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 $HOME/neo4j/plugins:/plugins \
--env NEO4J_AUTH=neo4j/password \
--env NEO4J_dbms_security_procedures_unrestricted='gds.*' \
graphstack/dozerdb:latest
# Install GDS plugin - see dozerdb.org for current instructions
# Verify GDS plugin works
# In Neo4j Browser (http://localhost:7474):
# RETURN gds.similarity.cosine([1,2,3], [2,3,4]) as similarity
Unified Tools
The server provides 4 unified MCP tools that integrate automatically with Claude:
memory_store- Create memories with observations and immediate relations in ONE operationmemory_find- Unified search/retrieval with semantic search, direct ID lookup, date filtering, and graph traversalmemory_modify- Comprehensive modification operations (update, delete, observations, relations)database_switch- Switch database context for isolated environments
Memory Structure
{
"id": "dZ$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