Memos Py

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A Python package enabling LLM models to interact with the Memos server via the MCP interface for searching, creating, retrieving, and managing memos.

by RyoJerryYu

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A Python package enabling LLM models to interact with the Memos server via the MCP interface for searching, creating, retrieving, and managing memos.

README

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MCP Server Memos 📝

PyPI version Python Version License smithery badge

A Python package that provides LLM models with the ability to interact with Memos server through the MCP (Model Context Protocol) interface.

🚀 Features

🔍 Search memos with keywords
✨ Create new memos with customizable visibility
📖 Retrieve memo content by ID
🏷️ List and manage memo tags
🔐 Secure authentication using access tokens

🛠️ Usage

You can include this package in your config file as bellow, just as you use other Python MCP plugins.

{
  ...,
  "mcpServers": {
    "fetch": { // other mcp servers
      "command": "uvx",
      "args": ["mcp-server-fetch"]
    },
    "memos": { // add this to your config
      "command": "uvx",
      "args": [
        "--prerelease=allow",
        "mcp-server-memos",
        "--host",
        "localhost",
        "--port",
        "5230",
        "--token",
        "your-access-token-here"
      ]
    }
  }
}

Other ways to use this package

📦 Installation

Installing via Smithery

To install mcp-server-memos-py for Claude Desktop automatically via Smithery:

npx -y @smithery/cli install @RyoJerryYu/mcp-server-memos-py --client claude

Installing Manually

pip install mcp-server-memos

Command Line

mcp-server-memos --host localhost --port 8080 --token YOUR_ACCESS_TOKEN

As a Library

from mcp_server_memos import Config, serve_stdio

config = Config(
    host="localhost",
    port=8080,
    token="YOUR_ACCESS_TOKEN"
)

await serve_stdio(config=config)

🔧 Configuration

Parameter	Description	Default
`host`	Memos server hostname	`localhost`
`port`	Memos server port	`8080`
`token`	Access token for authentication	`""`

🤝 Available Tools

This MCP server provides the following tools for interacting with Memos:

Tool Name	Description	Parameters
`list_memo_tags`	List all existing memo tags	- `parent`: The parent who owns the tags (format: memos/{id}, default: "memos/-") - `visibility`: Tag visibility (PUBLIC/PROTECTED/PRIVATE, default: PRIVATE)
`search_memo`	Search for memos using keywords	- `key_word`: The keywords to search for in memo content
`create_memo`	Create a new memo	- `content`: The content of the memo - `visibility`: Memo visibility (PUBLIC/PROTECTED/PRIVATE, default: PRIVATE)
`get_memo`	Get a specific memo by ID	- `name`: The name/ID of the memo (format: memos/{id})

🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

🙏 Acknowledgments

Memos - A lightweight, self-hosted memo hub
MCP (Model Context Protocol) - Protocol for LLM model applications

from github.com/RyoJerryYu/mcp-server-memos-py

Installing Memos Py

This server has no published package — it is built from source. Open the repository and follow its README.

▸ github.com/RyoJerryYu/mcp-server-memos-py

FAQ

Is Memos Py MCP free?

Yes, Memos Py MCP is free — one-click install via Unyly at no cost.

Does Memos Py need an API key?

No, Memos Py runs without API keys or environment variables.

Is Memos Py hosted or self-hosted?

Self-hosted: the server runs locally on your machine via the install command above.

How do I install Memos Py in Claude Desktop, Claude Code or Cursor?

Open Memos Py on unyly.org, pick your client tab (Claude Desktop, Claude Code, Cursor) and press Install — the config is generated automatically, no JSON editing.

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