GenParkEmbodiedTrajectoryQuinticSplineSmoother
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@GenParkEmbodiedTrajectoryQuinticSplineSmoothersmooth trajectory through (0,0), (5,3), (10,0) with zero start/end velocity"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
genpark-embodied-trajectory-quintic-spline-smoother-skill
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["GenParkEmbodiedTrajectoryQuinticSplineSmoother"]
Core --> Kinematics[Robotics Dynamics & Spatial Engine]
Kinematics --> Safety[Boundary & Collision Guardrails]
Safety --> MCPOutput[Standard MCP Tool Result / Control Vector]Related MCP server: GenParkEmbodiedSpatial3DOccupancyGridSolver
Quickstart & Usage
1. Direct Python Client Execution
python example_usage.py2. Standalone MCP Server Launch
Run the native STDIO MCP server:
python mcp_server.pyLicense
This project is licensed under the MIT License - see the LICENSE file for details.
This server cannot be deployed
Maintenance
Related MCP Connectors
Control plane for autonomous software labor. Agents claim objectives over MCP with audit trail.
Deterministic MCP solver for real equation systems (<=6 vars), Krawczyk-certified.
- DazbenchOAuthapp.dazbench
Task management your AI agents can actually run. One line becomes a context-ready task over MCP.
Built-environment forecasts, public benchmarks, and permit or zoning readiness through remote MCP.
Related MCP Servers
- AlicenseNot gradedqualityDmaintenanceWorld-first unified MCP gateway + Control Barrier Function (CBF-QP) safety engine for agentic robotics, enabling LLMs to control physical robots with mathematically proven safety.MIT
- AlicenseNot gradedqualityBmaintenanceEnables autonomous robotic systems to perform real-time 3D occupancy voxel mapping, raycast-based Bayesian occupancy updates, and sphere collision checking through standard MCP tools.7MIT
- AlicenseNot gradedqualityBmaintenanceEnables autonomous robotic systems to generate and smooth trajectories with continuous position, velocity, and acceleration boundary constraints, analytic jerk minimization, spatial intelligence, and tactile control through MCP tools.7MIT
- AlicenseNot gradedqualityBmaintenanceEnables real-time spatial intelligence, trajectory generation, and tactile control for autonomous robotic systems via MCP, including Coulomb friction cone checking, contact normal alignment, and grasp wrench quality evaluation.7MIT