mcp-memory-service and mcp-memory-keeper
These are competitors offering alternative approaches to persistent memory for AI agents—one targeting multi-framework pipelines with knowledge graphs and REST APIs, the other specialized for coding assistants with context management—where you would select based on your agent architecture and use case rather than use together.
About mcp-memory-service
doobidoo/mcp-memory-service
Open-source persistent memory for AI agent pipelines (LangGraph, CrewAI, AutoGen) and Claude. REST API + knowledge graph + autonomous consolidation.
This service provides a shared, persistent memory for AI agents, allowing them to retain information and learn across different tasks and sessions. It takes in decisions and facts from various agents, organizing them into a knowledge graph. The output is fast, relevant context that helps agents make better decisions, suitable for anyone building or managing multi-agent AI systems, like AI solution architects or AI product managers.
About mcp-memory-keeper
mkreyman/mcp-memory-keeper
MCP server for persistent context management in AI coding assistants
This tool helps developers using Claude AI coding assistants avoid losing important context during long coding sessions. It takes your ongoing conversation, code snippets, decisions, and progress as input and persistently stores them. This means Claude can remember everything even when its internal memory fills up or you start a new session, giving you a continuous development experience.
Related comparisons
Scores updated daily from GitHub, PyPI, and npm data. How scores work