Happy slice of mcp pizzaMCP.pizza

mcp-neo4j

MCP.Pizza Chef: neo4j-contrib

The mcp-neo4j server is an MCP server integration that connects large language models with Neo4j graph databases. It allows users to interact with Neo4j using natural language commands, which are translated into Cypher queries for execution. This server supports querying database schemas, reading and writing graph data, and managing knowledge graph memory. It integrates with MCP clients like Claude Desktop, VS Code, and others, enabling tasks such as visualizing top products, listing instances, creating new Aura instances, and storing collaborative work facts. The mcp-neo4j server streamlines graph data operations by bridging LLMs and Neo4j, enhancing productivity and data insight through conversational AI.

Use This MCP server To

Translate natural language to Cypher queries Query Neo4j graph database schema Execute read and write Cypher commands Visualize graph data as charts Manage Neo4j Aura instances via natural language Store and retrieve knowledge graph memory Integrate Neo4j with MCP clients like Claude Desktop Automate graph data analysis and reporting

README

Neo4j MCP Clients & Servers

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), 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 exeucte generated read and write Cypher queries on that database.

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.

Contributing

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

Blog Posts

License

MIT License

mcp-neo4j FAQ

How do I configure mcp-neo4j to connect to my Neo4j database?
You configure mcp-neo4j by providing your Neo4j connection details such as URI, username, and password in the server configuration file or environment variables.
Can mcp-neo4j execute both read and write Cypher queries?
Yes, mcp-neo4j supports executing both read and write Cypher queries generated from natural language inputs.
Does mcp-neo4j support integration with multiple MCP clients?
Yes, it works seamlessly with MCP clients like Claude Desktop, VS Code, Cursor, and Windsurf.
How does mcp-neo4j handle knowledge graph memory?
The mcp-neo4j-memory server component stores and manages knowledge graph memory, enabling persistent context and collaborative data storage.
Is it possible to visualize graph data using mcp-neo4j?
Yes, mcp-neo4j can render charts and visualizations from graph data based on natural language queries.
What security measures are recommended when using mcp-neo4j?
Use secure authentication methods, restrict access to the Neo4j instance, and ensure encrypted connections to protect data integrity.
Can mcp-neo4j create and manage Neo4j Aura instances?
Yes, it supports natural language commands to create and manage Aura instances with specified configurations.
Which LLM providers are compatible with mcp-neo4j?
mcp-neo4j is provider-agnostic and works with OpenAI, Anthropic Claude, and Google Gemini models.