Overview
Features
Natural language to Cypher
Translates natural language requests into Cypher queries for a configured Neo4j database and can retrieve the database schema or execute generated queries.
Knowledge graph memory
Stores and retrieves entities and relationships in a personal knowledge graph, accessible across sessions and clients.
Aura cloud management
Manage Neo4j Aura instances directly from your AI assistant: create/destroy, find by name, scale, and enable features.
Interactive data modeling
Create, validate, and visualize graph data models with support for Arrows.app import/export.
Multiple transport modes
All servers support STDIO, SSE, and HTTP for local tooling, web deployments, and microservices.
HTTP transport configuration
Run in HTTP mode with custom host/port/path or via environment variables.
Containerized deployment
Servers are containerized and ready for cloud deployment on AWS ECS Fargate and Azure Container Apps.
Cloud deployment guide
Includes a complete guide covering AWS ECS Fargate and Azure Container Apps, plus security, monitoring, and troubleshooting best practices.
Who Is This For?
- Developers:Integrate MCP with Neo4j to manage graphs and queries using natural language through Claude Desktop or other MCP clients.
- Neo4j users:Access and manage their graphs, memory graphs, and Aura resources with LLM-assisted workflows.
- AI teams:Build AI-powered graph analytics, modeling, and data visualization workflows with MCP.




