OMEGA — Persistent Memory for AI Coding Agents
Description
OMEGA is a local-first persistent memory system for AI coding agents, implemented as an MCP (Model Context Protocol) server. It provides 25 tools for storing, querying, and managing memories across sessions.
Key Features
- Semantic search (bge-small-en-v1.5 embeddings + FTS5 + contextual re-ranking)
- Auto-capture of decisions, lessons, and error patterns
- Graph relationships between memories (related, supersedes, contradicts)
- Checkpoint/resume for multi-session task continuity
- Intelligent forgetting with time-decay and conflict resolution
- Zero cloud dependencies (SQLite + CPU-only ONNX)
Relevance
OMEGA addresses the core challenge of long-term memory for AI agents — enabling cross-session learning, preference tracking, and knowledge accumulation. It scores #1 on LongMemEval (ICLR 2025), an academic benchmark testing temporal reasoning, relationship tracking, and factual recall across 500 multi-session tasks.
OMEGA — Persistent Memory for AI Coding Agents
Description
OMEGA is a local-first persistent memory system for AI coding agents, implemented as an MCP (Model Context Protocol) server. It provides 25 tools for storing, querying, and managing memories across sessions.
Key Features
Relevance
OMEGA addresses the core challenge of long-term memory for AI agents — enabling cross-session learning, preference tracking, and knowledge accumulation. It scores #1 on LongMemEval (ICLR 2025), an academic benchmark testing temporal reasoning, relationship tracking, and factual recall across 500 multi-session tasks.