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"A guide for data cleaning and analysis in Excel" matching MCP servers:

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    An MCP server that lets an LLM query a DuckDB warehouse of EuroLeague and EuroCup basketball data in natural language, offering tools for player and team stats, shot charts, boxscores, and fantasy draft analysis without contacting upstream APIs.
    13
    MIT
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    Provides seamless access to iRacing's racing simulation data, enabling AI assistants to retrieve driver profiles, career statistics, and team information. It features automatic authentication and tools for real-time driver lookups and season performance analysis.
    6
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    3
    MIT
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    Access football (soccer) data including competitions, matches, standings, and team details via the Football-Data.org API.
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    MIT
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    Provides football analytics tools including player scouting, comparisons, market-value filters, expected-goals tables, match-by-match form, team attacking profiles, match search, shot maps, and more for 10 leagues.
    6
    GPL 3.0
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    Enables AI agents to access comprehensive sports data including football, basketball, American football, and hockey leagues via 11 tools, with no API key required.
    MIT
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    Provides read-only access to sports data, odds intelligence, and historical stats via 10 MCP tools, with fast response times through Redis caching.
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    Enables fast real-time web search and access to premium data from trusted sources including news, financial markets, sports, and more. Supports AI agents with live data and curated content from various domains.
    10
    MIT
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    An open-source MCP server that connects to the SoccerDataAPI to deliver up-to-date football match information via natural language interactions.
    39
    MIT
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    NHL hockey data MCP server. 12 tools covering games, standings, player stats, goalie stats, odds, line movement, and matchup analysis across 16 seasons.
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    MIT
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    Tells you when your favourite football teams play and where to watch in Denmark, using data from TheSportsDB.com and built-in Danish broadcast hints.
    4
    MIT
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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.
    17
    1
    MIT
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    Enables AI assistants to analyze Fantasy Premier League data, providing tools for player search, fixture analysis, manager comparisons, and strategy prompts for transfer planning and lineup selection.
    19
    MIT
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    Enables natural language interaction with Sleeper Fantasy Football API data, allowing queries about leagues, players, matchups, draft results, and trade analysis.
    13
    13
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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.
    8
    2
    MIT
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    MCP server that provides F1 telemetry analysis, tyre degradation modeling, and pit strategy recommendations, delivering race engineer-style calls grounded in real data. It exposes tools for degradation fits, fuel correction, and strategy reasoning via LangGraph.
    4
    MIT
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    Python MCP server that provides comprehensive access to MLB statistics and baseball data through a FastAPI-based interface. Acts as a bridge between AI applications and MLB data sources, enabling seamless integration of baseball statistics, game information, player data, and more.
    24
    57
    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.
    13
    5