# genpark-embodied-spatial-3d-occupancy-grid-solver-skill

[![Organization](https://img.shields.io/badge/AlphaPark-OpenSource-blue.svg)](https://github.com/alphaparkinc)
[![Model Context Protocol](https://img.shields.io/badge/MCP-Standard-orange.svg)](https://modelcontextprotocol.io)
[![Zero-Dependency](https://img.shields.io/badge/Dependencies-Zero_External-brightgreen.svg)](#)
[![Python Version](https://img.shields.io/badge/Python-3.9%2B-blue.svg)](#)
[![License](https://img.shields.io/badge/License-MIT-green.svg)](LICENSE)

Production-grade Physical AI & Robotics skill engineered strictly with Python standard library. Provides real-time spatial intelligence, trajectory generation, and tactile control for autonomous robotic systems via the Model Context Protocol (MCP).

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## Architecture & Data Flow

```mermaid
flowchart TD
    Sensor[3D Depth Sensors / Joint Encoders / Tactile Array] --> Ingest[Telemetry Normalizer]
    Ingest --> Core["GenParkEmbodiedSpatial3DOccupancyGridSolver"]
    Core --> Kinematics[Robotics Dynamics & Spatial Engine]
    Kinematics --> Safety[Boundary & Collision Guardrails]
    Safety --> MCPOutput[Standard MCP Tool Result / Control Vector]
```

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## Quickstart & Usage

### 1. Direct Python Client Execution
```bash
python example_usage.py
```

### 2. Standalone MCP Server Launch
Run the native STDIO MCP server:
```bash
python mcp_server.py
```

---

## License

This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.