genpark-meta-muse-multimodal-episodic-resonance-mcp
Health Uyari
- License — License: NOASSERTION
- Description — Repository has a description
- Active repo — Last push 0 days ago
- Low visibility — Only 7 GitHub stars
Code Gecti
- Code scan — Scanned 4 files during light audit, no dangerous patterns found
Permissions Gecti
- Permissions — No dangerous permissions requested
Bu listing icin henuz AI raporu yok.
Multimodal sensory grounding (Meta Ray-Ban audio/vision) integrated with long-term episodic life memory graphs and empathetic emotional resonance (Muse).
genpark-meta-muse-multimodal-episodic-resonance-mcp
Production-Grade Personal AI Agent Infrastructure Skill • 100% Standard Library Python • Native Model Context Protocol (MCP)
📌 Overview & Capability
genpark-meta-muse-multimodal-episodic-resonance-mcp is a deterministic, high-performance, zero-dependency Python tool and native Model Context Protocol (MCP) server engineered for next-generation personal AI agents (distilling breakthrough capabilities from Today AI, Manus, Cue, Meta, Muse, and Instinct).
Executive Capability: Multimodal sensory grounding (Meta Ray-Ban audio/vision) integrated with long-term episodic life memory graphs and empathetic emotional resonance (Muse).
⚡ Key Highlights
- 🐍 Zero External
pipDependencies: Implemented entirely with pure Python standard library for instant zero-overhead execution. - 🔌 Native Model Context Protocol (MCP): Plugs directly into any MCP-compliant client via JSON-RPC 2.0 stdio.
- 🧠 Personal Agent Cognitive Architecture: Fast subconscious intent reflexes, ambient screen/clipboard cues, episodic life memory, and deep autonomous task resolution.
- 🛡️ Production-Hardened: Comprehensive error handling, boundary validation, and telemetry.
🏗️ Architecture
graph LR
User([👤 User / Ambient Environment]) -->|Sensory Signals & Goals| Core[⚡ genpark-meta-muse-multimodal-episodic-resonance-mcp Engine]
Core --> Memory[(🧠 Episodic & Context Graph)]
Core --> Executor[🤖 Autonomous Action Pipeline]
Executor --> Result[📊 Proactive Action & Telemetry]
Result --> User
🚀 Quickstart & Usage
1. Direct Python Client Execution
python example_usage.py
2. Programmatic Integration
from client import MetaMuseEpisodicResonance
client = MetaMuseEpisodicResonance()
result = client.run_meta_muse_benchmark()
print(result)
🔌 Model Context Protocol (MCP) Setup
Connect this skill to Claude Desktop, Cursor, or any MCP-compliant client:
claude_desktop_config.json
{
"mcpServers": {
"genpark-meta-muse-multimodal-episodic-resonance-mcp": {
"command": "python",
"args": ["/path/to/genpark-meta-muse-multimodal-episodic-resonance-mcp/mcp_server.py"]
}
}
}
Direct MCP Testing
python mcp_server.py --test
📊 Technical Specifications
| Parameter | Type | Required | Description |
|---|---|---|---|
payload |
string / dict |
Yes | Sensory inputs, task goals, or ambient telemetry |
options |
dict |
No | Cognitive depth, energy profiles, or execution timeouts |
Yorumlar (0)
Yorum birakmak icin giris yap.
Yorum birakSonuc bulunamadi