Memory Plus

Context7

Official Remote

Discover Context7 MCP, a powerful tool that injects fresh, version-specific code docs and examples from official sources directly into your AI prompts. Say goodbye to outdated or incorrect API info—Context7 ensures your language model answers come with the latest coding references. By simply adding "use context7" to your prompt, you get precise, reliable library documentation and working code snippets without leaving your editor. Designed for smooth integration with many MCP-compatible clients and IDEs, it enhances AI coding assistants with accurate, real-time context that boosts developer productivity and confidence.

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.

Provides a persistent, searchable, automatically updated 'second brain' for development by integrating ChromaDB with automated codebase indexing, chat logging, and sequential thinking tools that maintain context across sessions.

Basic Memory

Official

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

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

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.

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.

Provides persistent memory storage for assistants to create and retrieve memories with filtering options by app name, category, and result limits through a SQLite database with automatic setup.

Memory-powered agent framework that provides persistent memory capabilities across conversations and sessions using vector databases and embeddings, enabling context retention, reasoning pattern recognition, and shared workspace memory for team collaboration.

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

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.

Provides persistent memory capabilities through a SQLite-based knowledge graph that stores entities, observations, and relationships with full-text and semantic search using BGE-M3 embeddings for intelligent context retrieval across conversations.