Introduction

Neo4j MCP gives AI assistants and LLM-powered tools direct, structured access to your Neo4j graph database. By implementing the Model Context Protocol (MCP), it acts as a bridge between any MCP-compatible client, such as Claude, Cursor, or VS Code with MCP support, and your Neo4j instance.

Neo4j MCP is intended for:

  • Developers building or prototyping graph-backed AI applications who want to query Neo4j conversationally during development.

  • Data scientists and analysts who want to explore graph data without deep Cypher® expertise.

  • Platform and infrastructure teams deploying shared AI tooling that needs structured, auditable access to a Neo4j instance.

  • AI application builders integrating Neo4j as a knowledge source or reasoning backend in multi-agent systems.

Neo4j MCP enables AI agents to:

  • Explore your graph schema - discover node labels, relationship types, and property keys so the AI can reason about your data model without prior knowledge of it.

  • Run Cypher queries - execute, read, and write queries against your database in response to natural language prompts.

  • Inspect and analyze data - retrieve nodes, relationships, and paths to answer questions, generate summaries, or feed data to other workflows.

Prerequisites

Optional requirements

If an optional dependency is missing, the server starts in an adaptive mode. For instance, if the Graph Data Science (GDS) library is not detected in your Neo4j installation, the server still launches but will automatically disable all GDS-related tools, such as list-gds-procedures. All other tools remain available.

Examples for natural language prompts

Here are some example prompts you can try in Copilot or any other MCP client:

  • "What does my Neo4j instance contain? List all node labels, relationship types, and property keys."

  • "Find all Person nodes and their relationships in my Neo4j instance."

  • "Create a new User node with a name 'John' in my Neo4j instance."