F
licenseNot graded
qualityB
maintenanceEnables AI agents to maintain persistent personal memory and portable skills across MCP-compliant clients, with hybrid semantic recall and deterministic SQL analytics.
-
genpark-personal-agent-unified-autonomous-copilot-skill
Officialby alphaparkinc
This server does not currently have a deployable release on Glama. Follow the repository's setup instructions to install and configure it for your MCP client, including any required credentials and local dependencies.
genpark-personal-agent-unified-autonomous-copilot-skill
๐ GenPark MCP Hub โข ๐ฆ GenPark Official โข ๐ Documentation
๐ Overview & Capability
genpark-personal-agent-unified-autonomous-copilot-skill 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: Master cognitive personal copilot integrating Today AI (agenda), Manus (autonomous sandbox), Cue (ambient cues), Instinct (fast reflex), and Muse (episodic memory).
โก Key Highlights
๐ Zero External
pipDependencies: Implemented entirely with pure Python standard library for instant zero-overhead execution.๐ Native Model Context Protocol (MCP): Plugs directly into any MCP-compliant client via JSON-RPC 2.0 stdio.
๐ง Personal Agent Cognitive Architecture: Fast subconscious intent reflexes, ambient screen/clipboard cues, episodic life memory, and deep autonomous task resolution.
๐ก๏ธ Production-Hardened: Comprehensive error handling, boundary validation, and telemetry.
Related MCP server: pasm-mcp-server
๐๏ธ Architecture
graph LR
User([๐ค User / Ambient Environment]) -->|Sensory Signals & Goals| Core[โก genpark-personal-agent-unified-autonomous-copilot-skill Engine]
Core --> Memory[(๐ง Episodic & Context Graph)]
Core --> Executor[๐ค Autonomous Action Pipeline]
Executor --> Result[๐ Proactive Action & Telemetry]
Result --> User๐ Quickstart & Usage
1. Direct Python Client Execution
python example_usage.py2. Programmatic Integration
from client import PersonalAgentUnifiedCopilot
client = PersonalAgentUnifiedCopilot()
result = client.run_unified_copilot_benchmark()
print(result)๐ Model Context Protocol (MCP) Setup
Connect this skill to Claude Desktop, Cursor, or any MCP-compliant client:
claude_desktop_config.json
{
"mcpServers": {
"genpark-personal-agent-unified-autonomous-copilot-skill": {
"command": "python",
"args": ["/path/to/genpark-personal-agent-unified-autonomous-copilot-skill/mcp_server.py"]
}
}
}Direct MCP Testing
python mcp_server.py --test๐ Technical Specifications
Parameter | Type | Required | Description |
|
| Yes | Sensory inputs, task goals, or ambient telemetry |
|
| No | Cognitive depth, energy profiles, or execution timeouts |
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