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Memos

@MemTensor

Repository

About Memos

No overview available yet

#memos#memory-os#ai-agents

Config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "memos-api-mcp": {
      "timeout": 60,
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@memtensor/memos-api-mcp"
      ],
      "env": {
        "MEMOS_API_KEY": "<YOUR-TOKEN>",
        "MEMOS_USER_ID": "<YOUR-USER-ID>"
      }
    }
  }
}

Tools

No tools detected

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

What is MemOS?

MemOS is an open-source Agent Memory framework that equips AI agents with long-term memory, personality consistency, and contextual recall across sessions. It provides a unified API for memory representation, retrieval, and update, and is designed for AI companions, role-playing NPCs, and multi-agent systems.

How to use MemOS?

You can use MemOS via the free online API (sign up on the MemOS dashboard), by self-hosting a server with git clone and uvicorn memos.api.server_api:app, or by installing the local SDK with pip install MemoryOS. Example code demonstrates creating a MemCube or using the higher-level MOS orchestrator to store and retrieve memories for a user.

Key features of MemOS?

  • Memory-Augmented Generation (MAG) unified API
  • Modular MemCube architecture with multiple memory types
  • Textual, activation (KV cache), and parametric memory
  • Extensible with custom modules and data sources
  • Millisecond-level async memory addition (v1.1.3)

Use cases of MemOS?

  • AI companions that remember past conversations and user preferences

Comments

Basic information

Category

Other

Transports

stdio

Author

MemTensor

Submitted by

Wenqiang Wei

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