"Techniques for enabling agents to retain and utilize information across multiple sessions" matching MCP servers:

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

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.

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.

MCP server that connects AI assistants to the Statos football analytics platform, enabling natural language queries for match predictions, betting picks, league information, and admin market-suppression controls.

Enables AI agents to read and analyze your Boardsesh climbing logbook across boards like Kilter, Tension, and MoonBoard, with read-only access and optional credentials for personalized recommendations.

Searchable football data provider documentation for AI coding agents. Enables agents to look up verified docs on event types, qualifier IDs, coordinate systems, and more across 15 providers.

Enables AI agents to read and analyze your Kilter Board logbook, including sessions, sends, projects, and grade progress, entirely read-only.

Enables AI agents to search and retrieve detailed information about US golf courses, including course details, tees, climate, and nearby points of interest.

MCP server for motorsport event documents, enabling AI agents to search, read, compare amendments, and parse schedules via typed tools.

Provides professional cycling data from FirstCycling, allowing users to retrieve comprehensive information about cyclists, race results, historical cycling data, and team information through natural language queries.

Provides access to French Roller Derby rules documentation, enabling search across sections, retrieval of specific rule sections (game parameters, scoring, penalties, officiating), and browsing the complete rulebook.

An MCP Server implementation that integrates the Balldontlie API, to provide information about players, teams and games for the NBA, NFL and MLB.

A Model Context Protocol server that provides comprehensive Formula One racing data, enabling access to event schedules, driver information, telemetry data, race results, and performance analytics through natural language queries.

Provides AI assistants with commissioner-focused tools for fantasy sports leagues, enabling league overviews, standings, transactions, recaps, and manager activity across providers like Yahoo Fantasy.

MCP-compatible server that gives AI agents access to alternative sports data across 30+ leagues — odds, events, probabilities, settlement, and futures for prediction markets, DFS platforms, and sportsbooks.

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.

Provides access to Chess.com player data, game records, and public information through standardized MCP interfaces, allowing AI assistants to search and analyze chess information.

An MCP server that exposes sports-data APIs from multiple providers (AFL, Sportsbet, Entain, NRL) as interchangeable tools, enabling cross-provider odds and stats comparison.

Connect AI agents to OP.GG Esports data and retrieve upcoming League of Legends match schedules effortlessly. Access structured match information through a standardized interface, enhancing your AI's capabilities with real-time esports data.

Provides access to FantasyPros API for retrieving sports data including news, player information, consensus rankings, and projections across NFL, MLB, NBA, and NHL.