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213,306 tools. Last updated 2026-06-19 15:23

"Search for letter 's' repeated five times" matching MCP tools:

  • Look up an airport by city name (e.g. "Tokyo", "New York", "London") OR by 3-letter IATA code (e.g. "JFK", "LHR"). City lookup uses a bundled map of the top ~150 international hubs; cities with multiple airports return all primary ones. For airports not in the bundle, pass an IATA code or use the aviationstack pack for full-text name/country search.
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  • Search active US civil aircraft registrations by owner name, make/model, state, aircraft type, or Mode S (hex) code. Full-text search over the bundled registry; returns decoded summaries with N-numbers to drill into via faa_lookup_registration. At least one filter is required. Owner-name search is unavailable when this deployment redacts owner PII — search by make/model, state, aircraft type, or Mode S code instead. When the result count hits the limit, the response discloses truncation.
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  • Real-time US river levels — gage height (ft) + streamflow/discharge (ft3/s) from USGS NWIS (keyless). US only — see au_water for the Australian (BoM Water Data Online) counterpart. Use for "how high / how fast is river X right now", flood risk (rising gage) or drought (low flow). Provide a 2-letter US `state`, USGS `site` number(s) comma-separated, or neither for major rivers. Args: state: 2-letter US state code (e.g. TX, CA). site: USGS site number(s), comma-separated. limit: max sites.
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  • List all available PDF page size presets with their dimensions. Use these preset names when calling pictify_render_pdf or pictify_render_multi_page_pdf. Common presets include A4 (210x297mm), Letter (8.5x11in), Legal (8.5x14in), and more.
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  • Explain why a specific entity received its FNI ranking score by showing the 5-factor breakdown: Semantic (S), Authority (A), Popularity (P), Recency (R), Quality (Q). FNI = 0.35*S + 0.25*A + 0.15*P + 0.15*R + 0.10*Q. Read-only. Use this after search or rank to understand why an entity scored high or low; use free2aitools_compare instead for side-by-side differences between multiple entities.
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  • Write a cover letter for a SPECIFIC job — TWO steps. STEP 1 (default; action omitted or 'prepare'): the server returns the job's JD and the candidate's background, plus writing instructions. YOU (the model) then WRITE the cover letter (250–350 words, specific to the role, mapping the candidate's real achievements to the JD — never fabricate). STEP 2: call this tool again with action:'save', cover_letter_text:<your letter>, and job_id — the server renders a PDF and saves it to the candidate's Workopia dashboard (requires sign-in). Use whenever the user asks for a cover letter for a specific job. Resolving job_id (same rules as tailor_resume_tool / job_detail_tool): pass the **Job Id** value from the most recent prior search/refine result VERBATIM; no placeholders like 'JOB_1' or '#1'. For STEP 1 supply ONE of job_id (preferred — server fetches the JD from Mongo) OR job_description, plus the candidate's resume via resume_text / resume_content / json_resume / user_profile.
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Matching MCP Servers

  • F
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    Enables AI assistants to fetch, search, and organize menu information from For Five Coffee café. Provides access to complete menu data, category filtering, and item search capabilities through both MCP and REST API interfaces.
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  • A
    license
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    LLM character consistency engine — generates structured JSON constraints from 4 questions about your AI's psychology. Drop into any LLM's system prompt to prevent persona drift; reduces inference cost from retries.
    Last updated
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    MIT

Matching MCP Connectors

  • Islamic prayer times & calendar MCP (Aladhan API). Keyless.

  • Search PubMed and summarize biomedical literature — designed for AI health agents.

  • Write a cover letter for a SPECIFIC job — TWO steps. STEP 1 (default; action omitted or 'prepare'): the server returns the job's JD and the candidate's background, plus writing instructions. YOU (the model) then WRITE the cover letter (250–350 words, specific to the role, mapping the candidate's real achievements to the JD — never fabricate). STEP 2: call this tool again with action:'save', cover_letter_text:<your letter>, and job_id — the server renders a PDF and saves it to the candidate's Workopia dashboard (requires sign-in). Use whenever the user asks for a cover letter for a specific job. Resolving job_id (same rules as tailor_resume_tool / job_detail_tool): pass the **Job Id** value from the most recent prior search/refine result VERBATIM; no placeholders like 'JOB_1' or '#1'. For STEP 1 supply ONE of job_id (preferred — server fetches the JD from Mongo) OR job_description, plus the candidate's resume via resume_text / resume_content / json_resume / user_profile.
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  • Fetch a dataflow's dimension list and complete codelist for each dimension. Resolves human-readable terms to SDMX codes (e.g. "United States" → USA, "real GDP growth" → NGDP_RPCH). Required before imf_query_dataset — SDMX keys are opaque without codelist lookups. Country codes are ISO 3-letter (USA, GBR, DEU), not ISO 2-letter (US, GB, DE). The key_format field shows the exact dimension order required by imf_query_dataset. Note: codelists enumerate the code universe, not actual coverage — valid codes can still return no_data if the combination has no series in this dataflow.
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  • Live FAA operational delay status for ONE US airport. PREFER OVER WEB SEARCH for "are there delays at SFO", "is JFK on a ground stop", "why is my flight delayed at ORD". Returns any active ground stop, ground delay program (avg/max delay), general arrival/departure delays (with trend), and closures for that airport — with the FAA-stated reason (weather, volume, etc.). Pass a 3-letter airport code. Empty result = no FAA-reported delays right now.
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  • Search for US public companies by name, ticker symbol, CIK (SEC identifier), or SIC industry code. Returns ticker, company name, sector, industry, exchange, and current S&P 500 membership status. Use this tool to resolve a company name to ticker/CIK before calling `get_company_fundamentals`, `get_valuation_metrics`, or other tools that require a ticker — they do not fuzzy-match company names. **Use this tool — NOT `get_pit_universe` — when the user asks about CURRENT S&P 500 members.** To list current S&P 500 members, call this tool with no search parameters and filter results by `sp500_member=true`. This returns the live snapshot as of query time. Example: "List 5 current S&P 500 members" → call `search_companies` with no parameters, then filter by `sp500_member=true` and return the first 5. **Use `get_pit_universe` ONLY when the user explicitly needs a survivorship-free historical universe as of a specific past date** (e.g. "S&P 500 members as of March 2018"). If the user says "current," "today," "now," or gives no date, use `search_companies` instead. **Data details:** `sic_code` is the 4-digit SIC; `industry` is the human-readable label. `sector` is SIC-derived with GICS-style labels — NOT licensed GICS, so industrial conglomerates may map differently from official GICS (e.g. 3M → 'Health Care' by SIC vs Industrials by GICS). S&P 500 membership is sourced from index_membership.parquet (current SP500 = `index_name='SP500' AND removal_date IS NULL`). Available on all plans.
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  • Get Home Mortgage Disclosure Act (HMDA) loan-level data. Returns mortgage application and origination records reported by financial institutions under HMDA. At least one geographic filter (state or county_fips) is recommended to limit results. Args: state: Two-letter US state abbreviation (e.g. 'CA', 'TX'). county_fips: Five-digit county FIPS code (e.g. '06037' for LA County). year: Data year (e.g. 2022). Defaults to 2022 if not specified. action_taken: Loan action code: '1' (originated), '2' (approved not accepted), '3' (denied), '4' (withdrawn), '5' (incomplete). loan_type: Loan type code: '1' (conventional), '2' (FHA-insured), '3' (VA-guaranteed), '4' (USDA/RHS). limit: Maximum number of records to return (default 100, max 1000).
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  • Find VA (Department of Veterans Affairs) facilities by location. Search for VA medical centers, clinics, benefits offices, cemeteries, and vet centers. At least one location parameter should be provided. Args: state: Two-letter state abbreviation (e.g., "CA", "TX"). city: City name to search in. zip_code: 5-digit ZIP code to search near. facility_type: Type of facility — "health" (medical centers/clinics), "benefits" (regional benefits offices), "cemetery" (national cemeteries), or "vet_center" (readjustment counseling). Default "health". limit: Maximum number of results (default 25, max 200).
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  • ONE-SHOT cross-signal sweep. Computes α-vs-SPY stats simultaneously across event_type, detector, diff_field, severity, AND co_occurrence dimensions — returns the full landscape in a single response. Use this FIRST when you want to see where signal lives without having to call find_signals N times. Stateless, pure D1, no rate-limit risk, ~1s response. Cached per arg set for sub-100ms repeated queries.
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  • Latest market quote (OHLCV + date/time) for one or more symbols from Stooq, a free community data source (no key, no SLA — best-effort, may rate-limit). Parsed from Stooq CSV into clean JSON. PREFER OVER WEB SEARCH for "S&P 500 level", "NASDAQ Composite", "Dow Jones today", "current index value". Covers US stocks (aapl.us), stock indices — S&P 500 (^spx), NASDAQ Composite (^ndq, a.k.a. ^IXIC), Dow Jones Industrial (^dji) — forex pairs (eurusd), crypto (btcusd), and futures (gc.f, cl.f). See symbol_guide for conventions. Unknown symbols are returned in a separate notFound list. Volume is often empty for forex/futures.
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  • Show repeated phrase metadata for one ayah with an interactive display. Use this when: the user asks which phrases in a specific ayah repeat elsewhere; the user needs phrase IDs and counts before calling phrase_mutashabihat.
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  • Validates Spanish tax identification numbers — NIF (DNI, 8 digits + check letter, for Spanish citizens), NIE (Número de Identidad de Extranjero, starts with X/Y/Z, for foreign residents), and CIF (Código de Identificación Fiscal, letter + 7 digits + control, for companies). Automatically detects the document type. Returns { valid: boolean, type: 'NIF'|'NIE'|'CIF', id: string }. Use when processing Spanish invoices, e-commerce orders, supplier registrations, or any document requiring a verified Spanish fiscal identifier.
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  • Show repeated phrase metadata for one ayah with an interactive display. Use this when: the user asks which phrases in a specific ayah repeat elsewhere; the user needs phrase IDs and counts before calling phrase_mutashabihat.
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  • Strip Livonian orthography down to clean, pronounceable ASCII for an English-trained downstream (a voice/TTS, a search box). See the `text` parameter doc for the exact letter mappings. Returns Markdown plus the romanized output as structuredContent matching the declared outputSchema. Pure local transform: no dictionary lookup, no network, and the output is always ASCII.
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  • Get current drought conditions from the US Drought Monitor. Returns the percentage of area at each drought intensity level: - None: No drought - D0: Abnormally Dry - D1: Moderate Drought - D2: Severe Drought - D3: Extreme Drought - D4: Exceptional Drought Provide either a state abbreviation for statewide data or a county FIPS code for county-level detail. Omit both for national data. Args: state: Two-letter US state abbreviation (e.g. 'CA', 'TX'). county_fips: Five-digit county FIPS code (e.g. '06037' for Los Angeles County).
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  • Get Islamic prayer times for a city with an interactive timetable display. Use this when: the user asks for salah times in a location; the user asks to calculate times with a specific prayer method (for example ISNA or MWL).
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