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165,143 tools. Last updated 2026-05-31 16:04

"MLB" matching MCP tools:

  • Generate optimal DFS lineups using linear programming for NBA, NFL, MLB, or NHL. Apply cash game, tournament, or balanced strategies with player constraints and stacking preferences to maximize projected points within salary caps.
    MIT
  • Retrieve real-time betting odds from multiple sportsbooks for NBA, NFL, MLB, or NHL games, including spreads, totals, moneylines, and player props with line movement history.
    MIT
  • Retrieve available sports categories on Polymarket prediction markets to identify betting opportunities across leagues like NBA, NFL, EPL, and MLB.
    MIT
  • Retrieve full-season pitching statistics for an MLB team, including rotation and bullpen data from FanGraphs or Baseball Reference. Specify team abbreviation, season year, and optional pitcher name to access ERA, wins, strikeouts, WAR, and other metrics.
    MIT
  • Retrieve comprehensive batting statistics for an entire MLB team's roster during a specific season, including individual player data like plate appearances, home runs, averages, and WAR.
    MIT

Matching MCP Servers

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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.
    Last updated
    24
    52
    MIT
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    Connects Claude to the SportRadar MLB API to access real-time baseball data including game schedules, live scores, player statistics, team standings, injury reports, and play-by-play information through natural language queries.
    Last updated
    19
    1

Matching MCP Connectors

  • MLB Stats API MCP — official MLB statistics

  • Provides easy access to MLB, Baseball Savant, Statcast, and Fangraphs baseball data. Query detaile…

  • Analyze MLB hitter performance using Statcast percentile ranks for metrics like exit velocity and barrel rate. Compare players against league averages to evaluate their elite status in specific statistical categories.
    MIT
  • Retrieve scoring plays and highlights from a specific MLB team's most recent game by providing the team name and optional date.
    MIT
  • Create pseudocolor plots for large datasets on irregular grids to visualize 2D data distributions in scientific research.
    MIT
  • Retrieve Outs Above Average (OAA) leaderboards to evaluate defensive performance by position in MLB. This tool calculates how many outs a fielder saved compared to an average defender, using parameters like year, position, and minimum attempts.
    MIT
  • Search and retrieve pitch-level MLB Statcast data within specific date ranges, including pitch types, velocities, spin rates, exit velocities, launch angles, and expected statistics. Filter results by team to analyze baseball performance metrics.
    MIT
  • Retrieve detailed pitch-level data for MLB batters, including pitch types, velocities, exit velocities, launch angles, and expected batting averages within specified date ranges.
    MIT
  • Generate histograms to visualize data distribution and frequency patterns for analysis in machine learning research.
    MIT
  • Retrieve the current date in YYYY-MM-DD format for use with MLB statistics and baseball data operations.
    MIT
  • Identify prediction market divergence events where regulated markets show significant disagreement, revealing opportunities where information is still being incorporated.
    MIT
  • Runs a multi-agent analysis on a game using 12 specialized agents to evaluate odds, injuries, and line movements, delivering a consensus pick with confidence and edge breakdown.
    MIT
  • Create bar plots to compare categorical data values, generating publication-quality visualizations for research analysis.
    MIT
  • Find MLB player IDs and career details by entering a player's name. Use this tool to verify identities and obtain database identifiers for subsequent baseball data queries.
    MIT