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"Information on Formula 1" matching MCP servers:

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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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    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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    MIT
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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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    MIT
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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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    MIT
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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.
    5
    MIT
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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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    Enables Formula 1 data analysis through natural language, providing tools like track dominance, lap time analysis, and team performance comparisons.
    Apache 2.0
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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.
    MIT
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    Provides real-time and historical Formula 1 racing data through the Model Context Protocol, offering access to timing data, driver stats, race results, telemetry, and more.
    15
    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 interaction with Formula 1 data through LLM interfaces like Claude. Provides access to F1 information including circuits, constructors, drivers, grand prix, manufacturers, races, and seasons.
    Apache 2.0
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    Exposes Formula 1 historical data (race results, qualifying, pit stops, and championship standings) as callable tools for LLMs via the Jolpica-F1 API.
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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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  • F
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    Enables access to Formula 1 data from the openF1.org API, including driver information, race results, lap times, telemetry, pit stops, weather conditions, and live position data across multiple seasons.
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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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    A local MCP server that gives Claude (or any MCP-compatible AI client) access to Formula 1 race data. Load any session from 2018 onwards, ask questions in natural language, and get answers backed by real telemetry, timing, and strategy data.
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    48 AI-callable tools for FIFA World Cup 2026 football, Formula 1, and IPL cricket — Monte-Carlo bracket simulations, F1 pit-strategy modeling, and a Dream11 ILP optimizer, plus live odds and value-bet detection. Free, open-source, and works with any MCP client via uvx.
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    MIT
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    Provides access to Formula 1 data including driver and constructor championship standings with support for current and historical seasons. Enables users to query F1 championship information through natural language with plans for expanded race data and telemetry.
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    MIT
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    MCP server for Formula 1 data via the FastF1 library. Ask Claude (or any MCP-compatible client) about race results, lap times, telemetry, standings, pit stops, and qualifying — with historical data back to 1950 via the Ergast API.
    21
    MIT
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    Provides verified game rules, official links, and FAQ for the 17-0 NFL roster strategy game to MCP-compatible AI clients.
    2
    MIT