What is Memos?
Memos is a lightweight, self‑hosted memo hub. It allows you to store short notes and snippets on your own server.
@RyoJerryYu
基本信息
A Python package enabling LLM models to interact with the Memos server via the MCP interface for searching, creating, retrieving, and managing memos.
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"mcp-server-memos-py": {
"command": "npx",
"args": [
"-y",
"@smithery/cli",
"install",
"@RyoJerryYu/mcp-server-memos-py",
"--client",
"claude"
]
}
}
}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。
点击上方按钮,在临时沙箱中运行此服务器并实时获取工具列表。
MCP Server Memos 📝 is a Python package that gives LLM models the ability to interact with a Memos server through the Model Context Protocol (MCP) interface. It is designed for developers building LLM-powered applications that need to search, create, and manage self‑hosted memo notes.
Install the package via pip install mcp-server-memos or automatically through Smithery. Configure it with a hostname, port, and access token, then add it to your MCP client’s configuration file (e.g., "mcpServers" in Claude Desktop). You can also run it directly from the command line: mcp-server-memos --host localhost --port 8080 --token YOUR_ACCESS_TOKEN.
Memos is a lightweight, self‑hosted memo hub. It allows you to store short notes and snippets on your own server.
You can install it via `pip install mcp-server-memos` or use Smithery’s CLI: `npx -y @smithery/cli install @RyoJerryYu/mcp-server-memos-py --client claude`.
You need to provide the hostname and port of your Memos server (defaults: `localhost` and `8080`) and an access token for authentication. These can be set as command‑line arguments or in a Python `Config` object.
It offers four tools: `list_memo_tags` (list tags), `search_memo` (search by keyword), `create_memo` (create a new memo with a chosen visibility), and `get_memo` (retrieve a memo by its ID).
Yes. It uses an access token passed via the `--token` parameter or `token` config field. The token is sent to the Memos server for every request.

Handl speaks the Model Context Protocol. Your whole billing operation — projects, invoices, clients, reports, approvals — as tools any AI assistant can call, inside your autonomy rules.
AI Agents & MCPs & AI Workflow Automation • (~400 MCP servers for AI agents) • AI Automation / AI Agent with MCPs • AI Workflows & AI Agents • MCPs for AI Agents
This open-source curriculum introduces the fundamentals of Model Context Protocol (MCP) through real-world, cross-language examples in .NET, Java, TypeScript, JavaScript, Rust and Python. Designed for developers, it focuses on practical techniques for building modular, scalable,
Open-source MCP to use Blender with any LLM
Painless E2E Automation for Mobile and Web
评论