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MCP Neo4j Memory Server

@sylweriusz

代码仓库

关于 MCP Neo4j Memory Server

暂无概览

基本信息

分类

记忆与知识

许可证

MIT

运行时

node

传输方式

stdio

发布者

sylweriusz

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": {
      "command": "docker",
      "args": [
        "run",
        "\\"
      ]
    }
  }
}

工具

未检测到工具

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

What is MCP Neo4j Memory Server?

An MCP server that gives AI assistants persistent, intelligent memory using Neo4j’s graph database. It stores memories as interconnected knowledge nodes, supports semantic and exact search, creates typed relationships, organizes data by project, and tracks knowledge evolution over time.

How to use MCP Neo4j Memory Server?

Install via npm install @sylweriusz/mcp-neo4j-memory-server, then add the tool to your Claude Desktop config with environment variables NEO4J_URI, NEO4J_USERNAME, and NEO4J_PASSWORD. You must run a Neo4j database with the GDS plugin (recommended: DozerDB). Four unified MCP tools—memory_store, memory_find, memory_modify, and database_switch—handle all memory operations.

Key features of MCP Neo4j Memory Server

  • Stores memories as nodes with typed relationships and temporal metadata
  • Unified search: vectors, exact matches, wildcards, and graph traversal
  • Creates multiple memories with relations in a single batch request
  • Isolates projects via separate databases with instant switching
  • Filters memories by relative or absolute date on any temporal field
  • Zero-fallback error handling for reliable debugging

Use cases of MCP Neo4j Memory Server

  • Remember facts, preferences, and context across AI conversations
  • Find relevant memories using semantic search or exact ID lookups
  • Create meaningful connections between memories with cross-references
  • Organize and isolate memories for different projects or topics
  • Track how knowledge changes over time with versioned observations

FAQ from MCP Neo4j Memory Server

What database does the server require?

It requires Neo4j with the Graph Data Science (GDS) plugin. The recommended setup is DozerDB (docker pull graphstack/dozerdb). GDS is necessary for vector operations.

What are the four MCP tools?

memory_store (create memories with relations), memory_find (search/retrieve), memory_modify (update, delete, manage observations/relations), and database_switch (change project context).

How do I troubleshoot vector search failures?

Check the server logs for [VectorSearch] GDS Plugin detected. If missing, ensure the GDS plugin is installed and Neo4j is running with the correct configuration.

Can I use this server without a graph database?

No. Neo4j (with GDS) is a required persistent storage layer. The server has no fallback or in‑memory mode.

How do I connect to an existing Neo4j instance?

Set the NEO4J_URI, NEO4J_USERNAME, and NEO4J_PASSWORD environment variables in your MCP client config. Test connectivity via curl http://localhost:7474.

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