How do I use GenParkEmbodiedSpatial3DOccupancyGridSolver?

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.

GenParkEmbodiedSpatial3DOccupancyGridSolver

Official

by alphaparkinc

Overview Schema Source Related Servers Discussions Admin

Python

Local

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

Organization Model Context Protocol Zero-Dependency Python Version 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).

Architecture & Data Flow

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]

Quickstart & Usage

1. Direct Python Client Execution

python example_usage.py

2. Standalone MCP Server Launch

Run the native STDIO MCP server:

python mcp_server.py

License

This project is licensed under the MIT License - see the LICENSE file for details.

This server cannot be deployed

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