A Model Context Protocol server that enables AI agents to query a Graphiti knowledge graph and pgvector document store for evidence-backed responses via hybrid search and RAG.
A sophisticated AI-powered server providing intelligent, context-aware conversational capabilities with role-based advisors, semantic memory, multi-LLM support, and web browsing.
A Model Context Protocol server that integrates AI assistants with Mem0.ai's persistent memory system, allowing models to store, retrieve, search, and manage different types of memories.
A Python-based server providing persistent memory management for AI models with SQLite and Markdown dual backend storage. It features full-text search, RAG-enhanced querying, and cross-project knowledge sharing for integration with Claude, Cursor, and Rovo Dev.
A FastAPI server that implements the Model Context Protocol (MCP) using Server-Sent Events (SSE) transport to provide random cat facts on demand or as a continuous stream.
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.
Enables storing and querying structured information about software code entities (classes, functions, files) and their relationships (calls, imports) along with qualitative observations like design decisions and change rationale.
An implementation of persistent memory for Claude using a local knowledge graph, allowing the AI to remember information about users across conversations with customizable storage location.
Enables Claude to maintain persistent memory across conversations using a local knowledge graph with fuzzy search capabilities, allowing it to remember and recall information about users, relationships, and context.
A Model Context Protocol server that provides knowledge graph-based persistent memory for LLMs, allowing them to store, retrieve, and reason about information across multiple conversations and sessions.
Provides personalized Data Engineering learning updates by fetching recent news about DE concepts, patterns, and technologies, while tracking user knowledge to present only new information relevant to their learning journey.
Provides knowledge graph functionality for managing entities, relations, and observations in memory with strict validation rules to maintain data consistency.
Enables querying context about the MAM product components and architecture through MCP, allowing agents to retrieve targeted product information on demand instead of loading full documentation.
Enables Claude to remember information about users across chats using a persistent local knowledge graph that stores entities, relationships, and observations.