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    MCP server for RapidOddsAPI that provides bookmaker odds, live scores, arbitrage and value bets to AI assistants. It supports querying sports, odds, results, and betting opportunities with credit-based usage.
    5
    MIT
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    Enables AI agents to query live sports betting data including odds, edges, arbitrage opportunities, player/team stats, and reference data using the SportWizzard API.
    20
    47 npm
    MIT
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    Real-time sports card pricing, market analysis, arbitrage detection, grading ROI, investment advice, and player stats (NBA/NFL/MLB). 9 tools for AI agents helping collectors and investors.
    9
    16 PyPI
    2
    MIT
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    Connects AI assistants to SharpEdge AI to discover +EV sports betting opportunities and arbitrage edges across major sportsbooks. It provides real-time scanner statistics, sample betting edges, and educational content on advanced betting concepts like the Kelly Criterion.
    5
    8 npm
    MIT
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    Enables AI assistants to access sports betting odds data from 265+ bookmakers across 34 sports, including events, odds, historical data, arbitrage, and value bets.
    22
    257 npm
    1
    MIT
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    Enables AI agents to query live sports betting odds, best prices, arbitrage, +EV bets, and middles directly through Model Context Protocol tools.
    8
    MIT
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    Enables LLM-powered race engineers to compute Formula 1 pit-stop strategies from real session data, including tire degradation modeling, optimal pit windows, undercut/overcut simulation, and finish-position projection.
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    Provides AI agents with live, grounded sports data including model probabilities, track records, and European soccer and tennis arbitrage opportunities, so they answer from real numbers instead of stale guesses.
    13
    47 npm
    1
    MIT
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    Provides live Chinese sports lottery (竞彩) odds for World Cup 2026 matches, including 5 betting markets, and integrates with AI predictions and betting strategies.
    2
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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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    Interprets advanced hockey player cards to translate metrics into plain-language assessments, supporting player evaluation, claim verification, and player comparisons with deterministic rules.
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    Enables querying table tennis ratings, players, tournaments, and halls from rttf.ru, with respect for robots.txt restrictions.
    5
    MIT
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    Provides AI agents with direct access to KingsPlaybook's sports data including confirmed lineups, player projections, game lines, and pick history via native MCP tools.
    5
    31 npm
    MIT
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    Analyzes your Trackman golf data to diagnose weaknesses and generate personalized practice plans with drills and progress tracking, acting as a data-driven coach.
    8
    32 PyPI
    1
    MIT
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    Read-only MCP server for sourced Dota 2 tournament, team, player, schedule, and result data from Liquipedia, with revision-level metadata and caching.
    5
    2 npm
    MIT
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    Claudinho gives any MCP client live 2026 World Cup scores, fixtures, group standings, read-only prediction-market signals (Polymarket, informational only), and ready-to-paste match cards. Key-free; the schedule is bundled offline — only live state hits ESPN. Independent fan project — not affiliated with FIFA or Anthropic.
    9
    29
    MIT
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    Provides Claude Code and Claude Desktop with safe, read-only access to your local Garmin training data, readiness decisions, run details, and trends so you can get coaching advice in natural language.
    13
    1
    MIT
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    Four utilities in one server: PDF text, ruled tables and OCR from a URL as pages, documents or RAG chunks; YouTube thumbnail URLs and files with per-size availability; sports scores, schedules and standings across 33 leagues; and ATP/WTA tennis with per-set scores and draws.
    5
    MIT
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    Enables AI agents to read and analyze your Boardsesh climbing logbook across boards like Kilter, Tension, and MoonBoard, with read-only access and optional credentials for personalized recommendations.
    12
    MIT