Memos
@MemTensor
About Memos
No overview available yet
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
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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
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