"Answer" matching MCP servers:

Exposes Victoria's public transport (PTV) GTFS timetable data as MCP tools, allowing LLMs to answer natural-language questions about routes, stops, and departure times.

Enables AI clients to answer questions about a signed-in host's Partelisto data, including arrivals, check-in status, SES.HOSPEDAJES submission state, and plan usage, and with granted permission to resend a guest's check-in link.

An MCP server exposing Greater Helsinki public transport data from Digitransit, enabling LLM hosts to answer live transit queries, plan journeys, and fetch stop departures via natural language.

Enables AI assistants to look up verified, sourced dog rules for parks, beaches, trails, campgrounds, hotels and restaurant patios across California and Nevada, including leash and weight restrictions, pet fees and chain policies. It also supports trip planning, hotel matching by dog size and fee budget, highway stop lists, comparisons and change tracking, with each answer citing its official source and the date it was verified.

An MCP server that provides location-based services using Amap APIs, enabling AI assistants to answer navigation queries by resolving addresses, converting coordinates, and comparing walking, driving, and transit routes.

A private location archive with an MCP server, letting an agent answer questions about your past stays, trips, cities, and travel stats from data in your own Postgres.

Enables Claude to answer SEPTA Regional Rail timetable and real-time questions, including next trains, station departures, train positions and delays, and service alerts, with loose station-name matching.

Lets Claude answer questions about GB National Rail trains, including live departures and arrivals, platforms, timetables, service details, and journey planning with live delay overlay.

Enables Claude to estimate at-berth CO₂ for tanker calls and to query Brazilian port statistics, including cargo volumes, berthings, waiting times and hours at berth across ANTAQ installations from 2010 to 2026. Every answer carries its source, method caveats and partial-year warnings so the model can cite and qualify the figures it reports.

A Model Context Protocol server that provides real-time access to Hong Kong's KMB and Long Win Bus route information and arrival times, enabling Language Models to answer user questions about bus routes, stops, and ETAs.

Enables AI assistants to answer questions about Japan's railway network with accurate track-connection data, including station neighbors and local subgraphs for all 9,043 stations nationwide.

Everway turns forwarded confirmation emails into one day-by-day itinerary. This MCP server is a hosted bridge between your Everway account and MCP-compatible AI tools: once connected, your assistant can read your itinerary, answer questions about your plans, and add or update bookings.

A read-only MCP server exposing live eSIM provider, plan, pricing, and coverage data for Kenya from esimkenya.com. Lets AI assistants answer questions like "what's the best eSIM for Kenya / Maasai Mara / Nairobi" with current data and a ready affiliate link, via 3 tools: search/compare providers, get plan details, and head-to-head comparisons.

MCP server that provides tools for querying live transit data (stops, departures, routes, vehicles, alerts) from any WP GTFS Pro site, enabling AI assistants to answer rider questions.

Enables AI agents to answer Boston transit questions from live public data: upcoming MBTA departures and service alerts, nearest Bluebikes bikes and docks, nearby stops and stations, and door-to-door trip options across walking, biking, and transit. Every result reports its sources and as-of time, and the server is read-only.

A unified Model Context Protocol server for Houston-area civic, transit, and flood data, joining incompatible public data systems behind workflow-oriented tools. It enables AI assistants to answer questions like 'is my route flooding right now?' by integrating sources such as TranStar, HCFWS, and the GIS hub.

Enables AI assistants to answer hoteliers' questions about pricing plans, PMS comparisons, OTA commission savings, documentation search, and live demo availability, all grounded in FrontDesko's published pages with source URLs.

Enables users to compare live multimodal travel options — bike taxi, metro, AC cab, and city bus — by geocoding any real-world origin and destination and computing actual road distances, travel times, and dynamic INR fares. It filters out any options that would miss a stated deadline, returning structured route data plus a conversational voice answer for Alexa+ or other MCP-enabled agents.

Gives LLM clients structured, read-only access to Indian Railways data: station lookup, timetables, direct trains between stations, station boards, multi-train journeys, punctuality history, and (when a source is configured) seat availability and fares. Every answer carries provenance and cross-source verification status, so results are either real source data or an explicit error code, never fabricated.

Enables AI assistants to answer tourist queries about Kolkata Durga Puja by providing tools and datasets for pandal details, nearby pandals, metro stations, driving routes, restaurants, and restaurant opening hours.

Enables AI agents to turn flight details and usual sleep times into a science-based, day-by-day jet lag plan with exactly timed light, sleep, caffeine, nap and optional melatonin guidance, plus ready-to-schedule reminders and downloadable calendar files. Its read-only, stateless tools also answer "why" questions and can return only what is still ahead.

A dependency-free MCP server for Mumbai North operations that computes route lateness metrics, exposes underlying late trips, and reports data quality issues to answer whether a route was late and by how much.

Wraps four public railway APIs as 13 tools, 7 prompts and 5 resources, enabling an LLM client to answer live questions about station master data, timetables and timetable changes, elevator and escalator outages, and parking facilities and prognoses.

MCP server that provides real-time weather data, forecasts, city weather comparisons, and travel recommendations using the OpenMeteo API, enabling AI agents to answer weather-related queries and suggest optimal travel conditions.

Skywise is a weather-prediction MCP server that provides current conditions, forecasts, historical data, severe weather alerts, air quality, and travel recommendations. It powers an Agent Bricks agent to answer natural-language weather questions and make simple predictions like 'Will it rain in Chicago tomorrow?'