"Hybrid Memory Models Combining Relational, Graph, and RAG Approaches" matching MCP servers:

Enables AI agents to use a hybrid dense+sparse RAG system with tag-based long-term memory (importance, knowledge-type decay, access-frequency boost) via MCP tools for document ingestion, hybrid search, staged reranking, forgetting, and index management.

Universal FastMCP bridge into a hybrid memory stack, enabling MCP-capable agents to save, search, read, and recall memories using OpenViking and Honcho backends.

Self-hosted personal knowledge graph for Claude that persists across sessions, devices, and tools. Built on Neo4j with local semantic embeddings; OAuth 2.1 lets Claude Code, Claude Desktop, and claude.ai web all hit the same graph.

Provides AI coding agents with a local knowledge-graph memory, enabling cross-project retrieval via PageRank diffusion and tools to retrieve, write, extract, update, and view recent knowledge over MCP.

Local-first memory for Claude Code and any MCP client: hybrid vector + keyword search and a bi-temporal knowledge graph in one SQLite file. Local embeddings, no API key, $0/token.

A local-first Graph-RAG system that combines ChromaDB with metadata-based graph relationships and Gemini 2.5 Flash for intelligent Q\&A over your Obsidian vault.

Enables persistent, intelligent memory across sessions using a weighted, interconnected graph that evolves through conversation.

RAG Knowledge Graph - MCP server providing AI-powered tools and automation by MEOK AI Labs

An advanced MCP server providing RAG-enabled memory through a knowledge graph with vector search capabilities, enabling intelligent information storage, semantic retrieval, and document processing.

A personal memory MCP server for Obsidian/markdown vaults that provides hybrid retrieval (semantic, keyword, tag, time-aware co-occurrence) and is shared across multiple AI clients.

Enables AI agents to build and query a persistent knowledge graph with entities, relationships, and observations. Features a core index system that ensures critical information is always accessible across all memory operations.

A local MCP server enabling hybrid search over documents, memory, and knowledge graphs for retrieval-augmented generation, with tools for SQLite, semantic memory, and entity-relationship queries.

An MCP server that gives your agent a persistent project brain: vision, architecture decisions, conventions, roadmaps, and automatic session handoff.

A context-aware memory MCP server with authority weighting, conflict detection, and typed relationship edges for intelligent memory retrieval.

A graph-based MCP server that provides AI coding agents with persistent memory to store patterns, track complex relationships, and retrieve knowledge across sessions. It leverages graph structures to handle temporal queries and relational paths that traditional vector stores often miss.

A persistent memory server that implements a local knowledge graph using the Kuzu embedded database to store entities, relationships, and observations. It enables AI models to maintain structured long-term context through searchable nodes and comprehensive tag-based organization.

Graph-relational memory MCP server for persistent LLM memory, featuring wikilinks, BM25 auto-linking, spreading activation, and synaptic decay across five memory layers.

Provides a dynamic SQLite-backed code knowledge graph for AI assistants, with MCP tools to inspect symbols, find dependency paths, and analyze code structure across multiple languages.

Enables natural language querying of a football knowledge graph via Neo4j, generating Cypher queries and answers using LLMs, and also provides tools to build the graph from text.

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