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

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.

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.

Enables searching, comparing, and inspecting AI models by pricing, context window, and capabilities via the models.dev catalog.

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.

Classifies development task complexity (LIGHT/MEDIUM/HEAVY) and recommends the most cost-efficient AI model per provider, enabling optimized model selection for coding tasks.

A powerful Model Context Protocol server that creates intelligent graph representations of your codebase with comprehensive semantic analysis capabilities, supporting 11 languages and 26 MCP methods.

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

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

MCP server that lists available GitHub Models and compares responses from multiple models for the same prompt.

An MCP server that wraps the @apitomy/data-models library for querying, validating, and editing OpenAPI and AsyncAPI documents.

Unified MCP server with 46 tools for AI expert consultations, memory service integration (semantic search, knowledge graphs), workflow automation, and code sandboxing.

A persistent memory system using a local knowledge graph that enables Claude to remember information about users across chats, with advanced search, graph traversal, and filtering capabilities for entities, relations, and observations.

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

Enables AI agents to store, query, and trace a time-aware memory graph of nodes and edges in a single SQLite file, supporting weighted recall, temporal queries, and provenance-aware writes over MCP.

MCP server that indexes Obsidian notes and enables hybrid search (full-text, fuzzy, semantic) for AI assistants to find and read notes.

An MCP server that helps interact with and compare different GitHub Models, enabling listing, filtering, and comparing model responses.

Maps Salesforce metadata into a Neo4j graph database, enabling AI agents to reason about schema and generate accurate SOQL queries.

Enables AI assistants to persist and retrieve user information across chats via a local knowledge graph with entities, relations, and observations, using a SQLite-backed MCP interface.

Enables unified access to SQL, semantic vector search, and columnar analytics through a single MCP interface.