npx mcpbar@latest install sylweriusz/mcp-neo4j-memory-server -c claude

npx mcpbar@latest edit -c claude

{
  "mcpServers": {
    "Neo4j Knowledge Graph Memory Server": {
      "command": "npx",
      "args": [
        "-y",
        "@sylweriusz/mcp-neo4j-memory-server"
      ],
      "env": {
        "NEO4J_URI": "bolt://localhost:7687",
        "NEO4J_USERNAME": "neo4j",
        "NEO4J_PASSWORD": "your-password",
        "NEO4J_DATABASE": "neo4j"
      }
    }
  }
}

Neo4j Memory Server

A Model Context Protocol (MCP) server that provides AI assistants with persistent, intelligent memory capabilities using Neo4j's graph database with unified architecture

What it does

This server enables AI assistants to:

• Remember - Store memories as interconnected knowledge nodes with observations and metadata
• Search - Find relevant memories using semantic vector search, exact matching, and graph traversal
• Connect - Create meaningful relationships between memories with batch operations and cross-references
• Organize - Separate memories by project using different databases
• Evolve - Track how knowledge develops over time with temporal metadata and relationship networks

Features

Core Capabilities

• 🧠 Graph Memory - Memories as nodes, relationships as edges, observations as content
• 🔍 Unified Search - Semantic vectors, exact matching, wildcards, and graph traversal in one tool
• 🔗 Smart Relations - Typed connections with strength, source tracking, and temporal metadata
• 📊 Multi-Database - Isolated project contexts with instant switching

Advanced Operations

• ⚡ Batch Operations - Create multiple memories with relationships in single request using localId
• 🎯 Context Control - Response detail levels: minimal (lists), full (complete data), relations-only
• 📅 Time Queries - Filter by relative ("7d", "30d") or absolute dates on any temporal field
• 🌐 Graph Traversal - Navigate networks in any direction with depth control

Architecture

• 🚀 MCP Native - Seamless integration with Claude Desktop and MCP clients
• 💾 Persistent Storage - Neo4j graph database with GDS plugin for vector operations
• ⚠️ Zero-Fallback - Explicit errors for reliable debugging, no silent failures

Technical Highlights

• Built on Neo4j for scalable graph operations
• Vector embeddings using sentence transformers (384 dimensions)
• Clean architecture with domain-driven design
• Supports GDS plugin for advanced vector operations (necessary)
• Unified Architecture - 4 comprehensive tools for complete memory operations

Quick Start

npm install @sylweriusz/mcp-neo4j-memory-server

Add to Claude Desktop config:

{
  "mcpServers": {
    "memory": {
      "command": "npx",
      "args": ["-y", "@sylweriusz/mcp-neo4j-memory-server"],
      "env": {
        "NEO4J_URI": "bolt://localhost:7687",
        "NEO4J_USERNAME": "neo4j", 
        "NEO4J_PASSWORD": "your-password"
      }
    }
  }
}

Neo4j Setup

Working setup: DozerDB with GDS Plugin

For the database, use DozerDB with the Graph Data Science plug-in, GDS is not only recommended but necessary:

For current installation instructions, see: https://dozerdb.org/

Example setup:

# Run DozerDB container with latest version
docker run \
    -p 7474:7474 -p 7687:7687 \
    -v $HOME/neo4j/data:/data \
    -v $HOME/neo4j/logs:/logs \
    -v $HOME/neo4j/plugins:/plugins \
    --env NEO4J_AUTH=neo4j/password \
    --env NEO4J_dbms_security_procedures_unrestricted='gds.*' \
    graphstack/dozerdb:latest

# Install GDS plugin - see dozerdb.org for current instructions

# Verify GDS plugin works
# In Neo4j Browser (http://localhost:7474):
# RETURN gds.similarity.cosine([1,2,3], [2,3,4]) as similarity

Unified Tools

The server provides 4 unified MCP tools that integrate automatically with Claude:

• memory_store - Create memories with observations and immediate relations in ONE operation
• memory_find - Unified search/retrieval with semantic search, direct ID lookup, date filtering, and graph traversal
• memory_modify - Comprehensive modification operations (update, delete, observations, relations)
• database_switch - Switch database context for isolated environments

Memory Structure

{
  "id": "dZ$abc123",
  "name": "Project Alpha", 
  "memoryType": "project",
  "metadata": {"status": "active", "priority": "high"},
  "observations": [
    {"id": "dZ$obs456", "content": "Started development", "createdAt": "2025-06-08T10:00:00Z"}
  ],
  "related": {
    "ancestors": [{"id": "dZ$def789", "name": "Initiative", "relation": "PART_OF", "distance": 1}],
    "descendants": [{"id": "dZ$ghi012", "name": "Task", "relation": "INCLUDES", "distance": 1}]
  }
}

System Prompt

The simplest use of the memory tool, the following usually is more than enough.

## Memory Tool Usage
- Store all memory for this project in database: 'project-database-name'
- Use MCP memory tools exclusively for storing project-related information
- Begin each session by:
  1. Switching to this project's database
  2. Searching memory for data relevant to the user's prompt

Troubleshooting

Vector Search Issues:

• Check logs for [VectorSearch] GDS Plugin detected
• GDS Plugin requires DozerDB setup (see Neo4j Setup section)

Connection Issues:

• Verify Neo4j is running: docker ps
• Test connection: curl http://localhost:7474
• Check credentials in environment variables

License

MIT