Memory Management Servers

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 Say goodbye to outdated or incorrect API info—Context7 ensures your language model answers come with the latest coding references.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.

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 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.

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 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.

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.

Lara Translate

Official

Bridges to the Lara Translation API for accurate, context-aware text translations between languages with automatic language detection capabilities.

Lightweight, local RAG memory store for MCP agents. Easily record, retrieve, update, delete, and visualize persistent "memories" across sessions.

Integrates note-taking capabilities with AI models using TypeScript and DynamoDB for persistent memory and context management in applications.

Maintains structured markdown documents as living memory for focused projects, enabling systematic organization, search, and updates of accumulated context across multiple conversations.

Production-ready semantic memory management server that stores, retrieves, and manages contextual knowledge across sessions using PostgreSQL with pgvector for vector similarity search, featuring intelligent caching, multi-user support, memory relationships, automatic clustering, and background job processing for persistent AI memory and knowledge management systems.

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.

Provides a LibSQL-based persistent memory database for storing and retrieving knowledge graph entities and relations across conversations.

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.