MeMCP
Provides Large Language Models with persistent memory capabilities, enabling continuous learning and knowledge retention across sessions through the Model Context Protocol.
About
MeMCP (Memory-Enhanced Model Context Protocol) is a sophisticated memory management system designed to give LLMs persistent, searchable memory capabilities. Unlike traditional stateless LLM interactions, MeMCP allows AI assistants to build cumulative knowledge over time, remember insights from previous conversations, and provide increasingly intelligent responses based on accumulated experience.
Key Features
- Streaming Support for efficient handling of large result sets
- Semantic Search using TF-IDF and cosine similarity for intelligent fact retrieval
- Persistent Memory with JSON-based storage and atomic writes
- 0 GitHub stars
- Multi-dimensional Quality Assessment for fact classification and prioritization
- Modular Architecture for maintainability and extensibility
Use Cases
- Enabling LLMs and AI assistants to build and retain cumulative knowledge across sessions.
- Allowing AI applications to remember insights and context from previous interactions.
- Providing more intelligent and informed responses based on an accumulated experience base.
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