semvec/pypi-packages huggingface dataset:
scicomp-quantum-mcp 0.1.6
MCP server for wave mechanics and Schrodinger equation simulations
Requires Python: >=3.11
Keywords: gpu, mcp, model-context-protocol, physics, quantum, schrodinger, wavefunction

# scicomp-quantum-mcp

mcp-name: io.github.andylbrummer/quantum-mcp

MCP server for wave mechanics and Schrödinger equation simulations.

## Overview

This server provides tools for quantum mechanics simulations and wavefunction analysis:

- **Schrödinger solver** - Time-dependent wave equation simulations in 1D and 2D
- **Potential creation** - Crystalline lattices, custom potentials, harmonic oscillators
- **Wavefunction analysis** - Observable computation, probability density, energy analysis
- **Wave packets** - Gaussian wave packet creation and evolution
- **GPU acceleration** - Optional CUDA acceleration for large simulations

## Installation & Usage

```bash
# Run directly with uvx (no installation required)
uvx scicomp-quantum-mcp

# Or install with pip
pip install scicomp-quantum-mcp

# With GPU support
pip install scicomp-quantum-mcp[gpu]

# Run as command
scicomp-quantum-mcp
```

## Available Tools

### Potential Creation
- `create_lattice_potential` - Crystalline lattice potentials (square, hexagonal, triangular)
- `create_custom_potential` - Custom potential from mathematical function
- `create_gaussian_wavepacket` - Localized Gaussian wave packets
- `create_plane_wave` - Plane wave states

### Simulation
- `solve_schrodinger` - 1D time-dependent Schrödinger equation
- `solve_schrodinger_2d` - 2D time-dependent Schrödinger equation
- `get_task_status` - Monitor async simulations
- `get_simulation_result` - Retrieve completed simulation data

### Analysis
- `analyze_wavefunction` - Compute observables from wavefunction
- `visualize_potential` - Plot potential energy landscapes
- `render_video` - Animate probability density evolution

## Configuration

Enable GPU acceleration with environment variable:

```bash
MCP_USE_GPU=1 scicomp-quantum-mcp
```

## Examples

### 🎬 Visual Demos
Spectacular animated demonstrations:
- [Single-Slit Diffraction](https://andylbrummer.github.io/math-mcp/docs/demos/single-slit)
- [Double-Slit Interference](https://andylbrummer.github.io/math-mcp/docs/demos/double-slit)
- [Triple-Slit Interference](https://andylbrummer.github.io/math-mcp/docs/demos/triple-slit)
- [Bragg Scattering](https://andylbrummer.github.io/math-mcp/docs/demos/bragg-square)

Run demos with Claude:
```bash
claude -p "Simulate double-slit interference" \
  --allowedTools "mcp__quantum-mcp__*"
```

### 📖 Code Examples
Practical tutorials in [EXAMPLES.md](EXAMPLES.md):
- Particle in a box dynamics
- Double-slit interference patterns
- Quantum tunneling
- Crystal lattice scattering

### 📚 Full Documentation
See the [API documentation](https://andylbrummer.github.io/math-mcp/api/quantum-mcp) for complete reference.

## Part of Math-Physics-ML MCP System

Part of a comprehensive system for scientific computing. See the [documentation](https://andylbrummer.github.io/math-mcp/) for the complete ecosystem.
scicomp-mcp-common 0.1.6
Shared infrastructure for MCP servers: GPU management, async tasks, config, serialization
Requires Python: >=3.11
Keywords: async, cuda, gpu, mcp, model-context-protocol

# scicomp-mcp-common

Common utilities and base classes for the Math-Physics-ML MCP system.

## Overview

This package provides shared functionality used across all MCP servers in the Math-Physics-ML system, including:

- MCP server base classes and utilities
- Common error handling patterns
- Shared type definitions and protocols
- Utility functions for tool registration and management

## Installation

```bash
pip install scicomp-mcp-common
```

## Usage

This package is primarily used as a dependency by other MCP servers in the system. Direct usage is typically not needed for end users.

```python
from mcp_common import MCPServer, Tool

# Example: Used by other MCP servers
server = MCPServer()
```

## Part of Math-Physics-ML MCP System

This package is part of a larger system that includes:
- [scicomp-compute-core](https://pypi.org/project/scicomp-compute-core/) - GPU-accelerated computation core
- [scicomp-math-mcp](https://pypi.org/project/scicomp-math-mcp/) - Symbolic math and numerical computing
- [scicomp-quantum-mcp](https://pypi.org/project/scicomp-quantum-mcp/) - Quantum mechanics simulations
- [scicomp-molecular-mcp](https://pypi.org/project/scicomp-molecular-mcp/) - Molecular dynamics
- [scicomp-neural-mcp](https://pypi.org/project/scicomp-neural-mcp/) - Neural network training

See the [full documentation](https://andylbrummer.github.io/math-mcp/) for more details.
scicomp-compute-core 0.1.6
Unified computational primitives: NumPy/CuPy arrays, FFT, linear algebra
Requires Python: >=3.11
Keywords: cuda, cupy, fft, gpu, linear-algebra, numpy

# scicomp-compute-core

GPU-accelerated computation core for the Math-Physics-ML MCP system.

## Overview

This package provides high-performance array operations and numerical computing utilities with optional GPU acceleration using CuPy. It includes:

- **Array utilities** - Unified interface for NumPy and CuPy arrays
- **GPU acceleration** - Seamless CPU/GPU array conversion
- **Numerical operations** - Optimized mathematical functions
- **Linear algebra** - Matrix operations and decompositions
- **FFT operations** - Fast Fourier transforms with GPU support

## Installation

```bash
# CPU only
pip install scicomp-compute-core

# With GPU support (CUDA 12.x)
pip install scicomp-compute-core[gpu]
```

## Quick Start

```python
from compute_core.arrays import to_gpu, to_numpy
import numpy as np

# Create array on CPU
arr = np.array([1, 2, 3, 4, 5])

# Move to GPU (if available)
gpu_arr = to_gpu(arr)

# Perform GPU operations
result = gpu_arr * 2

# Move back to CPU
cpu_result = to_numpy(result)
```

## Features

- **Automatic device selection** - Works with or without GPU
- **Transparent acceleration** - Same API for CPU and GPU arrays
- **Type safety** - Full type hints for all functions
- **Performance** - Optimized for numerical computing workflows

## Part of Math-Physics-ML MCP System

This package is part of a larger system. See the [full documentation](https://andylbrummer.github.io/math-mcp/) for details on all available components.