io.github.neo4j-contrib/mcp-neo4j-aura-manager MCP Server
io.github.neo4j-contrib/mcp-neo4j-aura-manager
Manage Neo4j Aura database instances via natural language through Claude and other MCP clients.
What is the io.github.neo4j-contrib/mcp-neo4j-aura-manager MCP server?
The Neo4j Aura Manager MCP server enables you to manage your Neo4j Aura cloud database instances directly from AI assistants like Claude. It provides tools to create, destroy, list, scale, and configure Aura instances using natural language commands.
This server connects your AI assistant to the Neo4j Aura cloud service API, letting you perform administrative tasks on your database instances without leaving your chat interface. You can create new instances, manage scaling, enable features, and query instance details—all through conversational commands.
How to install io.github.neo4j-contrib/mcp-neo4j-aura-manager
Copy-paste configuration for popular MCP clients.
NEO4J_AURA_CLIENT_IDrequiredsecretNeo4j Aura API Client ID
NEO4J_AURA_CLIENT_SECRETrequiredsecretNeo4j Aura API Client Secret
NEO4J_NAMESPACENamespace for tools
Tools & capabilities
Tools this server exposes to the agent.
List instances— Retrieve a list of your Neo4j Aura instancesCreate instance— Create a new Neo4j Aura instance with specified configuration (name, tier, storage, features)Delete instance— Destroy a Neo4j Aura instanceScale instance— Adjust the size and resources of an existing instanceEnable features— Enable optional features like Graph Data Science on instancesFind instance by name— Search for and retrieve details of a specific instance
Use cases
- Create a new Aura Professional instance with 4GB storage and Graph Data Science enabled
- List all your current Neo4j Aura instances and their configurations
- Scale an existing instance up or down to adjust resources
- Delete instances you no longer need
- Enable Graph Data Science or other features on running instances
io.github.neo4j-contrib/mcp-neo4j-aura-manager MCP server FAQ
It's an MCP server that connects your AI assistant to Neo4j Aura's cloud management API, allowing you to create, manage, and configure database instances through natural language.
The server itself is free and open-source (MIT License), but you need a Neo4j Aura account and will be charged for the cloud instances you create and run.
Install via PyPI using `pip install mcp-neo4j-aura-manager`, then configure it in your MCP client's settings to connect to your Neo4j Aura account.
You need valid Neo4j Aura credentials (typically an API token or account credentials) to authenticate and manage your instances.
No, this is part of Neo4j Labs and is maintained by the Field GenAI team. The official product MCP server is available separately at https://github.com/neo4j/mcp.
The server supports STDIO (default for local use), SSE, and HTTP modes for cloud deployments on AWS ECS Fargate and Azure Container Apps.
README (reference)
Source of truth, from the repository.
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
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
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
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
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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io.github.neo4j-contrib/mcp-neo4j-cypher
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