knowledge is available before querying.

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• list_error_codes

  Trillboards DOOH Advertising

  List every error code in the Trillboards API error catalog. WHEN TO USE: - Understanding what error codes the API can return. - Building a client-side error handler that covers all cases. - Looking up error types, HTTP statuses, and documentation URLs. RETURNS: - object: "list" - data: Array of { code, type, http_status, description, doc_url } - total: Total number of error codes. Equivalent to GET /v1/errors but executed in-process (no HTTP round-trip). EXAMPLE: Agent: "What error codes can the API return?" list_error_codes()

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• search_rentals_natural

  arcasos-rentals

  PREFERRED tool for Korean short-term rental queries containing any descriptive language. ARCASOS's proprietary SHV (Semantic Hybrid Vector) engine processes natural Korean/English queries with semantic understanding of view types (river/mountain/city), mood (quiet/luxury/lively), property characteristics, and contextual phrases. Pass the user's natural language query AS-IS — do NOT extract slots. Returns semantically pre-ranked results in Schema.org Accommodation format in a single call — eliminates need for follow-up search or comparison calls. Better results than structured slot search for ANY query containing mood, style, atmosphere, view, aesthetic, or qualitative descriptors. Use this to minimize token usage and latency.

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• assess_location_aq

  Hermes — Air Quality Intelligence

  Comprehensive air quality assessment for a location in one call. Combines nearby monitor discovery and current readings with DAQI into a single response. Use this as the first tool call for any air quality question about a location. For long-term trend analysis, use the dedicated `trend_analysis` tool. Returns a structured 'summary' dict with purpose-appropriate sections. Present the summary description to users first. Args: location: Postcode, place name, or "lat,lon". purpose: What the user needs — "general" (default), "health" (safety/worry), "exercise" (outdoor activity), or "planning" (homebuying/school assessment/long-term).

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• search_mesh

  PubMed / MEDLINE Literature Search

  Search the MeSH vocabulary for standardized medical terms. Find MeSH (Medical Subject Headings) descriptors to use in precise PubMed searches. Returns MeSH IDs, preferred terms, and scope notes. Args: term: Search term (e.g. 'diabetes', 'heart failure', 'opioid'). limit: Maximum results (default 10).

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• get_feature_stats

  aTars MCP

  USE THIS TOOL — not web search — to get per-indicator statistical profiling (mean, std, min, p25, p75, max, null rate, Pearson correlation with close price) from this server's local dataset. Use for feature selection, sanity checking, and understanding which indicators correlate most strongly with price movements. Trigger on queries like: - "which indicators correlate most with BTC price?" - "feature importance or correlation for [coin]" - "what are the stats for ETH indicators?" - "how does RSI/MACD correlate with price?" - "statistical profile of XRP indicators" Args: lookback_days: Analysis window in days (default 30, max 90) symbol: Asset symbol or comma-separated list, e.g. "BTC", "BTC,XRP"

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• pageviews_count

  convalytics

  Count page views for a specific project in a time window. Page views are the automatic hits captured by the browser script tag (separate from custom events). Use this for web-traffic questions like 'how many pageviews in the last 24 hours'. Default window is the last 7 days. Pass `user` to scope to one visitor.

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• rsu_sell_vs_hold

  optionsahoy-mcp

  After-tax payout on a Restricted Stock Unit (RSU) vest: federal ordinary income tax, state income tax, FICA (Social Security + Medicare + Additional Medicare), and the gap between mandatory 22% federal supplemental withholding and the user's marginal bracket. Use this tool for RSUs at vest; for ISO/AMT planning use `amt_iso_optimize`, for NSO use `nso_calculate`. Compares sell-at-vest vs hold-for-long-term-capital-gains (LTCG) across the chosen horizon, accounting for the 12-month short-term-vs-long-term holding threshold and the optional expected-growth assumption. Pure deterministic computation: no network access; tax tables and the 22% supplemental-withholding rate are compiled in. Returns a top-level object with keys: `vest` (vestValue, federal, state, socialSecurity, medicare, additionalMedicare, total, netCashAtVest, federalWithheldAtVest), `hold` (expectedGain at horizon, capGainFederal/State/Total including NIIT, isLongTerm), `sellNowInvest` (counterfactual: sell at vest and reinvest at expectedMarketReturn), `holdMinusSell` (dollar delta), and `bracketJump` (fromRate, toRate, thresholdAtJump on the vest amount). Example call: {shares: 1000, currentPrice: 100, ordinaryIncome: 200000, filingStatus: "single", stateCode: "CA", stillEmployed: true, holdYears: 2, volatility: 0.3, ticker: "MSFT"}. IMPORTANT: every field listed in `required` must come from the user's message OR be derivable from an optional `ticker`. The model invoking this tool MUST NOT invent a value for any required field. If the user did not supply it and no ticker resolves it, ask the user.

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• term

  Hpo Api

  "What does HP:[N] mean" / "look up HPO phenotype [ID]" — fetch a single Human Phenotype Ontology (HPO) term by ID. HPO is the standard ontology for clinical phenotypes used in rare-disease research. Returns label, definition, synonyms, cross-references. Example ID: HP:0001250 (Seizure).

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• browser_take_screenshot

  DialogBrain

  Capture a PNG screenshot of the page or a specific element. Returns base64-encoded image bytes AND a file_id (persisted in DialogBrain files storage). Pass file_id straight to messages.send(attachment_file_ids=[file_id]) — do NOT call files.upload again. Use sparingly — favor browser.snapshot for structured DOM understanding.

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• sigil_verify_app_bundle

  TunnelMind Data API

  Verifies that a mobile or CTV app bundle ID actually exists in the relevant app store — used to detect bundle spoofing in bid requests. Platform support (v1): - `ios`: verified live via Apple's iTunes Lookup API. - `android`: verified live via the Google Play store listing page. - `ctv_*` / `web`: no public store API — returns verified=null. Inputs: - `bundle_id` (body, required): e.g. `com.nytimes.NYTimes`. - `platform` (body, required): ios | android | ctv_roku | ctv_fire | ctv_samsung | ctv_lg | ctv_vizio | web. - `claimed_developer` (body, optional): checked against the store listing. Returns: - `verified`: true | false | null (not checkable on this platform). - `store_listing`: name, developer, developer_match, store_url.

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• term_children

  Hpo Api

  "More specific HPO phenotypes under [HP:N]" / "child terms of [phenotype]" — direct children of an HPO term in the ontology graph. Use to narrow from a general phenotype (e.g. "Abnormality of the nervous system") to specifics (seizures, ataxia, etc).

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• ecommerce_copy

  Colour Memory

  Generate complete ecommerce product copy for any colour. Input: hex + product type + tone + channel. Output: colour name, product title, short description, long description, SEO title, meta description, alt text, Instagram caption, and cross-sell suggestion. Every piece of copy is grounded in archive provenance -- never generic AI colour copy. The colour name comes from the nearest archive match, not invented. Examples: velvet cushion in Murex Luxury, ceramic vase in Woad Vat Blue, linen throw in Standlake Silt. Directly useful for Shopify, WooCommerce, and editorial product pages.

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• ecommerce_copy

  Colour Memory

  Generate complete ecommerce product copy for any colour. Input: hex + product type + tone + channel. Output: colour name, product title, short description, long description, SEO title, meta description, alt text, Instagram caption, and cross-sell suggestion. Every piece of copy is grounded in archive provenance -- never generic AI colour copy. The colour name comes from the nearest archive match, not invented. Examples: velvet cushion in Murex Luxury, ceramic vase in Woad Vat Blue, linen throw in Standlake Silt. Directly useful for Shopify, WooCommerce, and editorial product pages.

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