
Mcp Neo4j Memory
io.github.neo4j-contrib由 GitHub 账号 neo4j-contrib 发布v1.0.0更新于 Oct 27, 2026
MCP Neo4j Knowledge Graph Memory Server
发布方自己的服务:Memory.fit
概览
为助手提供存放在 Neo4j 中的持久化知识图谱记忆,可跨会话创建、检索和删除实体、关系与观察记录。
- 可以做什么
- 读取与检索记忆图谱:读取整张图谱、按名称/类型/观察内容搜索节点,或按名称获取指定实体
- 创建和删除实体,包含名称、类型与初始观察内容
- 创建和删除实体之间带类型的关联关系
- 为已有实体添加观察内容,或删除指定的观察内容
- 可为工具名添加命名空间前缀,便于多租户部署
- 适用场景
- 适合希望助手跨对话或跨会话记住事实及其相互关系,并以图谱方式查询这些积累知识的场景。适用于已经运行或能够部署 Neo4j 数据库(本地或 Neo4j Aura)的用户。
- 运行要求
- 以本地 Python 包(pip 或 uvx)或 Docker 镜像方式运行。需要可访问的 Neo4j 实例及凭据:NEO4J_URI、NEO4J_USERNAME、NEO4J_PASSWORD,可选 NEO4J_DATABASE 与 NEO4J_NAMESPACE。默认使用 stdio 传输,也支持 HTTP 与 SSE 模式。
安装
在 SourceWeft 中
- 打开 控制台中的 Mcp Neo4j Memory,将其添加到工作区。
- 为需要使用其工具的对话启用该服务。
Desktop only,通过 STDIO。 STDIO 服务会启动本地进程,因此需要 SourceWeft 桌面宿主。
其他 MCP 客户端
参照 仓库 中的启动说明。
README
🧠🕸️ Neo4j Knowledge Graph Memory MCP Server
mcp-name: io.github.neo4j-contrib/mcp-neo4j-memory
🌟 Overview
A Model Context Protocol (MCP) server implementation that provides persistent memory capabilities through Neo4j graph database integration.
By storing information in a graph structure, this server maintains complex relationships between entities as memory nodes and enables long-term retention of knowledge that can be queried and analyzed across multiple conversations or sessions.
With Neo4j Aura you can host your own database server for free or share it with your collaborators. Otherwise you can run your own Neo4j server locally.
The MCP server leverages Neo4j's graph database capabilities to create an interconnected knowledge base that serves as an external memory system. Through Cypher queries, it allows exploration and retrieval of stored information, relationship analysis between different data points, and generation of insights from the accumulated knowledge. This memory can be further enhanced with Claude's capabilities.
🕸️ Graph Schema
Memory- A node representing an entity with a name, type, and observations.Relationship- A relationship between two entities with a type.
🔍 Usage Example
Results in Claude calling the create_entities and create_relations tools.
📦 Components
🔧 Tools
The server offers these core tools:
🔎 Query Tools
-
read_graph- Read the entire knowledge graph
- No input required
- Returns: Complete graph with entities and relations
-
search_nodes- Search for nodes based on a query
- Input:
query(string): Search query matching names, types, observations
- Returns: Matching subgraph
-
find_nodes- Find specific nodes by name
- Input:
names(array of strings): Entity names to retrieve
- Returns: Subgraph with specified nodes
♟️ Entity Management Tools
-
create_entities- Create multiple new entities in the knowledge graph
- Input:
entities: Array of objects with:name(string): Name of the entitytype(string): Type of the entityobservations(array of strings): Initial observations about the entity
- Returns: Created entities
-
delete_entities- Delete multiple entities and their associated relations
- Input:
entityNames(array of strings): Names of entities to delete
- Returns: Success confirmation
🔗 Relation Management Tools
-
create_relations- Create multiple new relations between entities
- Input:
relations: Array of objects with:source(string): Name of source entitytarget(string): Name of target entityrelationType(string): Type of relation
- Returns: Created relations
-
delete_relations- Delete multiple relations from the graph
- Input:
relations: Array of objects with same schema as create_relations
- Returns: Success confirmation
📝 Observation Management Tools
-
add_observations- Add new observations to existing entities
- Input:
observations: Array of objects with:entityName(string): Entity to add tocontents(array of strings): Observations to add
- Returns: Added observation details
-
delete_observations- Delete specific observations from entities
- Input:
deletions: Array of objects with:entityName(string): Entity to delete fromobservations(array of strings): Observations to remove
- Returns: Success confirmation
🔧 Usage with Claude Desktop
💾 Installation
⚙️ Configuration
Add the server to your claude_desktop_config.json with configuration of:
Alternatively, you can set environment variables:
Namespacing
For multi-tenant deployments, add --namespace to prefix tool names:
Tools become: myapp-read_graph, myapp-create_entities, etc.
Can also use NEO4J_NAMESPACE environment variable.
🌐 HTTP Transport Mode
The server supports HTTP transport for web-based deployments and microservices:
Environment variables for HTTP configuration:
🔄 Transport Modes
The server supports three transport modes:
- STDIO (default): Standard input/output for local tools and Claude Desktop
- SSE: Server-Sent Events for web-based deployments
- HTTP: Streamable HTTP for modern web deployments and microservices
🐳 Using with Docker
🔒 Security Protection
The server includes comprehensive security protection with secure defaults that protect against common web-based attacks while preserving full MCP functionality when using HTTP transport.
🛡️ DNS Rebinding Protection
TrustedHost Middleware validates Host headers to prevent DNS rebinding attacks:
Secure by Default:
- Only
localhostand127.0.0.1hosts are allowed by default
Environment Variable:
🌐 CORS Protection
Cross-Origin Resource Sharing (CORS) protection blocks browser-based requests by default:
Environment Variable:
🔧 Complete Security Configuration
Development Setup:
Production Setup:
🚨 Security Best Practices
For allow_origins:
- Be specific:
["https://example.com", "https://example.com"] - Never use
"*"in production with credentials - Use HTTPS origins in production
For allowed_hosts:
- Include your actual domain:
["example.com", "www.example.com"] - Include localhost only for development
- Never use
"*"unless you understand the risks
🐳 Docker Deployment
The Neo4j Memory MCP server can be deployed using Docker for remote deployments. Docker deployment should use HTTP transport for web accessibility. In order to integrate this deployment with applications like Claude Desktop, you will have to use a proxy in your MCP configuration such as mcp-remote.
📦 Using Your Built Image
After building locally with docker build -t mcp-neo4j-memory:latest .:
🔧 Environment Variables
🌐 SSE Transport for Legacy Web Access
When using SSE transport (for legacy web clients), the server exposes an HTTP endpoint:
🚀 Development
📦 Prerequisites
- Install
uv(Universal Virtualenv):
- Clone the repository and set up development environment:
🐳 Docker
Build and run the Docker container:
📄 License
This MCP server is licensed under the MIT License. This means you are free to use, modify, and distribute the software, subject to the terms and conditions of the MIT License. For more details, please see the LICENSE file in the project repository.
来源:servers/mcp-neo4j-memory/README.md,提交 1c7ad07
工具
0版本历史
1- v1.0.0最新Sep 16, 2026
评分
已满足适用检查项的 50%
该评分衡量此收录条目的完整程度,依据注册中心条目、端点与公开来源计算得出。它不是对服务器本身的评价,也不表示服务器安全或当前可用:可连通性是带日期的检查结果,评分也不包含安装量或用户评价。
- 近 30 天内可连通25 分
请保持端点能够响应 MCP 握手;SourceWeft 每 30 天探测一次。
- 已声明认证方式10 分
请在注册中心条目中声明凭据请求头,或保持端点能够响应探测,以便判定其认证方式。
- 已列出工具15 分
请让服务器在无凭据时响应 tools/list,或发布可在沙箱中无凭据启动的软件包。
- 描述必需15 分
- 图标10 分
- 文档15 分
- 许可证10 分
其他 Memory 集成

Memory.fit
fit.memory官方发布者
托管式 Memory.fit 服务器,让 AI 读取你的训练、睡眠、恢复与饮食数据,并写回每周计划、每日目标和饮食计划。
pg.ddx.io: the PostgreSQL community's memory
io.ddx.pg官方发布者
pg.ddx.io: the PostgreSQL community's memory 的托管 MCP 服务,由 pg.ddx.io 发布;无需登录;Streamable HTTP;29 个工具。
var.gg Naming Memory
gg.var官方发布者
远程 MCP 服务器,可根据领域概念推荐并检索韩、日、中、越、英多语言的代码标识符名称,并提供 ERD 结构查询。

Counterparts
ai.counterparts
面向 Claude Code 与 Claude Desktop 的本地优先长期记忆:助手自行写下关于你和项目的笔记,并在之后的会话中回忆起来。

LAHZE - Persian AI Memory Platform
由 GitHub 账号 pedramgholizadeh 发布
以波斯语为先的地理记忆平台:发现地点,起草并发布仅限波斯语的记忆。AI 翻译