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

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

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.

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.

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

AI-powered VMware storage management for vSphere. Manage datastores, iSCSI targets, and vSAN via natural language with 11 MCP tools.

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.

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.

A Streamable HTTP MCP server that provides remote access to ChromaDB for AI assistants like Claude. Enables semantic search and vector database operations from mobile devices and remote locations.

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

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.

Enables Codex to manage macOS local and cloud storage by indexing files, planning moves or copies, executing them with SHA-256 verification, and requiring explicit confirmation before deleting local originals.

Provides retrieval-augmented generation (RAG) capabilities by ingesting various document formats into a persistent ChromaDB vector store. It enables semantic search and retrieval using either OpenAI or Ollama embeddings for processing local files, directories, and URLs.

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

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 Model Context Protocol server that enables running Cypher queries and retrieving schema from Neo4j databases, supporting AI-driven graph exploration and text-to-Cypher workflows.

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.