Memphora MCP Server
Add persistent memory to Claude, Cursor, Windsurf, and other AI assistants using the Model Context Protocol (MCP).
这是什么?
此MCP服务器将您的AI助手连接到 孟波拉,使其能够:
- 记住 对话中的信息
- 搜索 你的个人知识库
- 提取 自动从对话中获得见解
- 召回 你的偏好、事实和背景
快速开始
1.安装
# Using pip
pip install memphora-mcp
# Or using uvx (recommended for Claude Desktop)
uvx memphora-mcp2.获取API密钥
- 首选 memphora.ai/仪表板
- 创建帐户或登录
- 从仪表板复制API密钥
3.配置克劳德桌面
添加到您的Claude Desktop配置文件中:
macOS: ~/Library/Application Support/Claude/claude_desktop_config.json 窗户: %APPDATA%\Claude\claude_desktop_config.json
{
"mcpServers": {
"memphora": {
"command": "uvx",
"args": ["memphora-mcp"],
"env": {
"MEMPHORA_API_KEY": "your_api_key_here",
"MEMPHORA_USER_ID": "your_unique_user_id"
}
}
}
}4.重新启动克劳德桌面
关闭并重新打开Claude Desktop。你应该看到Memphora工具可用!
使用示例
存储记忆
告诉克劳德一些关于你自己的事情:
You: "I work at Google as a software engineer"
Claude: [stores memory] "Got it! I'll remember that you work at Google as a software engineer."
You: "My favorite programming language is Python"
Claude: [stores memory] "Noted! I'll remember that Python is your favorite programming language."回忆往事
问克劳德你以前告诉过它的事情:
You: "Where do I work?"
Claude: [searches memories] "You work at Google as a software engineer."
You: "What programming languages do I like?"
Claude: [searches memories] "Your favorite programming language is Python."自动上下文
克劳德会在相关时自动搜索您的记忆:
You: "Can you help me with some code?"
Claude: [searches memories for context]
"Sure! Since you prefer Python and work at Google, I'll write this in Python
following Google's style guide..."可用工具
| 工具 | 说明 |
|---|---|
memphora_search | 在记忆中搜索相关信息 |
memphora_store | 存储新信息以备将来召回 |
memphora_extract_conversation | 从对话中提取记忆 |
memphora_list_memories | 列出所有存储的内存 |
memphora_delete | 删除特定内存 |
配置选项
| 环境变量 | 描述 | 默认值 |
|---|---|---|
MEMPHORA_API_KEY | 您的Memphora API密钥 | 必需 |
MEMPHORA_USER_ID | 您记忆的唯一标识符 | mcp_default_user |
与其他MCP客户端一起使用
光标
添加到光标设置中:
{
"mcp": {
"servers": {
"memphora": {
"command": "uvx",
"args": ["memphora-mcp"],
"env": {
"MEMPHORA_API_KEY": "your_api_key_here"
}
}
}
}
}帆板运动
添加到您的Windsurf MCP配置中:
{
"mcpServers": {
"memphora": {
"command": "python",
"args": ["-m", "memphora_mcp"],
"env": {
"MEMPHORA_API_KEY": "your_api_key_here"
}
}
}
}发展
本地运行
# Clone the repo
git clone https://github.com/Memphora/memphora-mcp.git
cd memphora-mcp
# Install dependencies
pip install -e ".[dev]"
# Set your API key
export MEMPHORA_API_KEY="your_key"
# Run the server
python -m memphora_mcp测试
pytest tests/隐私和安全
- 您的记忆安全地存储在Memphora的云中
- 每个用户都有独立的内存存储
- API密钥存储在本地计算机上
- 所有通信均通过HTTPS加密
支持
- 文档: memphora.ai/docs
- 问题:
- 电子邮件:support@memphora.ai
许可证
MIT许可证-请参阅 许可证 了解详情。
