What is Openmemory Mcp

OpenMemory-MCP is a personal memory layer for large language models that is private, portable, and open-source. It allows users to store their memories locally, providing complete control over their data while enabling the development of AI applications with personalized memory.

Use cases

Use cases for OpenMemory-MCP include building customized AI chatbots, personal assistants that remember user preferences, educational tools that adapt to individual learning styles, and any application that benefits from a personalized memory layer.

How to use

To use OpenMemory-MCP, clone the repository from GitHub, configure the necessary environment variables in the ‘docker-compose.yml’ file, and ensure that Docker and Docker Compose are installed on your system. After setting up, you can deploy the service and start using it.

Key features

Key features of OpenMemory-MCP include local memory storage for data privacy, support for multiple AI models (such as OpenAI, Anthropic, and others), easy deployment with Docker Compose, and the ability to create personalized AI applications.

Where to use

OpenMemory-MCP can be used in various fields including AI development, personalized applications, data privacy solutions, and any scenario where users require control over their AI interactions and memory.

OpenMemory

OpenMemory 是您的个人记忆层，用于大语言模型 - 私有、便携且开源。您的记忆存储在本地，为您提供对数据的完全控制。构建具有个性化记忆的人工智能应用程序，同时保持数据安全。

在 原项目 的基础上，我们做了以下修改：

• 去掉 make 统一使用 docker-compose.yml 管理配置，方便部署到云服务器。
• 修复在 Windows 部署中时 UI 无法访问的问题。

支持的模型：

• OpenAI、Azure OpenAI 以及其他 OpenAI 兼容的代理
• Anthropic
• Ollama
• Together
• Groq
• Litellm
• Mistral AI
• Google AI、Gemini
• DeepSeek
• xAI
• LM Studio
• LangChain

前提条件

在开始之前，请确保你的系统已安装以下软件，支持Windows、MacOS 和 Linux：

• Docker: 安装指南
• Docker Compose: 安装指南

1. 克隆仓库

首先，将项目代码克隆到你的本地机器：

git clone https://github.com/osen77/OpenMemory-MCP.git
cd OpenMemory-MCP

2. 配置环境变量

你需要为后端服务配置 API 密钥和其他必要的环境变量。这些变量直接在 docker-compose.yml 文件中定义。

打开 docker-compose.yml 文件，找到 openmemory-mcp 服务下的 environment 部分，并根据你的需求进行修改：

services:
  openmemory-mcp:
    # ...
    environment:
      - USER=USER  # 设置默认用户 ID
      - API_KEY=sk-xx # <-- **请将此处替换为你的真实 API 密钥**
      - OPENAI_BASE_URL=https://xxx # 替换 OpenAI 兼容的代理，删除则使用默认 OpenAI
    # ...
  openmemory-ui:
    # ...
    environment:
      - NEXT_PUBLIC_API_URL=http://localhost:8765 # 前端访问后端的地址,如果部署到服务器上,请修改为服务器的地址或域名
      - NEXT_PUBLIC_USER_ID=USER # 前端使用的用户 ID
    # ...

重要提示：

• USER/NEXT_PUBLIC_USER_ID: 确保前后端的 USER 和 NEXT_PUBLIC_USER_ID 保持一致。

3. 构建并运行服务

配置完成后，使用 Docker Compose 构建并启动所有服务：

docker compose up --build -d

• --build: 首次运行或代码更改后，此选项强制重新构建镜像。
• -d: 在后台运行所有服务，释放你的终端。

首次构建可能需要一些时间，因为 Docker Compose 会下载基础镜像、安装依赖并构建应用程序镜像。

4. 访问应用程序

一旦所有服务成功启动，你可以通过以下地址访问应用程序：

• OpenMemory UI (前端): http://localhost:3000
• OpenMemory API (后端): http://localhost:8765/docs
• OpenMemory MCP: http://localhost:8765/mcp/openmemory/sse/{USER} 替换USER为设置的ID
• Qdrant 向量数据库: http://localhost:6333/dashboard

5. 清理

要停止并移除所有 Docker 容器、网络和卷：

docker compose down -v

-v 选项将同时移除 Qdrant 持久化数据卷，慎用。如果只想停止服务而不删除数据，请使用 docker compose down。

Project Structure

• api/ - Backend APIs + MCP server
• ui/ - Frontend React application

Contributing

We are a team of developers passionate about the future of AI and open-source software. With years of experience in both fields, we believe in the power of community-driven development and are excited to build tools that make AI more accessible and personalized.

We welcome all forms of contributions:

• Bug reports and feature requests
• Documentation improvements
• Code contributions
• Testing and feedback
• Community support

How to contribute:

1. Fork the repository
2. Create your feature branch (git checkout -b openmemory/feature/amazing-feature)
3. Commit your changes (git commit -m 'Add some amazing feature')
4. Push to the branch (git push origin openmemory/feature/amazing-feature)
5. Open a Pull Request

Join us in building the future of AI memory management! Your contributions help make OpenMemory better for everyone.