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Why this server?
A high-performance, persistent memory system for the Model Context Protocol (MCP) providing vector search capabilities and efficient knowledge storage using libSQL as the backing store.
Why this server?
This project is based on the Knowledge Graph Memory Server from the MCP servers repository and retains its core functionality.
Why this server?
A custom Memory MCP Server that acts as a cache for Infrastructure-as-Code information, allowing users to store, summarize, and manage notes with a custom URI scheme and simple resource handling.
Why this server?
A basic implementation of persistent memory using a local knowledge graph. This lets Claude remember information about the user across chats.
Why this server?
Provides a semantic memory layer that integrates LLMs with OpenSearch, enabling storage and retrieval of memories within the OpenSearch engine.
Why this server?
A Model Context Protocol server that reduces token consumption by efficiently caching data between language model interactions, automatically storing and retrieving information to minimize redundant token usage.
Why this server?
A basic implementation of persistent memory using a local knowledge graph. This lets Claude remember information about the user across chats.
Why this server?
A tool for Model Context Protocol (MCP) that allows you to analyze web content and add it to your knowledge base, storing content as Markdown files for easy viewing with tools like Obsidian.
Why this server?
Image Tools MCP is a Model Context Protocol (MCP) service that retrieves image dimensions and compresses images from URLs and local files using the TinyPNG API. It supports converting images to formats like webp, jpeg/jpg, and png, providing detailed information on width, height, type, and compressi
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.