"Windows Performance Toolkit and xperf.exe" matching MCP servers:

Answers operational questions about route on-time performance, such as lateness rates and trip evidence, using structured tools for route summary, trip lateness, and data quality.

Compute and analyze bus route lateness using trip data, with drill-down and cross-referencing against rider complaints and operational logs.

Answers whether a route ran late and by how much, with drill-down into individual trip delays and an audit trail of data-quality exclusions and duplicate resolutions.

Enables AI assistants to query and manage logistics shipment data, supporting operations like tracking, quoting, and performance analysis via nine tools backed by a demo dataset or a REST API.

Enables pilots to assemble a preflight briefing per 14 CFR §91.103 by fetching weather, airport info, aircraft performance, fuel estimates, alternates, and NOTAMs.

Live scuba diving planning for AI agents — ranked dive-forecast windows near any place for any day, best-time climatology per destination, marine-life seasonality from GBIF sightings, and facts for 4,800+ dive sites. Free and read-only; hosted at https://pickadive.com/mcp.

A high-performance FastAPI backend for train ticket queries in China, supporting real-time ticket availability, station information, transfers, and train schedules through the Model Context Protocol for AI assistants and automation.

Provides on-time performance analysis for Mumbai North bus routes via tools for route summaries, late trip drill-down, and data quality reports. It quarantines invalid data and surfaces policy questions instead of hidden normalizations.

Enables AI agents to query orders, manage routes, track drivers, and analyze delivery performance on the FleetSync last-mile delivery platform through natural language.

Provides auditable Mumbai route lateness metrics, including route ranking, performance summaries, and trip-level evidence, derived from a reloadable CSV dataset.

Enables searching 12306 railway ticket information, filtering trains, querying passing stations, and searching transfer routes through MCP.

Enables AI assistants to retrieve real cabin layouts, compare free seats against traveller preferences, access seat reviews and ratings, and create seat alerts for flights across 150+ airlines.

Provides AI assistants with real-time and forecast airport intelligence, including security wait times, FAA delays, EU border queues, lounge and terminal info, aviation weather, and baggage performance for over 8,000 airports.

Tour and excursion search on supertours.ru — destinations across Russia and abroad.

Enables AI assistants to search and compare airport lounges worldwide and check access eligibility by credit card, membership, airline status, or ticket class, with optional sign-in for logging visits, writing reviews, and maintaining a wishlist.

RollingGo MCP is a high-performance hotel search and recommendation service built on the MCP (Model Context Protocol) standard. It connects large language models with a massive database of domestic and international hotel data, providing real-time structured hotel search capabilities for AI assistants, agents, travel planning tools, or IDE plugins like Cursor/Windsurf.

Enables AI assistants to search flights and hotels, manage bookings, check flight status, and access delay statistics through the TravelCode corporate travel API, all via natural language conversations.

Flexible multi-leg, multi-airport flight search that finds the cheapest route across an entire itinerary — available as a CLI and as an MCP server for AI agents.

Enables AI clients to explore cheapest destinations, optimize multi-leg flight itineraries, and reference airport/region data via MCP tools and resources.

A Model Context Protocol (MCP) server that provides access to a trip tracking SQLite database. This server enables AI assistants to query and manage flight trip information including users, airports, and flight details.