Context7

Knowledge Graph Memory

Official

Build and query persistent semantic networks for data management. A basic implementation of persistent memory using a local knowledge graph. This lets Claude remember information about the user across chats.

Provides a knowledge graph-enhanced retrieval system that combines vector search with graph-based relationships for persistent memory and contextual information retrieval

Provides a structured thought process management system for maintaining explicit reasoning steps, policy verification, and tool output analysis through persistent memory storage

Maintains persistent project context through a structured Memory Bank system of five markdown files that track goals, status, progress, decisions, and patterns with automatic timestamp tracking and workflow guidance for consistent documentation across development sessions.

Structures reasoning processes through defined thought stages, managing a history of thoughts with metadata for transparent, step-by-step problem solving and decision making.

Basic Memory

Official

Knowledge management system that builds a persistent semantic graph in markdown, locally.

TypeScript-based server for tracking project context across sessions, enabling persistent knowledge sharing through modular, markdown-based memory management with support for multiple development modes.

Database-backed project memory management system that stores decisions, progress tracking, and system patterns in a queryable knowledge graph with vector embeddings for semantic search and comprehensive import/export functionality.

Provides structured problem-solving tools through Sequential Story and Sequential Thinking approaches, enabling narrative-based or Python-implemented thought sequences with branching and visual formatting capabilities for enhanced memory retention.

Provides persistent intelligence infrastructure for codebase analysis through hybrid Rust-TypeScript architecture that combines Tree-sitter AST parsing with semantic concept extraction, developer pattern recognition, and SQLite-based persistence to build contextual understanding of codebases over time, learning from developer behavior and architectural decisions.