Neo4j MCP

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.

Features

• Explore your graph schema - discover node labels, relationship types, and property keys
• Let AI reason on your data model without prior knowledge
• 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

Installation

Install with PyPI:

pip install neo4j-mcp-server

Otherwise see MCP documentation -> Installation.

Server configuration (VSCode)

Create / edit mcp.json:

{
  "servers": {
    "neo4j": {
      "type": "stdio",
      "command": "python",
      "args": ["-m", "neo4j_mcp_server"],
      "env": {
        "NEO4J_URI": "bolt://localhost:7687",
        "NEO4J_USERNAME": "neo4j",
        "NEO4J_PASSWORD": "password",
        "NEO4J_DATABASE": "neo4j",
        "NEO4J_READ_ONLY": "true",
        "NEO4J_TELEMETRY": "false",
        "NEO4J_LOG_LEVEL": "info",
        "NEO4J_LOG_FORMAT": "text",
        "NEO4J_SCHEMA_SAMPLE_SIZE": "100"
      }
    }
  }
}

See MCP documentation > Configuration for more details.

Links

• Documentation: The official Neo4j MCP documentation.
• Discord: The Neo4j discord channel.
• Contributing Guide: Contribution workflow, development environment, mocks and testing.

For issues and feedback, you can also create a GitHub issue with reproduction details (omit sensitive data).