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"Accessing and Viewing Data in a MariaDB Database" 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.
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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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    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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    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
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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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    2
    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.
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    MIT
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    Provides structured access to a World Cup SQLite database via MCP tools, enabling queries for tournaments, team histories, head-to-head matches, and player records.
    4
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    Enables querying volleyball match, team, and tournament data from VolleyballWorld API through SQL queries on a SQLite database.
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    Provides verified NFL stats (2016–2025) and Sleeper league context through an MCP server, with tools for querying metrics, comparing entities, verifying claims, and accessing league data.
    MIT
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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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    Optimizes your starting XI for Biwenger World Cup 2026 using fixed prices, with API endpoints for lineup optimization, player comparisons, and captain picks. Operates locally without accessing your actual Biwenger account.
    MIT
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    Enables triathlon coaches and athletes to interact with Garmin Connect, including retrieving health/activity data, building and uploading structured workouts (cycling, running, swimming, brick), and accessing coaching analytics like readiness, load, and performance trends.
    MIT
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    An MCP server that provides access to over 12 years of NFL play-by-play data through a local DuckDB database. It enables users to query player performance, team statistics, and situational efficiency metrics like EPA and WPA using natural language.
    13
    MIT