@ryaker
基本信息
OpenAI just added memory across your chats across your openAI account. But wouldn't it be awesome to have general AI memory across all your interactions with any and all AI tools, IDEs, chatbots.... Now if it supports MCP you can with https://mem0.ai/ Give Claude desktop memory.
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"mem0-memory-general": {
"command": "<PATH TO SERVER>/mcp-mem0-server",
"args": [],
"env": {
"MEM0_API_KEY": "<YOUR MEM0 KEY>"
}
}
}
}工具列表暂未提供
当前收录暂时没有可展示的工具列表，不代表服务没有工具。请查阅项目文档了解支持的能力。
工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。
Mem0 General is a Model Context Protocol (MCP) server that bridges AI assistants with Mem0.ai’s persistent memory system. It enables compatible AI models to store, retrieve, search, and manage memories across short-term and long-term types, including knowledge graphs.
Install the package with pip install mcp-mem0-server, then add a configuration entry to your MCP config file (e.g., ~/.cursor/mcp.json) that sets the MEM0_API_KEY environment variable and runs the command mcp-mem0-server. After restarting the client application (Cursor or Claude Desktop), the server tools are available.
Run `pip install mcp-mem0-server`. Then add a configuration entry in your MCP config file (e.g., `~/.cursor/mcp.json`) that uses `"command": "mcp-mem0-server"` and includes the environment variable `MEM0_API_KEY` set to your Mem0 API key.
Short-term memories: conversation memory, working memory, and attention memory. Long-term memories: episodic memory, semantic memory, and procedural memory.
All memories in the system use `"default_user"` as the default user_id unless overridden.
Custom memory categories, memory processing instructions, knowledge graph relations between entities, selective memory filtering, and a feedback mechanism for memory quality.
Memories are stored and managed by Mem0.ai’s cloud memory system; the server acts as a client to that API using your Mem0 API key.
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