MCP Neo4j Memory Server

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