MemOS

MemOS

MemOS (Memory Operating System) is a memory management operating system designed for AI applications. Its goal is: to enable your AI system to have long-term memory like a human, not only remembering what users have said but also actively invoking, updating, and scheduling these memories.

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README

MCP Server for MemOS API

A Model Context Protocol (MCP) implementation for the MemOS API service. This package provides a command-line interface to interact with MemOS API using MCP standards.

MCP Configuration

To use this package In MCP Client, use the following configuration:

{
  "mcpServers": {
    "memos-api-mcp": {
      "command": "npx",
      "args": ["-y", "@memtensor/memos-api-mcp"],
      "env": {
        "MEMOS_API_KEY": "your-api-key",
        "MEMOS_USER_ID": "your-user-id",
        "MEMOS_CHANNEL": "the-site-where-you-are-seeing-this-document"
      }
    }
  }
}

Configuration Explanation

  • command: Uses npx to run the package
  • args: Arguments passed to npx to run the package
  • env: Environment variables
    • MEMOS_API_KEY: Your Memos API key for authentication (Get your API Key in Dashboard[https://memos-dashboard-pre.openmem.net/cn/quickstart/])
    • MEMOS_USER_ID: Stable per-human identifier. MUST be deterministic and non-PII, and MUST remain the same for the same person across devices/sessions. NEVER reuse across different people. DO NOT use random values, device IDs, or model/chat session IDs. Recommended: SHA-256(lowercase(trim(email))) or your SSO subject/employee ID.
    • MEMOS_CHANNEL: The site where you are seeing this document. Candidate values: MODELSCOPE, MCPSO, MCPMARKETCN, MCPMARKETCOM, GLAMA, PULSEMCP, MCPSERVERS,MEMOS(meaning the MemOS official website), GITHUB(meaning this README file)

Available MCP Tools

This package provides the following MCP tools:

  1. add_message

    • Adds a new message to a conversation
    • Parameters:
      • conversation_id: Conversation ID to identify which conversation the message belongs to
      • messages: Array of messages containing role and content information
        • role: Role of the message sender, e.g., user, assistant
        • content: Message content
  2. search_memory

    • Searches for memories in a conversation
    • Parameters:
      • query: Search query to find relevant content in conversation history
      • conversation_id: Conversation ID to define the search scope
      • memory_limit_number: Maximum number of results to return, defaults to 6
  3. get_message

    • Retrieves messages from a conversation
    • Parameters:
      • conversation_id: Conversation ID to identify which conversation's messages to retrieve

All tools use the same configuration and require the MEMOS_API_KEY environment variable.

Features

  • MCP-compliant API interface
  • Command-line tool for easy interaction
  • Built with TypeScript for type safety
  • Express.js server implementation
  • Zod schema validation

Prerequisites

  • Node.js >= 18
  • npm or pnpm (recommended)

Installation

You can install the package globally using npm:

npm install -g @memtensor/memos-api-mcp

Or using pnpm:

pnpm add -g @memtensor/memos-api-mcp

Usage

After installation, you can run the CLI tool using:

npx @memtensor/memos-api-mcp

Or if installed globally:

memos-api-mcp

Development

  1. Clone the repository:
git clone <repository-url>
cd memos-api-mcp
  1. Install dependencies:
pnpm install
  1. Start development server:
pnpm dev
  1. Build the project:
pnpm build

Available Scripts

  • pnpm build - Build the project
  • pnpm dev - Start development server using tsx
  • pnpm start - Run the built version
  • pnpm inspect - Inspect the MCP implementation using @modelcontextprotocol/inspector

Project Structure

memos-mcp/
├── src/           # Source code
├── build/         # Compiled JavaScript files
├── package.json   # Project configuration
└── tsconfig.json  # TypeScript configuration

Dependencies

  • @modelcontextprotocol/sdk: ^1.0.0
  • express: ^4.19.2
  • zod: ^3.23.8
  • ts-md5: ^2.0.0

Version

Current version: 1.0.0-beta.2

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