Why this server?

Provides structured memory management across chat sessions for Claude, allowing it to maintain context and build a knowledge base.

Why this server?

A TypeScript-based MCP server that provides a memory system for Large Language Models (LLMs), allowing users to interact with multiple LLM providers while maintaining conversation history.

Why this server?

Provides a centralized MCP-based system for managing and accessing multi-project memory banks remotely, with features like project isolation and file structure validation.

Why this server?

A Claude-compatible MCP server that enables storing and summarizing notes through a simple note storage system with custom URI scheme.

Why this server?

Enables LLMs to search, retrieve, and manage documents through Rememberizer's knowledge management API.

Why this server?

A server for managing project documentation and context across Claude AI sessions through global and branch-specific memory banks, enabling consistent knowledge management with structured JSON document storage.

Why this server?

Processes emails from Outlook with date filtering, storing them in SQLite databases while generating vector embeddings for semantic search capabilities in MongoDB.

Why this server?

Memory manager for AI apps and Agents using various graph and vector stores and allowing ingestion from 30+ data sources

Why this server?

Provides a centralized MCP-based system for managing and accessing multi-project memory banks remotely, with features like project isolation, file structure validation, and type-safe operations.

Why this server?

Enables neural memory sequence learning with a memory-augmented model for improved code understanding and generation, featuring state management, novelty detection, and model persistence.