How do I connect the Neo4j MCP Server to my AI client?

To connect Neo4j to your client (like Claude Desktop or Cursor), add the server command to your configuration file (e.g., 'claude_desktop_config.json'). You can run it locally using npx or deploy it to our secure managed cloud at MCPserver.in with one-click.

What security controls are available on the Neo4j integration?

The Neo4j MCP server keeps your API credentials secured in environment variables on your host or deployed cluster. It executes tools in a sandboxed runtime, requiring user confirmation for write, delete, or external publishing actions.

Does the Neo4j MCP Server support real-time data lookups?

Yes! By utilizing Model Context Protocol Resources, the Neo4j server queries active API endpoints on-demand, returning live context directly to the LLM context window without relying on outdated web caches.

What are the typical use cases for the Neo4j AI connector?

Common use cases include automating Neo4j data lookups, pulling active report profiles, updating statuses directly from chat inputs, and synchronizing project files with development environments.

What is the cost of running the Neo4j MCP integration?

Running the server locally on your machine is 100% free. If you deploy it to our fully-managed hosting in India for team access, it is covered under the Developer tier (₹999/mo) or our Pro plan with low-latency edge scaling.

Verified MCP Connector

Neo4j MCP Server

Connect to Neo4j graph databases. Allow AI models to execute Cypher queries and traverse intricate network relationships.

Quick Answer / TL;DR

The Neo4j MCP server establishes a secure, local or remote JSON-RPC 2.0 communication tunnel, allowing AI models (like Claude or Cursor) to automatically discover and execute capabilities (tools, prompts, and resources) within the Neo4j ecosystem with extremely low latency.

Key Takeaways

Map graph database nodes
Analyze fraud networks
Retrieve path connections

Core Integration Concept

Connecting the model to Neo4j bypasses complex setup. The LLM can auto-discover what endpoints are active, what input variables are expected, and how answers will be delivered.

Verified Use Cases

Map graph database nodes

Analyze fraud networks

Retrieve path connections

Setup Overview

Connection Setup Checklist

Prepare Credentials: Obtain your Neo4j Auth Credentials credentials directly from your Neo4j settings.
Update Config: Add the executable tool command structure directly to your Claude config file.
Restart & Confirm: Reload the desktop model client to complete the connection handshake sequence.

Sample Connection Schema

{
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "name": "execute_neo4j",
    "arguments": {
      "query": "status_check"
    }
  },
  "id": 1
}

Security Considerations

To guarantee perfect data isolation, safeguard the Neo4j Auth Credentials credentials. Always run integrations in sandboxed contexts to block unsolicited access.

Best Practices

Configure exact resource boundaries for the Cypher queries execution feature.
Configure exact resource boundaries for the Graph metadata map feature.
Configure exact resource boundaries for the Node count tallies feature.
Configure exact resource boundaries for the Relationship insights feature.

Dr. Devashish Sen

Lead Systems & Protocol Architect, MCPserver India

Published: 2026-03-12

Updated: 2026-07-09

References & Technical Specifications

Required Auth Keys

Neo4j Auth Credentials

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Neo4j - FAQ

Contextual information and technical support details regarding Model Context Protocol integration