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mason-yb-zhang

local-memory-mcp

by mason-yb-zhang
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Python
Local

local-memory-mcp

本地向量 + 知识图谱记忆 MCP Server，基于 LanceDB 和 Kuzu。

所有数据保存在本地 ~/.kimi-memory/，不依赖外部云服务，适合给 Kimi Code、workbuddy、Cursor 等 Agent 提供跨会话共享记忆。

特性

  • 向量语义检索：使用 BGE 中文 Embedding 模型，支持同义词召回

  • 知识图谱关系：用 Kuzu 存储记忆之间的主题、项目、工具、时间关系

  • 短期 / 长期记忆：自动分层，支持 promote、decay、consolidate

  • 跨 Agent 共享：通过 MCP 协议接入任意支持 MCP 的 Agent

  • 本地备份：一键导出 JSONL + 打包数据目录到百度网盘同步空间

Related MCP server: Memsolus MCP Server

快速开始

cd ~/.kimi-code/skills/local-memory-mcp
python scripts/install.py

安装脚本会：

  1. 创建 Python 虚拟环境

  2. 安装 LanceDB、Kuzu、sentence-transformers 等依赖

  3. 预下载 BGE-small 中文 Embedding 模型

  4. 注册 MCP Server 到 Kimi Code

然后重启 Kimi Code CLI即可使用。

数据目录

~/.kimi-memory/
├── lancedb/     # 向量数据库
├── kuzu/        # 图数据库
├── models/      # 本地 Embedding 模型
├── backups/     # 备份文件
└── config.yaml  # 配置文件

备份

# 导出 JSONL 并打包到百度网盘同步目录
python scripts/backup.py

# 只导出 JSONL
python scripts/backup.py --jsonl-only

# 指定目标目录
python scripts/backup.py --target D:\\Backups\\kimi-memory

环境变量

变量

说明

默认值

LOCAL_MEMORY_DATA_DIR

数据根目录

~/.kimi-memory

LOCAL_MEMORY_EMBEDDING_MODEL

Embedding 模型

BAAI/bge-small-zh-v1.5

LOCAL_MEMORY_DEFAULT_TOP_K

默认搜索条数

5

LOCAL_MEMORY_DEFAULT_DECAY_DAYS

短期记忆过期天数

30

License

MIT

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