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    Provides easy access to Formula 1 data including championship standings, event info, season calendars, track visualizations, session results, and driver/constructor info via FastF1 and OpenF1 API.
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    MIT
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    Provides comprehensive Formula 1 data and analytics for Claude Desktop, including race results, telemetry, standings, and strategy insights through 36+ tools.
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    MIT
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    Enables querying K League official data (rankings, matches, players) via SQL using natural language, with a pre-built SQLite database.
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    Provides live Formula 1 data such as driver standings, race results, and schedule for the current season, enabling users to ask about F1 without stale training data.
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    A real-time Formula 1 analytics server that lets you ask natural language questions about races, lap times, tyre strategies, pit stops, and more using live data from the OpenF1 API.
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    Provides game rules, roster constraints, FAQ, and official links for the 27-0 NRL fantasy draft game, enabling AI clients to retrieve this knowledge.
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    MIT
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    Provides professional cycling data from FirstCycling, allowing users to retrieve comprehensive information about cyclists, race results, historical cycling data, and team information through natural language queries.
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    MIT
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    Exposes the canonical 17-0 knowledge surface including game rules, roster constraints, and entry points for the NFL roster strategy game to MCP-compatible AI clients.
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    A Model Context Protocol server that provides comprehensive Formula One racing data, enabling access to event schedules, driver information, telemetry data, race results, and performance analytics through natural language queries.
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    This project implements a Model Context Protocol (MCP) server providing Formula One racing data using the Python FastF1 library. Inspired by an existing TypeScript server, it offers similar F1 data functionalities natively in Python via FastF1.
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    Provides Formula One data and statistics through a Model Context Protocol interface, allowing users to access race calendars, session results, driver statistics, telemetry data, and championship standings.
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    Provides comprehensive Formula 1 data access including race schedules, session results, lap times, telemetry data, driver/constructor standings, and circuit information. Enables users to retrieve and analyze F1 racing data through natural language queries using the FastF1 Python package.
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    MIT
  • F
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    Provides advanced Formula 1 analytics including real-time telemetry processing, tire degradation modeling, weather impact analysis, and Monte Carlo race strategy simulation for comprehensive F1 data analysis.
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    An MCP server that provides 118+ Formula 1 analytics tools, enabling race analysis, driver comparisons, telemetry exploration, and strategy simulation through natural language.
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    MIT