Unleashing the Power of LLMs with Neo4j: A Deep Dive into Model Context Protocol (MCP) Integration

The Model Context Protocol (MCP) is revolutionizing how Large Language Models (LLMs) interact with external systems. By providing a standardized interface, MCP empowers developers to seamlessly connect LLMs with the data and tools they need to build intelligent, context-aware applications. This document explores the Neo4j MCP ecosystem, showcasing how you can leverage this powerful protocol to unlock new possibilities for graph-powered AI.

Neo4j MCP Servers: Bridging the Gap Between Natural Language and Graph Data

This suite of Neo4j MCP servers provides a robust foundation for integrating Neo4j with various MCP-compliant clients, such as Claude Desktop, VS Code, Cursor, and Windsurf. This integration enables you to interact with your Neo4j data and Aura account using natural language, opening up a world of possibilities:

• Effortless Graph Exploration: Ask questions like "What is in this graph?" and receive insightful summaries of your data.
• Dynamic Data Visualization: Generate charts and visualizations on the fly, such as "Render a chart from the top products sold by frequency, total and average volume."
• Simplified Cloud Management: Manage your Neo4j Aura instances with ease, using commands like "List my instances" or "Create a new instance named mcp-test for Aura Professional with 4GB and Graph Data Science enabled."
• Knowledge Graph Enrichment: Seamlessly store and retrieve information in your personal knowledge graph, capturing valuable insights like "Store the fact that I worked on the Neo4j MCP Servers today with Andreas and Oskar."

1. mcp-neo4j-cypher: Natural Language to Cypher Query Conversion

This server acts as a translator, converting natural language requests into executable Cypher queries. By understanding your database schema, it can generate both read and write queries, allowing you to interact with your Neo4j data in a more intuitive way.

• Explore the Details

2. mcp-neo4j-memory: Persistent Knowledge Graph Storage

This server enables you to store and retrieve entities and relationships within a Neo4j instance, creating a persistent knowledge graph that can be accessed across different sessions, conversations, and clients. This allows you to build a rich, interconnected understanding of your data over time.

• Explore the Details

3. mcp-neo4j-cloud-aura-api: Streamlined Neo4j Aura Management

This server provides a direct interface to the Neo4j Aura cloud service management API, allowing you to manage your Aura instances directly from your AI assistant. Create, destroy, scale, and configure your instances with simple natural language commands.

• Explore the Details

Contributing to the Neo4j MCP Ecosystem

We encourage contributions from the community! If you're passionate about graph technology and LLMs, please feel free to submit a Pull Request.

Further Reading: Deepen Your Understanding of Neo4j and MCP

• Everything a Developer Needs to Know About the Model Context Protocol (MCP): A comprehensive overview of the MCP protocol and its benefits.
• Claude Converses With Neo4j Via MCP - Graph Database & Analytics: Explore how Claude, a powerful LLM, can interact with Neo4j through MCP.
• Building Knowledge Graphs With Claude and Neo4j: A No-Code MCP Approach - Graph Database & Analytics: Learn how to build knowledge graphs using Claude and Neo4j with a no-code MCP approach.