"Using an MCP server to generate structured ADK agents" matching MCP servers:

Enables AI agents to interact with ActiveNet OpenAPI services for managing organizations, activities, customers, facilities, and more.

This project implements a Model Context Protocol (MCP) server providing Formula One racing data using the Python FastF1 library. Inspired by an existing TypeScript server, it offers similar F1 data functionalities natively in Python via FastF1.

Standalone Model Context Protocol server for PropProfessor, plus a small query CLI for local analysis.

Enables AI agents to query live sports betting data including odds, edges, arbitrage opportunities, player/team stats, and reference data using the SportWizzard API.

Enables conversational AI to fetch live World Cup matches, standings, results, and generate journalist-style match summaries using MCP tools and prompts.

Enables AI agents to query live and historical sports analytics, consensus betting odds, predictions, scores, schedules, standings, rosters, news, play-by-play, and win probabilities through structured tools and resources.

MCP server that provides structured access to real-time sportsbook data from iddaa, including live events, competitions, and league fixtures with strategy analysis. Designed for AI agents and automation workflows.

Provides structured Valorant esports analytics data and metrics through MCP, including match analysis, player profiling, scouting reports, and ad-hoc SQL queries. Enables AI models to generate accurate coaching insights from pre-computed analytics tables.

Enables fast real-time web search and access to premium data from trusted sources including news, financial markets, sports, and more. Supports AI agents with live data and curated content from various domains.

An MCP server that analyzes upcoming weather at alpine peaks and trailheads worldwide, ranking the best windows for climbing and ascent using high-resolution forecast models.

Enables AI agents to discover, browse, and trade structured sports tokens on the SPRTX network via JSON-RPC 2.0 over Streamable HTTP.

An MCP server that provides access to over 12 years of NFL play-by-play data through a local DuckDB database. It enables users to query player performance, team statistics, and situational efficiency metrics like EPA and WPA using natural language.

MCP server for AI agent access to JKTJJ's structured BJJ data — gyms, coaches, events, and cities worldwide.

Enables Claude to analyze a player's public FACEIT CS2 data, diagnose strengths and weaknesses, and generate personalized improvement plans.

An HTTP broker that exposes Strava data and operations (activities, routes, segments, etc.) as MCP tools, allowing users to interact with their own Strava account via natural language using per-user OAuth2 authentication.

An MCP server that answers football questions with interactive widgets, centered on the 2026 FIFA World Cup using SofaScore API data.

An MCP Server that provides access to League of Legends statistics via the SportData.io API, allowing agents to query and analyze LoL competitive gaming data.

An MCP server for accessing college basketball statistics through the SportsData.io CBB v3 Stats API, enabling AI agents to retrieve and analyze college basketball data through natural language interactions.

This Model Context Protocol server provides access to the Sleeper Fantasy Football API, enabling agents to fetch data about users, leagues, drafts, rosters, matchups, and player information without requiring an API key.

An MCP server providing domain tools for validating, risk-assessing, and replanning multi-day hiking itineraries in the Chornohora range using curated trail data.