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Mcp Neo4j Data Modeling

neo4j-contrib/mcp-neo4j
958STDIOregistry active
Summary

This is one of four servers from the Neo4j Labs team, each tackling a different use case. This one focuses on creating and validating graph data models for Neo4j. You can design node labels, relationships, and properties through conversation, then export models to Arrows.app or import existing ones back in for refinement. It's actively maintained but comes without SLAs or backward compatibility guarantees since it's part of the experimental Labs program. If you're sketching out a graph schema with an LLM before committing it to a database, or iterating on data model designs conversationally, this gives you a dedicated toolset for that workflow.

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Neo4j Labs MCP Servers

Neo4j Labs

These MCP servers are a part of the Neo4j Labs program. They are developed and maintained by the Neo4j Field GenAI team and welcome contributions from the larger developer community. These servers are frequently updated with new and experimental features, but are not supported by the Neo4j product team.

They are actively developed and maintained, but we don’t provide any SLAs or guarantees around backwards compatibility and deprecation.

If you are looking for the official product Neo4j MCP server please find it here.

Overview

Model Context Protocol (MCP) is a standardized protocol for managing context between large language models (LLMs) and external systems.

This lets you use Claude Desktop, or any other MCP Client (VS Code, Cursor, Windsurf, Gemini CLI), to use natural language to accomplish things with Neo4j and your Aura account, e.g.:

  • What is in this graph?
  • Render a chart from the top products sold by frequency, total and average volume
  • List my instances
  • Create a new instance named mcp-test for Aura Professional with 4GB and Graph Data Science enabled
  • Store the fact that I worked on the Neo4j MCP Servers today with Andreas and Oskar

Servers

mcp-neo4j-cypher - natural language to Cypher queries

Details in Readme

Get database schema for a configured database and execute generated read and write Cypher queries on that database.

Requirement: Requires the APOC plugin to be installed and enabled on the Neo4j instance for schema inspection.

mcp-neo4j-memory - knowledge graph memory stored in Neo4j

Details in Readme

Store and retrieve entities and relationships from your personal knowledge graph in a local or remote Neo4j instance. Access that information over different sessions, conversations, clients.

mcp-neo4j-cloud-aura-api - Neo4j Aura cloud service management API

Details in Readme

Manage your Neo4j Aura instances directly from the comfort of your AI assistant chat.

Create and destroy instances, find instances by name, scale them up and down and enable features.

mcp-neo4j-data-modeling - interactive graph data modeling and visualization

Details in Readme

Create, validate, and visualize Neo4j graph data models. Allows for model import/export from Arrows.app.

Transport Modes

All servers support multiple transport modes:

  • STDIO (default): Standard input/output for local tools and Claude Desktop integration
  • SSE: Server-Sent Events for web-based deployments
  • HTTP: Streamable HTTP for modern web deployments and microservices

HTTP Transport Configuration

To run a server in HTTP mode, use the --transport http flag:

# Basic HTTP mode
mcp-neo4j-cypher --transport http

# Custom HTTP configuration
mcp-neo4j-cypher --transport http --host 127.0.0.1 --port 8080 --path /api/mcp/

Environment variables are also supported:

export NEO4J_TRANSPORT=http
export NEO4J_MCP_SERVER_HOST=127.0.0.1
export NEO4J_MCP_SERVER_PORT=8080
export NEO4J_MCP_SERVER_PATH=/api/mcp/
mcp-neo4j-cypher

Cloud Deployment

All servers in this repository are containerized and ready for cloud deployment on platforms like AWS ECS Fargate and Azure Container Apps. Each server supports HTTP transport mode specifically designed for scalable, production-ready deployments with auto-scaling and load balancing capabilities.

📋 Complete Cloud Deployment Guide →

The deployment guide covers:

  • AWS ECS Fargate: Step-by-step deployment with auto-scaling and Application Load Balancer
  • Azure Container Apps: Serverless container deployment with built-in scaling and traffic management
  • Configuration Best Practices: Security, monitoring, resource recommendations, and troubleshooting
  • Integration Examples: Connecting MCP clients to cloud-deployed servers

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

Blog Posts

  • Everything a Developer Needs to Know About the Model Context Protocol (MCP)
  • Claude Converses With Neo4j Via MCP - Graph Database & Analytics
  • Building Knowledge Graphs With Claude and Neo4j: A No-Code MCP Approach - Graph Database & Analytics
  • Using the Neo4j Extension in Gemini CLI

License

MIT License

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Configuration

NEO4J_NAMESPACE

The namespace to use for the MCP server tool names.

Categories
DatabasesData & Analytics
Registryactive
Packagemcp-neo4j-data-modeling
TransportSTDIO
UpdatedNov 7, 2025
View on GitHub

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