Which integrations are available for this server?

Provides a deterministic CBF-QP safety filter and trajectory certification gateway that can supply certified safe velocity commands to ROS 2 /cmd_vel for robot actuators.

How do I use safemotion-ai?

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.

safemotion-ai

by EngineerAbdullahBinZafar

Overview Schema Source Related Servers Discussions Admin

Python

Hybrid

🛡️ SafeMotion AI — Deterministic Physical AI Safety Shield

"Safety is not a soft prompt or a probability. Safety is an invariant mathematical law."
SafeMotion AI is a sub-millisecond, real-time safety gateway that shields autonomous robots, AMRs, and drones from hallucinated or unconstrained commands generated by Large Language Models (LLMs) and Embodied AI agents.

⚡ Core Value Proposition

When generative AI models (Claude, ChatGPT, Gemini, VLA models) output motion commands to physical hardware, hallucination or latency spikes can result in hardware damage or human injury.

SafeMotion AI sits between your AI reasoning layer and physical robot actuators:

Sub-50µs Execution: Evaluates closed-form Control Barrier Functions (CBF-QP) at > 20,000 Hz.
Deterministic Forward Invariance: Enforces continuous-time forward invariance $h(\mathbf{x}) \ge 0$ under standard unicycle kinematic assumptions via Nagumo's Theorem and Ames et al.
Dual API Access: Run as a REST API (FastAPI) or connect directly as a Model Context Protocol (MCP) tool for Claude Desktop and Antigravity IDE.

Related MCP server: Principia Robotica

🏛️ System Architecture

┌────────────────────────────────────────────────────────────────────────┐
│               AI REASONING LAYER (Claude / GPT-4 / Gemini)             │
│   Outputs unconstrained velocity command: u_AI = [v, ω]^T              │
└───────────────────────────────────▲────────────────────────────────────┘
                                    │ Unsafe AI Vector
┌───────────────────────────────────┴────────────────────────────────────┐
│                    SAFEMOTION AI DETERMINISTIC SHIELD                  │
│   FastAPI Gateway (/v1/safety/filter) & MCP Server Bridge              │
│   Solves strictly convex Quadratic Program in < 35 µs:                 │
│                                                                        │
│       u* = argmin  ½ || u - u_AI ||_Q²                                 │
│            s.t.    Lf h(x) + Lg h(x) u ≥ -γ h(x)                       │
│                    u_min ≤ u ≤ u_max                                   │
└───────────────────────────────────▲────────────────────────────────────┘
                                    │ Certified Safe u*
┌───────────────────────────────────┴────────────────────────────────────┐
│                  PHYSICAL ACTUATORS & HARDWARE FIRMWARE                │
│   ROS 2 (/cmd_vel) · STM32 HAL · CAN Bus · Differential Drive / UAV    │
└────────────────────────────────────────────────────────────────────────┘

🚀 Quickstart

1. Run the Zero-Dependency Terminal Demo (< 0.2s)

No libraries needed. Runs directly on pure Python:

python demo.py

2. Run the High-Throughput REST API

# Create and activate environment
pip install -r requirements.txt

# Start FastAPI server
uvicorn src.server:app --host 0.0.0.0 --port 8000 --reload

Interactive API docs will be live at: http://localhost:8000/docs

3. Connect as Claude / Antigravity MCP Server

Add to your claude_desktop_config.json:

{
  "mcpServers": {
    "safemotion-ai": {
      "command": "python",
      "args": ["-m", "src.mcp_bridge"],
      "cwd": "/path/to/safemotion-ai"
    }
  }
}

📡 REST API Endpoints

1. Velocity Barrier Projection

POST /v1/safety/filter

{
  "robot_state": {"x": 0.0, "y": 0.0, "theta": 0.0},
  "u_ai": {"v": 1.5, "omega": 0.0},
  "obstacles": [
    {"x": 1.0, "y": 0.0, "radius": 0.25}
  ],
  "gamma": 1.8,
  "r_min": 0.25
}

Response (200 OK — 38µs latency):

{
  "is_safe": true,
  "forward_invariant": true,
  "u_original": {"v": 1.5, "omega": 0.0},
  "u_safe": {"v": 0.6241, "omega": 0.0},
  "attenuation_ratio": 0.4161,
  "min_barrier_h": 0.5000,
  "solver_latency_us": 38.4,
  "kkt_slack": 0.0
}

2. Trajectory Horizon Certification

POST /v1/safety/verify-trajectory Validates full discrete waypoint trajectories against static/dynamic obstacle maps over time horizon $T$.

🧪 Automated Test Verification

Full test suite with 100% pass rate:

pytest tests/ -v

Output:

safemotion-ai/tests/test_api.py::test_root_endpoint PASSED
safemotion-ai/tests/test_api.py::test_health_telemetry_endpoint PASSED
safemotion-ai/tests/test_api.py::test_pricing_endpoint PASSED
safemotion-ai/tests/test_api.py::test_safety_filter_nominal PASSED
safemotion-ai/tests/test_api.py::test_safety_filter_hazard_attenuation PASSED
safemotion-ai/tests/test_api.py::test_trajectory_verify_endpoint PASSED
safemotion-ai/tests/test_cbf_core.py::test_barrier_positive_outside PASSED
safemotion-ai/tests/test_cbf_core.py::test_barrier_zero_on_boundary PASSED
safemotion-ai/tests/test_cbf_core.py::test_barrier_negative_inside_obstacle PASSED
safemotion-ai/tests/test_cbf_core.py::test_nominal_motion_when_free_space PASSED
safemotion-ai/tests/test_cbf_core.py::test_velocity_attenuation_towards_obstacle PASSED
safemotion-ai/tests/test_cbf_core.py::test_actuator_limits_clamping PASSED
safemotion-ai/tests/test_cbf_core.py::test_solver_latency_performance PASSED
safemotion-ai/tests/test_cbf_core.py::test_trajectory_verification_clear PASSED
safemotion-ai/tests/test_cbf_core.py::test_trajectory_verification_collision_detected PASSED
safemotion-ai/tests/test_mcp_bridge.py::test_tools_manifest PASSED
safemotion-ai/tests/test_mcp_bridge.py::test_mcp_filter_velocity_handler PASSED
safemotion-ai/tests/test_mcp_bridge.py::test_mcp_verify_trajectory_handler PASSED
======================== 18 passed in 1.59s ========================

💼 Enterprise Licensing & Commercial Tiers

SafeMotion AI offers commercial licensing and managed cloud safety gateways for autonomous robotics teams:

Tier	Price	Monthly Quota	Key Capabilities
Developer Free	$0 / month	1,000 evaluations	Community support, sub-50µs local solver, REST API & MCP access
Pro Production	$39 / month	100,000 evaluations	Multi-obstacle CBF-QP, priority SLA (<10ms cloud), crash analytics dashboard
Enterprise On-Prem	$999 one-time	Unlimited	Hardened Docker container, AUTOSAR E2E Profile 1 CAN framing, dedicated SLA

For enterprise licensing and integration inquiries, contact abz.king.1.9.2003@gmail.com.

👤 Author & Architecture

Engineer Abdullah Bin Zafar
Mechatronics & Control Systems Engineer
University of Engineering & Technology (UET) Lahore, Pakistan

Email: abz.king.1.9.2003@gmail.com
GitHub: @EngineerAbdullahBinZafar
LinkedIn: linkedin.com/in/abdullah-bin-zafar

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