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MCP Neo4j Knowledge Graph Memory Server

@JovanHsu

代码仓库

基本信息

分类

记忆与知识

许可证

MIT

传输方式

stdio

作者

JovanHsu

关于 MCP Neo4j Knowledge Graph Memory Server

MCP Memory Server with Neo4j backend for AI knowledge graph storage

#mcp-neo4j#knowledge-graph#memory-server

MCP Neo4j Knowledge Graph Memory Server 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "mcp-neo4j-memory-server-jovanhsu": {
      "command": "npx",
      "args": [
        "@jovanhsu/mcp-neo4j-memory-server"
      ]
    }
  }
}

MCP Neo4j Knowledge Graph Memory Server 工具

工具列表暂未提供

当前收录暂时没有可展示的工具列表，不代表服务没有工具。请查阅项目文档了解支持的能力。

点击上方按钮,在临时沙箱中运行此服务器并实时获取工具列表。

概览

What is MCP Neo4j Knowledge Graph Memory Server?

MCP Neo4j Knowledge Graph Memory Server is an MCP-compatible server that uses Neo4j as its backend storage engine for persisting and retrieving knowledge graphs during AI assistant interactions. It is an enhanced version of the official Knowledge Graph Memory Server, aimed at developers who need a scalable, queryable memory layer for AI conversations.

How to use MCP Neo4j Knowledge Graph Memory Server?

Install via npm (npm install -g @jovanhsu/mcp-neo4j-memory-server) or Docker. Configure environment variables NEO4J_URI, NEO4J_USER, NEO4J_PASSWORD, and NEO4J_DATABASE. Integrate with Claude Desktop by adding the server configuration to claude_desktop_config.json, or use MCP Inspector for testing. The server exposes tools to create, read, update, and delete entities, relations, and observations.

Key features of MCP Neo4j Knowledge Graph Memory Server

  • Neo4j-based high-performance graph database storage
  • Powerful fuzzy search and exact matching capabilities
  • Complete CRUD operations for entities, relations, and observations
  • Fully compatible with the MCP protocol
  • Supports complex graph queries and traversals
  • Docker support for easy deployment

Use cases of MCP Neo4j Knowledge Graph Memory Server

  • Persistent memory for AI assistants to remember user identities, preferences, and goals
  • Build complex knowledge graphs with native relationship querying
  • Scale conversational memory storage to large datasets with Neo4j’s clustering
  • Visualise and debug knowledge graphs using Neo4j’s built-in tools

常见问题

1

What advantages does this Neo4j version have over the official JSON-file version?

It offers native graph storage, high-performance Cypher queries, first-class relationship handling, built-in visualisation, and better scalability for large knowledge graphs.

2

What are the runtime requirements?

Node.js >= 22.0.0 and a Neo4j database (local or remote) are required.

3

How do I configure the server to connect to my Neo4j instance?

Set the environment variables `NEO4J_URI`, `NEO4J_USER`, `NEO4J_PASSWORD`, and `NEO4J_DATABASE`. If not set, defaults point to `bolt://localhost:7687` with user `neo4j` and password `password`.

4

Where does the knowledge graph data live?

Data is stored in your Neo4j database. The server does not persist any data locally; all entities, relations, and observations are written into the configured Neo4j instance.

5

What transport protocol does the server use?

It uses the MCP protocol over stdio transport, enabling integration with Claude Desktop or any MCP client. Authentication to Neo4j is handled via environment credentials, not through the MCP layer.

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