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by sandst1 • Uncategorized
An MCP server providing a generalization-capable memory layer for LLMs to store and recall abstracted knowledge.
A project-local or centralized memory system to store and recall generalized knowledge from experiences.
Consolidate episodic data into abstract concepts with confidence and conditions for better reasoning.
Integrated task management, entity relationship tracking, and outcome-based learning within their memory.
Remind is a memory layer designed for large language models that consolidates specific experiences into generalized concepts, mimicking human memory. It supports auto-ingestion of conversation text, entity graph linking, outcome tracking, and task management, accessible via CLI or a centralized MCP server with a web UI and REST API. This enables agents to maintain project-local or centralized memory with advanced retrieval and consolidation features.