MCP Neo4j Memory Server
@sylweriusz
MCP Neo4j Memory Server について
概要はまだありません
基本情報
設定
以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。
{
"mcpServers": {
"mcp-neo4j-memory-server": {
"command": "docker",
"args": [
"run",
"\\"
]
}
}
}ツール
ツールは検出されませんでした
ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。
概要
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.
「メモリとナレッジ」の他のコンテンツ
MCP server for Obsidian
MarkusPfundsteinMCP server that interacts with Obsidian via the Obsidian rest API community plugin

Dash Api Docs Mcp Server
KapeliMCP server for Dash, the macOS API documentation browser
Memory Bank MCP Server
alioshrA Model Context Protocol (MCP) server implementation for remote memory bank management, inspired by Cline Memory Bank.
Jupyter Notebook MCP Server (for Cursor)
jbenoModel Context Protocol (MCP) server designed to allow AI agents within Cursor to interact with Jupyter Notebook (.ipynb) files
Context7 MCP - Up-to-date Docs For Any Cursor Prompt
upstashContext7 Platform -- Up-to-date code documentation for LLMs and AI code editors
コメント