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MLB Stats MCP Server

@etweisberg

代码仓库

基本信息

分类

其他

传输方式

stdio

作者

etweisberg

关于 MLB Stats MCP Server

MCP server for advanced baseball analytics (statcast, fangraphs, baseball reference, mlb stats API)

#mcp#baseball-statistics#statcast#baseball-data#mlb-stats-api#baseball-analytics#fangraphs#mcp-server#mcp-client

MLB Stats MCP Server 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "mlb-mcp": {
      "command": "uv",
      "args": [
        "venv"
      ]
    }
  }
}

MLB Stats MCP Server 工具

工具列表暂未提供

当前收录暂时没有可展示的工具列表，不代表服务没有工具。请查阅项目文档了解支持的能力。

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

What is MLB Stats MCP Server?

A Python project that implements a Model Context Protocol (MCP) server for accessing Major League Baseball statistics. It combines the MLB Stats API and the pybaseball library (Statcast, FanGraphs, Baseball Reference) to provide structured baseball data to MCP-compatible clients like Claude Desktop.

How to use MLB Stats MCP Server?

Install uv, create a virtual environment (uv venv), activate it, and install dependencies (uv pip install -e .). Set the ANTHROPIC_API_KEY environment variable and optionally configure logging. Then add the server to your MCP client (e.g., Claude Desktop) using the provided JSON configuration.

Key features of MLB Stats MCP Server

  • Combines MLB Stats API, Statcast, FanGraphs, and Baseball Reference data.
  • Generates matplotlib plots returned as base64-encoded images.
  • Configurable logging via environment variables (MLB_STATS_LOG_LEVEL, MLB_STATS_LOG_FILE).
  • Comprehensive test suite using pytest and pytest-asyncio.
  • Linting and code formatting enforced by Ruff and pre-commit hooks.
  • Option to install automatically via Smithery for Claude Desktop.

Use cases of MLB Stats MCP Server

  • Query player statistics, game logs, and team data from multiple MLB sources.
  • Retrieve Statcast metrics (exit velocity, launch angle, etc.) for advanced analysis.
  • Generate and view matplotlib visualizations of baseball data.
  • Integrate real-time baseball data into AI assistants using MCP protocol.

常见问题

1

What dependencies does the server require?

Python, `uv` (package manager), and libraries including `mcp[cli]`, `mlb-statsapi`, `httpx`, `pytest`, `pytest-asyncio`, and `matplotlib` (for plotting).

2

How do I install the server?

Run `uv venv && source .venv/bin/activate && uv pip install -e .` in the project directory. Alternatively, install via Smithery with `npx -y @smithery/cli install @etweisberg/mlb-mcp --client claude`.

3

How do I configure the server for Claude Desktop?

Add an entry to `claude_desktop_config.json` with the `command` set to your `uv` path, `args` pointing to `python -m mlb_stats_mcp.server`, and `env` for logging and API key.

4

How do I configure logging?

Set the environment variables `MLB_STATS_LOG_LEVEL` (e.g., DEBUG, INFO) and `MLB_STATS_LOG_FILE` (path to log file). If the log file is not set, logs go to stdout.

5

What data sources are available through the tools?

The server provides tools for the MLB Stats API, Statcast data, and supplemental `pybaseball` functions for FanGraphs and Baseball Reference statistics.

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