memora and MegaMemory
These tools appear to be **competitors**, as both are MCP servers designed for providing persistent semantic storage, knowledge graphs, and cross-session context to AI agents.
About memora
agentic-box/memora
Give your AI agents persistent memory — MCP server for semantic storage, knowledge graphs, and cross-session context
Implements a Model Context Protocol (MCP) server with pluggable embedding backends (OpenAI, sentence-transformers, TF-IDF) and multi-tiered storage—local SQLite, Cloudflare D1, or S3/R2 with optional encryption and compression. Features include interactive knowledge graph visualization, RAG-powered chat with streaming LLM tool calling, event notifications for inter-agent communication, and automated memory deduplication via LLM comparison. Integrates with Claude Code and Codex CLI through stdio or HTTP transports.
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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