"Neo4j memory configuration and management" matching MCP servers:

Provides AI assistants with persistent, graph-based memory using Neo4j, enabling semantic search and complex relationship tracking. It features specialized Cloudflare Access support for secure remote connections and isolated multi-database management for different projects.

An MCP server that enables LLMs to perform semantic and fulltext searches within Neo4j while executing complex, search-augmented Cypher queries for GraphRAG applications. It provides tools for database schema discovery and supports multi-provider embeddings to facilitate advanced graph traversals.

Enables LLMs to interact with Neo4j graph databases using natural language to execute Cypher queries and introspect database schemas. It supports both read and write operations for local, Docker, and cloud-based instances like Neo4j Aura.

This server enables interaction between Neo4j databases and Claude Desktop, allowing users to execute Cypher queries, create nodes, and establish relationships in the database.

Enables AI assistants to interact with Neo4j graph databases through natural language, supporting Cypher queries, schema management, data manipulation, and graph algorithms.

Automatically discovers vector indexes in a Neo4j database and exposes each as a semantic search tool with metadata pre-filtering, enabling natural language queries with dynamic filter support.

Enables natural language queries to a Neo4j knowledge graph built from PostgreSQL data, integrating with Claude Desktop and REST API.

Enables AI agents to store, retrieve, and connect information in a Neo4j graph database as persistent memory, with semantic relationships, natural language search, and temporal tracking across conversations.

Enables AI assistants to use Neo4j knowledge graphs and Qdrant vector databases for hybrid reasoning, combining structured facts with semantic search for advanced knowledge management, research analysis, and standardized coding workflows.

Provides Claude Co-work with MCP tools to search and record organizational memory, including search, read, query, ingest, remember, sync, and status operations.

MCP server providing durable Substrate organizational memory tools, including search, read, query, ingest, remember, and sync. It integrates with Codex to automatically capture completed turns and session boundaries for persistent memory.

Enables LLM agents to explore and search a 1C:Enterprise configuration codebase, including metadata objects, module procedures, call graphs, and semantic similarity search.

A local MCP server that gives AI assistants persistent long-term memory using a biological neural architecture with cortex, synapses, and hippocampus.

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.

Embedded, local-first agent memory: facts extracted into a per-namespace SQLite file (vec0 + FTS5) with hybrid retrieval and point-in-time (time-travel) queries. ADD-only history over stdio — no server process, no cloud dependency.

MCP server providing persistent memory for AI applications, enabling Claude to store and recall memories with hybrid search and knowledge graph.

Exposes tools that let an agent search a local Markdown-based memory store, fetch full cards by id, write new knowledge cards that are indexed immediately, and inspect or rebuild the SQLite index. All retrieval runs locally over Chinese-friendly full-text search with graded exact/prefix matching, so agents without a memory system can recall prior notes while existing Markdown files stay read-only.

Provides persistent memory for AI agents using hybrid search (vector embeddings + BM25) with neural reranking, enabling storage and retrieval of insights, debugging solutions, and patterns across coding sessions.

Provides persistent local memory for any MCP-compatible AI agent, enabling agents to store, search, recall, forget, export, and manage preferences, rules, and facts with zero dependencies, no cloud, and no API keys.

Provides AI agents with persistent, searchable memory using semantic search, auto-linking, and categorization, with zero-config local setup or production-ready external providers.