TeamSafeAI/LIFE

Overview

LIFE is a persistent identity architecture for AI agents, implemented as 16 MCP servers covering drives, heart, memory, patterns, journal, genesis, garden, vision, voice, and more. It runs with zero dependencies and was built across 938 conversations.

Best for

Best for
Developers building persistent, identity-driven AI agents in Python

Use cases

• Give an AI agent a persistent memory and identity across sessions
• Build modular agent subsystems using separate MCP servers
• Experiment with long-running agent architectures in Python

How to use

Install

pip install -r requirements.txt && python setup.py

Tools exposed

• CORE/semantic/embedding_service.py

Example client config

{\n  "servers": [\n    {\n      "name": "LIFE",\n      "args": ["/path/to/your/LIFE/CORE/drives/server.py"],\n      "transport": "stdio"\n    }\n  ]\n}

Notes

LIFE is a persistent identity architecture for AI agents, implemented as 16 MCP servers covering drives, heart, memory, patterns, journal, genesis, garden, vision, voice, and more. It runs with zero dependencies and was built across 938 conversations.

5 stars on GitHub. Last updated 2026-02-16. Licensed MIT.

Use cases

• Give an AI agent a persistent memory and identity across sessions
• Build modular agent subsystems using separate MCP servers
• Experiment with long-running agent architectures in Python

Pros

• Zero dependencies simplifies deployment and reduces conflicts
• Modular MCP server design allows selective use of components
• Built from extensive real-world conversation data

Cons

• Limited documentation or community support outside the original conversations
• 16 servers may be overkill for simple agent tasks
• Python-only limits integration with non-Python stacks

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.