MLB API MCP Server

Overview

The MLB API MCP Server serves as a dedicated bridge between AI assistants and the rich ecosystem of Major League Baseball data. By exposing MLB statistics, game information, player bios, and live‑game feeds as MCP tools rather than traditional REST endpoints, the server allows AI models to retrieve up‑to‑date baseball content with a single, well‑typed request. This eliminates the need for custom parsers or manual API key handling in client applications, streamlining development and ensuring consistent data quality.

What the server solves is twofold. First, it consolidates disparate baseball data sources—standings, schedules, sabermetrics, play‑by‑play logs, and even video highlights—into a unified, schema‑validated interface. Second, it packages that data into the MCP tool model so that any AI client following the Model Context Protocol can call these tools directly, receive structured JSON responses, and embed them into conversations or workflows. Developers building sports analytics dashboards, fantasy‑league assistants, or real‑time commentary bots can therefore focus on business logic while the server handles data fetching, caching, and validation.

Key capabilities include:

• Comprehensive MLB coverage: standings, schedules, team rosters, player stats (traditional and advanced sabermetrics), live game boxscores, linescores, play‑by‑play events, and video highlights.
• Flexible querying: filter by league, season, date range, team, or player name; retrieve specific event types within a game.
• Tool‑centric API: each functionality is exposed as an MCP tool (e.g., , ), ensuring type safety and clear contracts for AI clients.
• Automatic documentation: visiting generates interactive tool listings and schema previews, simplifying onboarding for developers.

Real‑world use cases abound. A fantasy baseball assistant can query and to advise lineup decisions, while a sports journalist’s chatbot can pull live play‑by‑play data via to generate instant game summaries. A coaching analytics platform might use to evaluate opponent strengths, and a mobile app could embed video highlights from to keep fans engaged between innings.

Integration into AI workflows is straightforward: an MCP‑enabled client sends a JSON payload to specifying the desired tool and parameters. The server returns a fully typed response, ready for the assistant to interpret or present. Because all data is fetched through a single protocol endpoint, developers can swap out the MLB backend for another sports API without changing client logic—only the MCP tool list would update. This modularity, combined with robust schema validation and live data access, makes the MLB API MCP Server a powerful asset for any developer looking to enrich AI applications with authoritative baseball information.