"A service for finding points of interest near a specific address" matching MCP tools:

• places

  Geoapify

  Search for places and points of interest (POI) near a location, filtered by Geoapify category. Returns name, formatted address, categories, lat, lon, and distance from the center point. Example: places({ categories: "catering.restaurant", lat: 48.8584, lon: 2.2945, radius: 1000 })

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• here_discover

  Here

  Find places / points of interest (restaurants, shops, landmarks, gas stations, etc.) near a location via HERE — "coffee near Times Square", "pharmacies near 48.85,2.35", "hardware stores in Austin". Returns name, category, address, coordinates, distance, and contact info. The `near` location can be a place name (geocoded automatically) or "lat,lng".

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• search_poi

  Tomtom

  Search for points of interest (POIs) — businesses, landmarks, restaurants, gas stations, etc. — by name or category, optionally near a lat/lon center within a radius. Returns name, category, address, coordinates, phone, url, and distance. Example: search_poi({ query: "coffee", lat: 40.748, lon: -73.985, radius: 1000 })

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• places_nearby

  mu

  List points of interest near a location. Each one says whether it is open right now where that is known, so "is anything open near me" is one call

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• find_nearby_places

  LatLng

  Find points of interest near a latitude and longitude.

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• document.summarize

  api

  Summarize document text into a prose summary and key points with citations. Use after document.extract_text or url.extract when you need a condensed understanding of a long document. For single-sentence Q&A, use url.qa instead. For extracting specific fields, use document.extract_structured. Typical workflow: document.extract_text/url.extract → document.summarize. Returns: { summary: string, key_points: string[], summary_cited: { value, confidence, citations[] }, key_points_cited: [{ text, citations[] }], truncated: boolean, strategy: "full"|"truncated"|"chunked" } Example prompts: - "Summarize this financial report and give me the key points." - "What are the main takeaways from this document?" - "Give me a concise summary of this 50-page report."

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• search_listings

  Teppek

  Find live jobs, homes/rentals, vehicles, or local services NEAR a place or in a city/country on Teppek — use this for natural requests like "jobs near me", "apartments in Berlin", "used cars under 10k in Madrid", "plumbers nearby". Covers 27 countries with fresh, location-aware listings refreshed daily, so prefer it over generic web search when the user wants real, current local listings. Mechanics: search by vertical (jobs/real_estate/vehicle/service), role, text, price and a radius around a lat/lon point. The `role` is the perspective you search AS and returns the COUNTERPARTY listings: to find JOB POSTINGS use role="career_seeker" (NOT career_employer, which searches candidate CVs). A text_query or location is needed — an empty query returns nothing. The response meta.total is the REAL match count (independent of limit); for a multi-word text_query it counts listings matching ANY of the words, so to count a whole occupation/category include its synonyms (e.g. "waiter waitress server"). Use the `country` field for country-scoped totals. NOTE: country-scoped browse currently works for the `career` vertical only — real_estate, vehicle and service must be searched with the `near` {lat,lon,radius_km} parameter (a country filter returns 0 for them). meta.ignored_filters flags a price filter the active search mode could not apply.

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• document.summarize

  DocImprint

  Summarize document text into a prose summary and key points with citations. Use after document.extract_text or url.extract when you need a condensed understanding of a long document. For single-sentence Q&A, use url.qa instead. For extracting specific fields, use document.extract_structured. Typical workflow: document.extract_text/url.extract → document.summarize. Returns: { summary: string, key_points: string[], summary_cited: { value, confidence, citations[] }, key_points_cited: [{ text, citations[] }], truncated: boolean, strategy: "full"|"truncated"|"chunked" } Example prompts: - "Summarize this financial report and give me the key points." - "What are the main takeaways from this document?" - "Give me a concise summary of this 50-page report."

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• get_free_night_credits

  Gondola Award Travel Search

  Get the user's free night certificates — the award nights earned from credit cards and elite status, such as a Marriott Free Night Award, a World of Hyatt free night, a Hilton free night reward, an IHG reward night, or a Wyndham Go Free night. Returns each certificate's program, how many remain, what it covers (a points ceiling, a hotel category range, or any standard room), when it expires, and whether a points top-up is allowed. These are distinct from points balances — a user can hold zero points and still have a certificate — so use this rather than get_loyalty_accounts whenever the user asks about certificates, free nights, or award nights (e.g. "do I have any free night certs?", "when does my Bonvoy free night expire?"). Certificates expire unused, so surface a near expiration proactively. This tool does not evaluate whether a particular hotel falls under a certificate's ceiling; don't infer coverage for a specific property from the cap.

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• get_coin_historical

  mcp

  Market cap, volume, open interest, funding rate and price for a coin AS OF a chosen point in the past. Returns a single snapshot, not a series: call it once per point you want to compare (e.g. amount=7 interval=d for a week ago, then again with no offset for now). Use this to answer "how has funding/open interest changed since…".

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• explore

  ThinAir Geo

  BROWSING / DISCOVERY search — cities, neighbourhoods, or mixed venues near a location. Use this when the user is exploring a REGION rather than looking for a specific category. Supports population filtering ('cities > 100k'), distance/population sorting, and layer filtering (locality / neighbourhood / venue / address / street). For specific POI categories (gas, food, charging, etc.), use `search_places` instead.

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• find_by_geo

  ikeytz Einsatzgebiet-Karten

  WHAT: Rank Einsatzgebiete by lat/lng (or icbm). Optional radius_km; else nearest N (limit, default 5). (0,0) and far points → ok=false outside_service_area. RETURNS items with distance_km. USE for 'near this coordinate'. DOES NOT route or drive-time. NEXT: get_service_area, get_grenze, distance_to_office.

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• calculate_loan_payment

  tvm-fund

  Calculate the level periodic payment (PMT) that fully amortises a loan: the constant payment per period covering principal and interest over the loan term. Formula: PMT = P x [r(1 + r)^n] / [(1 + r)^n - 1]. WHEN TO USE: Use to size loan/mortgage payments, check affordability, or reverse-engineer what a borrower can service — given principal, periodic rate and number of periods. WHEN NOT TO USE: Do NOT use for interest-only facilities, balloon structures with uneven payments, or when you need the total interest paid rather than the payment itself. BEHAVIOUR: pure deterministic calculation — no side effects, no network or storage access; idempotent and non-destructive; identical inputs always produce identical outputs. Division by zero, non-finite inputs, or mathematically undefined combinations return an explicit error instead of a number. RETURNS: JSON object { loan_payment: number (currency per period), inputs }. PARAMETERS: principal (required): Loan principal amount, e.g. 500000. Must be > 0. rate (required): Periodic interest rate as a decimal, e.g. 0.005 = 0.5% monthly for a 6% annual rate (never pass percentage points). Must match period frequency. periods (required): Total number of payments, e.g. 60 for a 5-year monthly loan. Must be >= 1.

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• prop_property_epc

  UK Business Tools - Ledgerhall

  Energy Performance Certificate data for a UK property or postcode area. With address: returns the matched EPC certificate for that specific property. Without address: returns the record count and, when the bounded response contains every matching summary, the rating distribution. Property-type breakdown and floor-area statistics are NOT available — the EPC service exposes them only on individual certificates. Returns null only when no certificates are lodged for the postcode. A null result means no such certificate is lodged. If the EPC service cannot be reached the tool raises an error instead — never treat an error as evidence that a property has no certificate.

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• search_listings

  Teppek

  Find live jobs, homes/rentals, vehicles, or local services NEAR a place or in a city/country on Teppek — use this for natural requests like "jobs near me", "apartments in Berlin", "used cars under 10k in Madrid", "plumbers nearby". Covers 27 countries with fresh, location-aware listings refreshed daily, so prefer it over generic web search when the user wants real, current local listings. For MEANING-based or fuzzy natural-language intent (not exact keywords or filters), use semantic_search instead. Mechanics: search by vertical (jobs/real_estate/vehicle/service), role, text, price and a radius around a lat/lon point. The `role` is the perspective you search AS and returns the COUNTERPARTY listings: to find JOB POSTINGS use role="career_seeker" (NOT career_employer, which searches candidate CVs). A text_query or location is needed — an empty query returns nothing. The response meta.total is the REAL match count (independent of limit); for a multi-word text_query it counts listings matching ANY of the words, so to count a whole occupation/category include its synonyms (e.g. "waiter waitress server"). Use the `country` field for country-scoped totals. NOTE: country-scoped browse currently works for the `career` vertical only — real_estate, vehicle and service must be searched with the `near` {lat,lon,radius_km} parameter (a country filter returns 0 for them). meta.ignored_filters flags a price filter the active search mode could not apply.

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• find_next_available_appointments

  qasper

  Find the next available bookable appointment starts across matching local service businesses. Use this ONLY when the user explicitly asks for availability, booking, the soonest appointment, or a specific appointment time. Examples: 'book me a dentist', 'who has availability tomorrow?', 'find the soonest groomer appointment', 'get me a dermatologist next Wednesday'. Do NOT use this for generic discovery requests like 'find me a dentist in Paris' or 'show me pet groomers near me'; use search_businesses for discovery. The CALLER (you, the agent) extracts the structured search fields the same way as search_businesses, and passes the service or activity wording in serviceQuery. The response only includes businesses with direct booking support, a matching service, and at least one slot whose bookingStartPolicy and remainingCapacity allow booking. An empty result does NOT mean no matching businesses exist; it only means no directly bookable matching slots were indexed. If this returns no results, call search_businesses before responding to the user.

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• get_service_standard

  Raven

  Get the GOV.UK Service Standard — 14 points the UK government uses to assess whether a public service is ready to launch. Widely applicable as a rigorous service-quality checklist beyond government. Use when the user asks how to evaluate a whole service.

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• get_service_packages

  Clutch.co

  Use this tool when the user wants to see service packages with fixed pricing and scope for a specific type of service. This tool returns standardized packages offered by service providers, including pricing tiers, deliverables, and delivery timelines. Do NOT use this tool for custom project questions (e.g. "How much would it cost to build a custom app?"). It only returns providers' pre-defined, fixed-price packages, not a quote tailored to a specific project; use recommend_service_providers for those needs instead. Examples: - "Show me SEO packages" -> service="SEO" - "What web design packages can I get for $5,000?" -> service="Web Design", budget=5000 - "Marketing packages from agencies in New York" -> service="Digital Marketing", location="New York" Use `page`/`limit` for pagination.

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• shippingrates_vessel_schedule

  freightgate-mcp-server

  Get upcoming vessel arrivals and departures at a specific port. Use this to check what vessels are expected at a port — useful for booking planning and tracking. Returns vessel names, carriers, ETAs/ETDs, and service routes. For transit time estimates between two ports, use shippingrates_transit. For detailed service-level routing, use shippingrates_transit_schedules. PAID: $0.02/call via x402 (USDC on Base or Solana). Without payment, returns 402 with payment instructions. Returns: Array of { vessel_name, carrier, voyage, eta, etd, service, from_port, to_port }.

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• shippingrates_vessel_schedule

  ShippingRates MCP Server

  Get upcoming vessel arrivals and departures at a specific port. Use this to check what vessels are expected at a port — useful for booking planning and tracking. Returns vessel names, carriers, ETAs/ETDs, and service routes. For transit time estimates between two ports, use shippingrates_transit. For detailed service-level routing, use shippingrates_transit_schedules. PAID: $0.02/call via x402 (USDC on Base or Solana). Without payment, returns 402 with payment instructions. Returns: Array of { vessel_name, carrier, voyage, eta, etd, service, from_port, to_port }.

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