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.
Consolidates multi-agent memory using a knowledge graph with typed edges (causes, fixes, contradicts) and autonomous compression, accessible via REST API with ONNX-based embeddings that run locally. Implements Remote MCP support for browser-based claude.ai integration via Server-Sent Events, alongside traditional desktop MCP, with OAuth 2.0 authentication and self-hosted infrastructure (no cloud lock-in). Agent identity is tracked via `X-Agent-ID` headers for scoped retrieval, and conversation threading is preserved through `conversation_id` fields, enabling both shared memory across agent fleets and inter-agent messaging through semantic tag-based filtering.
About mcp-memory-keeper
mkreyman/mcp-memory-keeper
MCP server for persistent context management in AI coding assistants
Provides a SQLite-backed persistent memory layer using the Model Context Protocol (MCP), enabling Claude to save and restore context across sessions through channels (auto-derived from git branches), checkpoints, and typed relationships between stored items. Integrates with Claude Code via stdio transport and includes batch operations, smart compaction, full-text search, and real-time change tracking to preserve architectural decisions and progress without manual intervention.
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