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 Say goodbye to outdated or incorrect API info—Context7 ensures your language model answers come with the latest coding references.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

T

Think Tool

Remote

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

Basic Memory

Official

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

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.

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 intelligent memory management and task tracking for software development projects with automatic project detection, semantic search, and SQLite-based persistence that maintains context across coding sessions through memory classification, relationship building, and context-aware task creation.

S

Structured Thinking

Remote

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

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.

A local, persistent memory system for AI coding assistants that stores decisions, patterns, and session context via MCP tools. It enables cross-session memory management using SQLite and optional vector search without external dependencies or cloud storage.

A persistent AI memory server that enables storage and retrieval of context and project artifacts across conversations. It features full-text search, version history, and automatic content chunking using local SQLite or hosted cloud storage.

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.

Doclea MCP

Official

Provides persistent memory for AI coding assistants, storing and retrieving architectural decisions, patterns, and solutions across sessions using semantic search, while also offering git integration for commit messages and code expertise mapping.

Enables persistent memory for AI systems by providing tools for episodic, semantic, and procedural data storage through a vector-and-graph-enhanced database. It allows models to maintain long-term continuity using similarity search, thematic clustering, and identity tracking.

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

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.

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.