PLTM

Provides persistent semantic memory capabilities through PostgreSQL with pgvector embeddings, enabling project-based memory namespacing, semantic search, and relationship management for building connected knowledge graphs across conversations.

Stores entities and relationships in a Neo4j graph database with semantic search and temporal filtering, enabling persistent contextual memory for conversational systems through 10 specialized tools for creating memories, building connections, and querying knowledge graphs with configurable depth tr

Provides persistent memory storage with temporal versioning, semantic search, and automatic decay using SQLite for reliability and Qdrant for vector similarity search to maintain context across conversations and learn from past interactions.