Memoer (Persistent Memory Storage)

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 Say goodbye to outdated or incorrect API info—Context7 ensures your language model answers come with the latest coding references.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

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.

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.

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.

Integrates Ollama's local LLM models with MCP-compatible applications, enabling on-premise AI processing and custom model deployment while maintaining data control.

Integrates with Penpot's API to enable project browsing, file retrieval, object searching, and visual component export with automatic screenshot generation for converting UI designs into functional code.

Experience seamless AI-powered 3D modeling by connecting Blender with Claude AI via the Model Context Protocol. BlenderMCP enables two-way communication, allowing you to create, modify, and inspect 3D scenes directly through AI prompts. Control objects, materials, lighting, and execute Python code in Blender effortlessly. Access assets from Poly Haven and generate AI-driven models using Hyper3D Rodin. This integration enhances creative workflows by combining Blender’s robust tools with Claude’s intelligent guidance, making 3D content creation faster, interactive, and more intuitive. Perfect for artists and developers seeking AI-assisted 3D design within Blender’s environment.

Integrates with Ollama for local large language model inference, enabling text generation and model management without relying on cloud APIs.

MoviePy-based video editing server that provides comprehensive video and audio processing capabilities including trimming, merging, resizing, effects, format conversion, YouTube downloading, and text/image overlays through an in-memory object store for chaining operations efficiently.

Bridges local llama-server instances with MCP clients, providing chat interface, health monitoring, and configurable generation parameters for integrating llama.cpp models with desktop applications

Integrates with n8n workflow automation platform to enable natural language workflow creation, management, and deployment with encrypted credential handling, role-based access control, and automated testing capabilities.

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

Extracts text from videos and audio files across platforms like YouTube, Bilibili, TikTok, Instagram, Twitter/X, Facebook, and Vimeo using Whisper speech recognition for transcription, content analysis, and accessibility improvements.

Integrates with LlamaIndexTS to provide access to various LLM providers for code generation, documentation writing, and question answering tasks

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.

Human-like temporal memory for AI assistants that naturally fades over time unless reinforced through use, mimicking the Ebbinghaus forgetting curve

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.

Human-like temporal memory for AI assistants that naturally fades over time unless reinforced through use, mimicking the Ebbinghaus forgetting curve

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

Leverage Rememberizer's document API for AI-powered semantic search and retrieval of enterprise knowledge.

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.

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