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MCP-Mem0: Your Gateway to Long-Term Agent Memory

@yellnuts

代码仓库

基本信息

分类

AI 与智能体

许可证

MIT license

传输方式

stdio

作者

yellnuts

关于 MCP-Mem0: Your Gateway to Long-Term Agent Memory

MCP server for long term agent memory with Mem0. Also useful as a template to get you started building your own MCP server with Python!

#agent#database#memory#mcp#assistant#persistent-memory#memory-management#llm#llm-memory#mem0#mem0ai#mcp-server#modelcontextprotocol#model-context-protocol-servers

MCP-Mem0: Your Gateway to Long-Term Agent Memory 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "mcp-mem0-yellnuts": {
      "command": "python",
      "args": [
        "server.py"
      ]
    }
  }
}

MCP-Mem0: Your Gateway to Long-Term Agent Memory 工具

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。

概览

What is MCP-Mem0?

MCP-Mem0 is a Python-based server for managing long-term agent memory using Mem0. It also serves as a template for building custom MCP servers. It targets developers who need persistent memory storage for AI agents.

How to use MCP-Mem0?

Clone the repository, install dependencies with pip install -r requirements.txt, and run python server.py. The server starts on http://localhost:5000 and exposes HTTP endpoints for creating, retrieving, and deleting memories. Configuration can be adjusted in config.json.

Key features of MCP-Mem0

  • Long-term memory storage and retrieval for agents
  • Python‑based, easy to customize and extend
  • Lightweight with minimal resource requirements
  • Serves as a template for building new MCP servers
  • Configurable memory expiry, logging, and port

Use cases of MCP-Mem0

  • Persist conversation history for conversational AI agents
  • Maintain context across sessions in multi‑turn agent applications
  • Serve as a foundation for prototyping custom MCP servers
  • Experiment with memory management in research projects

常见问题

1

What does MCP-Mem0 do?

It provides a server that stores and retrieves long‑term memories for agents via HTTP requests, using the Mem0 system.

2

What are the system requirements?

Python 3.6 or higher and the packages listed in `requirements.txt`. No other runtime dependencies are specified.

3

How do I start the server?

After installing dependencies, run `python server.py` from the repository root. The server will listen on port 5000 by default.

4

What API endpoints are available?

Three main endpoints: `POST /memory` to create a memory, `GET /memory/{agent_id}` to retrieve it, and `DELETE /memory/{agent_id}` to delete it.

5

Can I configure memory expiry?

Yes. Edit the `config.json` file in the root directory to set parameters like `memory_expiry`, `logging_level`, and `port`.

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