MARM-Systems and MegaMemory
Both projects appear to be competing implementations of a "Memory Control Plane" (MCP) server designed to provide persistent knowledge graphs and context sharing for AI agents.
About MARM-Systems
Lyellr88/MARM-Systems
Turn AI into a persistent, memory-powered collaborator. Universal MCP Server (supports HTTP, STDIO, and WebSocket) enabling cross-platform AI memory, multi-agent coordination, and context sharing. Built with MARM protocol for structured reasoning that evolves with your work.
# Technical Summary Implements semantic vector-based memory indexing with auto-classification of conversation content (code, decisions, configs) and enables cross-session recall via FastAPI-backed HTTP/STDIO transports that integrate natively with Claude, Gemini, and other MCP-compatible agents. The architecture uses SQLite with WAL mode for persistent storage and connection pooling, exposing 18 MCP tools for granular memory control—including structured session logs, reusable notebooks, and smart context fallbacks when vector similarity alone is insufficient. Designed for production workflows requiring reliable long-term context across multiple AI agents and deployment cycles, with Docker containerization and rate-limiting built-in.
About MegaMemory
0xK3vin/MegaMemory
Persistent project knowledge graph for coding agents. MCP server with semantic search, in-process embeddings, and web explorer.
Uses in-process ONNX embeddings (all-MiniLM-L6-v2) and SQLite with WAL for zero-dependency semantic search and persistence. Operates as an MCP stdio server integrated with Claude Code, OpenCode, Antigravity, and Codex, with built-in two-way merge conflict resolution for collaborative knowledge graph management across branches. The LLM itself acts as the indexer—concepts are stored in natural language rather than parsed code symbols—enabling agents to update the graph after each task and query semantic context before starting new ones.
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