"Using ChromaDB and Neo4j for persistent memory storage" matching MCP servers:

Provides AI assistants with persistent graph-based memory capabilities using Neo4j, enabling semantic search, relationship tracking, and knowledge organization across multiple project contexts.

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.

Gives Claude Code long-term memory that persists across sessions via hybrid BM25 and vector semantic search, with multi-project isolation.

Enhanced knowledge graph memory server for AI assistants that uses Neo4j as the backend storage engine, enabling powerful graph queries and efficient storage of user interaction information with full MCP protocol compatibility.

Turns a codebase into a persistent knowledge graph so AI coding agents can answer structural questions about functions, call chains, routes, and cross-service links through graph queries instead of reading files one by one.

A memory management system that enables AI assistants to store, search, and visualize persistent conversation contexts using a Neo4j graph database. It provides an MCP server for integration with Claude Desktop along with a web-based dashboard for managing relationship-based knowledge.

Neo4j MCP Canary is a fast-moving, experimental release of the Neo4j MCP server for customers who want to explore emerging capabilities before they are considered for the official server.

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.

MCP server for Neo4j graph database operations, enabling Cypher queries, node/relationship management, and schema discovery.

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

Provides persistent, inspectable memory storage for AI agents using SQLite. Agents can store, recall, and search memories across sessions via three MCP tools.

MCP server for Neo4j that provides abstract graph operations for LLMs, enabling safe and consistent interaction with Neo4j databases through tools like search, insert, update, delete, and schema introspection.

A single local MCP gateway for Neo4j that exposes both proxied generic Neo4j tools (schema, Cypher, GDS) and custom YAML-defined use-case tools behind one stdio endpoint.

Enables LLMs to run complex graph algorithms on Neo4j databases, answering graph-related questions by selecting and executing appropriate parameterised graph algorithms.

A lightweight memory layer for MCP servers that persists user context across LLM sessions with minimal token cost, supporting key-value dedup, multi-tenant namespaces, and optional TTL.

A self-hostable MCP server that provides permanent memory for AI agents using Postgres + pgvector for semantic search and Markdown file sync.

A local-first MCP server providing persistent, searchable knowledge base via SQLite, enabling AI agents to save and recall facts across sessions without cloud dependencies.

Enables LLM agents to maintain structured long-term memory and knowledge using SQLite, with graph storage and relational query tools for persistent context.

Enables interaction with Neo4j databases from the Cursor IDE by executing Cypher queries, managing connections, and retrieving database information.

A fork of the Neo4j Model Context Protocol server that enables interaction with Neo4j knowledge graphs through environment variable configuration and improved options for remote connections.