Which sports leagues and events are covered?

It offers extensive coverage of major professional leagues including NFL, NBA, MLB, NHL, MLS, Premier League, Champions League, alongside NCAA college football, basketball, and baseball.

What kind of sports data can I access?

You can access live scores, detailed team information, game summaries, college rankings, league standings, multi-league news, and historical data across 20+ specific ESPN API endpoints.

Does it support advanced data filtering?

Yes, the server features advanced parameter support, allowing detailed data filtering by dates, specific weeks, season types (preseason, regular, postseason), and team identifiers for precise results.

How can I deploy and use the ESPN MCP Server?

The server supports flexible deployment via Node.js (STDIO and HTTP streaming modes), Docker, and Kubernetes. It's designed for seamless integration with MCP clients or as a standalone HTTP API.

What is the ESPN MCP Server?

The ESPN MCP Server is a modern Model Context Protocol (MCP) server designed to provide developers with comprehensive, real-time access to ESPN's hidden sports APIs.

ESPN

Name: ESPN
Author: DynamicEndpoints

byDynamicEndpoints

0•

Desarrollo de API

Analíticas y Monitorización

Web Scraping y Recopilación de Datos

Provides comprehensive access to ESPN's hidden sports APIs via a modern Model Context Protocol server, offering real-time data and advanced filtering capabilities.

The ESPN tool acts as a robust Model Context Protocol (MCP) server, designed to unlock and centralize access to ESPN's extensive, often hidden, sports APIs. Built with TypeScript, it offers a production-ready solution for developers and AI agents needing real-time and historical sports data across a multitude of leagues including NFL, NBA, MLB, NHL, and various college sports. With features like advanced parameter support, multi-transport options (STDIO and HTTP), smart routing, and dynamic resources, it streamlines the process of integrating rich sports content into applications or for analytical purposes.

Características Principales

01Extensive coverage of major sports leagues and college sports

02Smart routing for automatic endpoint selection based on sport/league combinations

03Multi-transport support for STDIO and HTTP streaming with MCP compliance

040 GitHub stars

05Comprehensive access to 20+ hidden ESPN API endpoints

06Advanced parameter support for detailed data filtering (dates, weeks, season types)

Casos de Uso

01Integrating real-time and historical sports data into MCP-compatible AI clients and agents.

02Developing web applications requiring ESPN scores, team information, and news via a structured API.

03Powering AI-driven sports analysis, predictions, and head-to-head comparisons for various leagues.