This project is an MCP server for managing memory text files, helping AI models like Claude maintain context between conversations. It provides functions to add, search, delete, and list memories, supporting exact matching operations based on substrings. It is designed to store memories in simple text files, similar to ChatGPT's memory mechanism, and triggers memory storage through prompts and training.

This is a server that connects the TrainingPeaks training data platform to AI assistants like Claude through the Model Context Protocol (MCP). It allows users to query training data, analyze training loads, compare power data, and track fitness trends through natural language, without waiting for official API approval and using secure cookie authentication.

NotHumanAllowed is a multi - agent cognitive dataset generation engine that conducts multiple rounds of deliberation through 38 professional AI agents, generating auditable reasoning trajectories and structured knowledge records for training next - generation AI systems.

This project provides an interface for AI assistants to access Haskell documentation. By retrieving authoritative documentation on Hackage in real - time, it solves the problem of insufficient training data for AI in the Haskell field and improves the accuracy of code generation and explanation.

AWorld is a multi - agent system framework aiming to bridge the gap between theoretical MAS capabilities and practical applications, providing a full - set solution from single - agent to multi - agent collaboration/competition. The project supports scenarios such as browser/mobile operations and GAIA benchmark testing, adopts a client - server architecture, integrates a rich toolchain, and includes performance evaluation and training functions.