MCP 服务器

Memory Custom

一个定制的 MCP 内存服务器，能够创建和管理知识图谱，并具有自定义内存路径和时间戳等功能，用于捕获通过语言模型进行的交互。

AI记忆系统

数据库交互

数据与应用分析

访问服务器

Tools

set_memory_file_path

Set the memory file path

get_current_time

Get the current time

create_entities

Create multiple new entities in the knowledge graph

create_relations

Create multiple new relations between entities in the knowledge graph. Relations should be in active voice

add_observations

Add new observations to existing entities in the knowledge graph

delete_entities

Delete multiple entities and their associated relations from the knowledge graph

delete_observations

Delete specific observations from entities in the knowledge graph

delete_relations

Delete multiple relations from the knowledge graph

read_graph

Read the entire knowledge graph

search_nodes

Search for nodes in the knowledge graph based on a query

open_nodes

Open specific nodes in the knowledge graph by their names

README

Memory Custom

此项目为 MCP 团队提供的 Memory 服务器添加了新功能。它允许创建和管理知识图谱，该图谱通过语言模型 (LLM) 捕获交互。

新功能

1. 自定义内存路径

用户现在可以为不同的项目指定不同的内存文件路径。
原因？：此功能增强了内存数据的组织和管理，允许项目特定的内存存储。

2. 时间戳

服务器现在为交互生成时间戳。
原因？：时间戳能够跟踪每个内存的创建或修改时间，为存储的数据提供更好的上下文和历史记录。

开始使用

前提条件

Node.js（版本 16 或更高）

通过 Smithery 安装

要通过 Smithery 自动为 Claude Desktop 安装 Knowledge Graph Memory Server：

npx -y @smithery/cli install @BRO3886/mcp-memory-custom --client claude

安装

克隆存储库：

git clone git@github.com:BRO3886/mcp-memory-custom.git
cd mcp-memory-custom

安装依赖项：
```
npm install
```

配置

在运行服务器之前，您可以设置 MEMORY_FILE_PATH 环境变量来指定内存文件的路径。如果未设置，服务器将默认使用与脚本位于同一目录中的 memory.json。

运行服务器

更新 mcp server json 文件

将此添加到您的 claude_desktop_config.json / .cursor/mcp.json 文件中：

{
  "mcpServers": {
    "memory": {
      "command": "node",
      "args": ["/path/to/mcp-memory-custom/dist/index.js"]
    }
  }
}

系统提示更改：

Follow these steps for each interaction:
1. The memoryFilePath for this project is /path/to/memory/project_name.json - always pass this path to the memory file operations (when creating entities, relations, or retrieving memory etc.)
2. User Identification:
   - You should assume that you are interacting with default_user
   - If you have not identified default_user, proactively try to do so.

3. Memory Retrieval:
   - Always begin your chat by saying only "Remembering..." and retrieve all relevant information from your knowledge graph
   - Always refer to your knowledge graph as your "memory"

4. Memory
   - While conversing with the user, be attentive to any new information that falls into these categories:
     a) Basic Identity (age, gender, location, job title, education level, etc.)
     b) Behaviors (interests, habits, etc.)
     c) Preferences (communication style, preferred language, etc.)
     d) Goals (goals, targets, aspirations, etc.)
     e) Relationships (personal and professional relationships up to 3 degrees of separation)

5. Memory Update:
   - If any new information was gathered during the interaction, update your memory as follows:
     a) Create entities for recurring organizations, people, and significant events, add timestamps to wherever required. You can get current timestamp via get_current_time
     b) Connect them to the current entities using relations
     c) Store facts about them as observations, add timestamps to observations via get_current_time


IMPORTANT: Provide a helpful and engaging response, asking relevant questions to encourage user engagement. Update the memory during the interaction, if required, based on the new information gathered (point 4).