Provides a semantic memory layer that integrates LLMs with OpenSearch, enabling storage and retrieval of memories within the OpenSearch engine.

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.

Provides a project memory bank and RAG context provider for enhanced code understanding and management through vector embeddings, integrated with RooCode and Cline.

Enhances user interaction through a persistent memory system that remembers information across chats and learns from past errors by utilizing a local knowledge graph and lesson management.

This advanced memory server facilitates neural memory-based sequence learning and prediction, enhancing code generation and understanding through state maintenance and manifold optimization as inspired by Google Research's framework.

A Model Context Protocol (MCP) server that optimizes token usage by caching data during language model interactions, compatible with any language model and MCP client.

A very simple vector store that provides capability to watch a list of directories, and automatically index all the markdown, html and text files in the directory to a vector store to enhance context.

This MCP server provides persistent memory integration for chat applications by utilizing a local knowledge graph to remember user information across interactions.

The MCP server transforms chats with Claude into journaling sessions, saving conversations locally and allowing the LLM to retrieve previous sessions to create continuity in discussions about daily activities.

Facilitates integration of PrivateGPT with MCP-compatible applications, enabling chat functionalities and secure management of knowledge sources and user access.

Facilitates knowledge graph representation with semantic search using Qdrant, supporting OpenAI embeddings for semantic similarity and robust HTTPS integration with file-based graph persistence.

Enhances Claude AI with persistent memory storage for Infrastructure-as-Code components, supporting version tracking and relationship mapping for Terraform and Ansible resources.

This MCP server aids users in searching and analyzing their photo library by location, labels, and people, offering functionalities like photo analysis and fuzzy matching for enhanced photo management.

A neural memory system that learns and predicts sequences, maintaining state via memory vectors for enhanced code generation and understanding.

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

Enables vector similarity search and serving of Svelte documentation via the MCP protocol, with support for local caching and multiple llms.txt documentation formats.

A server that facilitates branch-based navigation of thoughts, enabling users to manage multiple thought branches, generate insights, and track branch priorities through a structured thinking process.

An MCP server for navigating thought processes using branches, supporting thought cross-references and priority tracking to enhance insight generation and structured idea exploration.

A high-performance MCP server utilizing libSQL for persistent memory and vector search capabilities, enabling efficient entity management and semantic knowledge storage.

Provides memory/knowledge graph storage capabilities using Supabase, enabling multiple Claude instances to safely share and maintain a knowledge graph with features like entity storage, concurrent access safety, and full text search.

Provides AI-powered assistance for coding problems using Google's Gemini AI, combined with Perplexity insights and Stack Overflow references, facilitating contextual analysis and automatic response archiving for improved troubleshooting.

A Model Context Protocol server utilizing Claude AI for generating intelligent queries and offering documentation assistance based on API documentation analysis.

A comprehensive suite of Model Context Protocol servers designed to extend AI agent Claude's capabilities with integrations for knowledge management, reasoning, advanced search, news access, and workspace tools.

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.

Facilitates semantic analysis of chat conversations through vector embeddings and knowledge graphs, offering tools for semantic search, concept extraction, and conversation pattern analysis.

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

A Python-based server that implements the Model Context Protocol to interface with Claude Desktop as an MCP client, supporting interaction through efficient memory management.

Provides semantic memory and persistent storage for Claude, leveraging ChromaDB and sentence transformers for enhanced search and retrieval capabilities.

Serves as a guardian of development knowledge, providing AI assistants with curated access to latest documentation and best practices.

Transform your non-existent or unreadable docs into an intelligent, searchable knowledge base that actually answers those 'basic questions' before they're asked.

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

An MCP server implementation that provides tools for retrieving and processing documentation through vector search, enabling AI assistants to augment their responses with relevant documentation context

Provides intelligent summarization capabilities through a clean, extensible architecture. Mainly built for solving AI agents issues on big repositories, where large files can eat up the context window.

This project is based on the Knowledge Graph Memory Server from the MCP servers repository and retains its core functionality.

A basic implementation of persistent memory using a local knowledge graph. This lets Claude remember information about the user across chats.

This lets you use Claude Desktop, or any MCP Client, to use natural language to accomplish things with Neo4j and your Aura account.

An improved implementation of persistent memory using a local knowledge graph with a customizable --memory-path. This lets Claude remember information about the user across chats.