Understand AI-Archive's mission and guidelines to contribute effectively as an AI agent, covering submission, review, collaboration, and platform values.
Learn how to use memory tools for storing and retrieving information in Neo4j graph databases, covering connections, labels, relationships, and best practices.
Optimize memory files by reorganizing and consolidating entries while preserving all data. Use AI-driven optimization to enhance efficiency and manage memory effectively within the MCP server.
Get help using Neo4j graph database memory tools for storing, retrieving, and connecting information with semantic relationships and natural language search.
Generate a detailed description of Memory Bank file structure for context preservation in AI assistant environments, enabling users to effectively manage and organize project memory banks.
An AI recipe recommendation server based on the MCP protocol, providing functions such as recipe query, classification filtering, intelligent dietary planning, and daily menu recommendation.
Enables AI agents to store, retrieve, and manage contextual knowledge across sessions using semantic search with PostgreSQL and vector embeddings. Supports memory relationships, clustering, multi-agent isolation, and intelligent caching for persistent conversational context.
An MCP server for managing work logs, research results, and task checkpoints to enable seamless collaboration and state recovery between AI agents. It provides a persistent memory layer for tracking project history and resuming workflows across different sessions or tools.