Neo4J Server Remote

The Neo4J Server Remote MCP server bridges the gap between conversational AI assistants and graph databases. By exposing Neo4j through the Model Context Protocol, it allows assistants like Claude to execute Cypher queries, retrieve schema information, and manipulate graph data as if they were native tools. This capability removes the need for developers to write custom adapters or manage low‑level database connections, enabling rapid integration of graph analytics into AI workflows.

At its core, the server offers three categories of tools. The query tools— and —handle read‑only and update operations respectively, returning results in JSON format that can be directly consumed by downstream prompts or visualizations. The schema tool, , provides a comprehensive view of node labels, properties, and relationships, which is invaluable for generating context‑aware prompts or auto‑completing query templates. Together these tools give developers a declarative interface to the graph, abstracting away connection strings, transaction handling, and result parsing.

The server supports two transport modes: Server‑Sent Events (SSE) for real‑time, streaming interactions and STDIO for local or containerized deployments. SSE is the default mode, making it easy to host a single instance that multiple AI assistants can query concurrently. STDIO is ideal for development or when network restrictions prevent external access, allowing the server to run as a child process of an AI client. Both modes preserve the same MCP contract, ensuring consistent behavior across environments.

Real‑world use cases abound. A data analyst can ask an AI assistant to “find all employees who worked on project X and have more than five years of experience,” and the assistant will translate that into a Cypher query, execute it via , and return the results. A knowledge‑base builder might use to generate documentation for new graph entities, while an application developer could employ to seed test data. Because the server exposes a prompt () that walks users through schema creation and sample data insertion, onboarding is streamlined for teams unfamiliar with Neo4j.

What sets this MCP server apart is its focus on remote accessibility combined with a lightweight transport layer. Developers can host the server behind an API gateway, secure it with TLS, or run it locally for debugging—all without modifying the AI client. The server’s design adheres to MIT licensing, encouraging community contributions and rapid iteration. By turning graph operations into first‑class MCP tools, the Neo4J Server Remote empowers AI assistants to unlock insights from complex relational data with minimal friction.