Configuration
This guide explains how to configure the Math-Physics-ML MCP servers for use with Claude Desktop or Claude Code.
Available MCP Servers
The system provides four specialized MCP servers:
- math-mcp - Symbolic algebra and GPU-accelerated numerical computing
- quantum-mcp - Wave mechanics and Schrödinger equation simulations
- molecular-mcp - Classical molecular dynamics simulations
- neural-mcp - Neural network training and experimentation
Prerequisites
Before configuring the MCP servers, ensure they are installed:
# Verify installation
ls -la .venv/bin/*-mcp
# You should see:
# - .venv/bin/math-mcp
# - .venv/bin/quantum-mcp
# - .venv/bin/molecular-mcp
# - .venv/bin/neural-mcp
If the servers are not installed, run:
uv sync --all-extras
uv pip install --python .venv/bin/python3 -e shared/mcp-common -e shared/compute-core
uv pip install --python .venv/bin/python3 -e servers/math-mcp -e servers/quantum-mcp
uv pip install --python .venv/bin/python3 -e servers/molecular-mcp -e servers/neural-mcp
Configuration Methods
Claude Desktop Configuration
Claude Desktop is the recommended method for GUI-based usage.
Configuration File Location:
- Linux/macOS:
~/.config/Claude/claude_desktop_config.json - Windows:
%APPDATA%\Claude\claude_desktop_config.json
Configuration:
Add the following to your claude_desktop_config.json file:
{
"mcpServers": {
"math-mcp": {
"command": "uv",
"args": [
"run",
"--directory",
"/home/beagle/work/math-mcp",
"math-mcp"
]
},
"quantum-mcp": {
"command": "uv",
"args": [
"run",
"--directory",
"/home/beagle/work/math-mcp",
"quantum-mcp"
]
},
"molecular-mcp": {
"command": "uv",
"args": [
"run",
"--directory",
"/home/beagle/work/math-mcp",
"molecular-mcp"
]
},
"neural-mcp": {
"command": "uv",
"args": [
"run",
"--directory",
"/home/beagle/work/math-mcp",
"neural-mcp"
]
}
}
}
Important: Replace /home/beagle/work/math-mcp with the absolute path to your math-mcp installation directory.
Verification:
- Restart Claude Desktop
- Start a new conversation
- The MCP servers should appear in the tools panel
- Try using a tool: "Create a 5x5 matrix of random numbers" (uses math-mcp)
Claude Code CLI Configuration
For command-line usage with Claude Code:
# Add servers manually using Claude Code CLI
claude-code config add-mcp-server math-mcp "uv run --directory $(pwd) math-mcp"
claude-code config add-mcp-server quantum-mcp "uv run --directory $(pwd) quantum-mcp"
claude-code config add-mcp-server molecular-mcp "uv run --directory $(pwd) molecular-mcp"
claude-code config add-mcp-server neural-mcp "uv run --directory $(pwd) neural-mcp"
Alternatively, use the provided mcp-servers.json configuration file in the project root.
Verification:
# List available MCPs
claude-code mcp list
# Check server status
claude-code mcp status
Direct Execution (Testing)
For testing and development, you can run any MCP server directly:
# Activate the virtual environment
source .venv/bin/activate # Linux/macOS
# or
.venv\Scripts\activate # Windows
# Run any server directly
math-mcp
quantum-mcp
molecular-mcp
neural-mcp
# Or with uv (no activation needed)
uv run math-mcp
uv run quantum-mcp
uv run molecular-mcp
uv run neural-mcp
Tool Discovery
Each MCP server provides an info tool for progressive discovery of capabilities:
Math MCP
info(topic="overview") # See all categories
info(topic="symbolic") # Symbolic algebra tools
info(topic="numerical") # Numerical computing tools
info(topic="transforms") # FFT and transforms
info(topic="optimization") # Optimization tools
info(topic="matrix_multiply") # Specific tool help
Quantum MCP
info(topic="overview") # All quantum tools
info(topic="solve_schrodinger") # Schrödinger solver help
Molecular MCP
info() # All molecular dynamics tools
Neural MCP
info() # All neural network tools
GPU Support
All MCP servers support GPU acceleration with automatic CPU fallback:
- GPU Available: Set
use_gpu=Truein tool calls for 10-100x speedup - No GPU: Automatically falls back to CPU (NumPy instead of CuPy)
- Check Status: GPU Manager logs CUDA availability at startup
To verify GPU availability:
# Check CUDA availability
python -c "import torch; print(torch.cuda.is_available())"
python -c "import cupy; print(cupy.cuda.is_available())"
Configuration Files
The system uses the following configuration files:
- mcp-servers.json - Pre-configured server definitions
- config.kdl - GPU memory settings and runtime configuration
- pyproject.toml - Package dependencies and entry points
GPU Memory Configuration
Edit config.kdl to customize GPU memory settings:
gpu {
memory_pool_size "500MB"
memory_growth true
}
Troubleshooting
Server Won't Start
# Check Python version (requires 3.11+)
python --version
# Reinstall dependencies
uv sync
# Reinstall servers
uv pip install -e servers/math-mcp -e servers/quantum-mcp \
-e servers/molecular-mcp -e servers/neural-mcp
Entry Points Not Found
# Verify installation
pip show math-mcp quantum-mcp molecular-mcp neural-mcp
# Check entry points
which math-mcp quantum-mcp molecular-mcp neural-mcp
# Should show paths like:
# /path/to/math-mcp/.venv/bin/math-mcp
GPU Not Detected
# Check CUDA availability
python -c "import torch; print(torch.cuda.is_available())"
python -c "import cupy; print(cupy.cuda.is_available())"
# If False, install CUDA toolkit or use CPU mode (automatic fallback)
Tools Not Appearing in Claude Desktop
- Ensure the configuration file path is correct
- Verify the absolute path to math-mcp directory is correct
- Restart Claude Desktop completely
- Check Claude Desktop logs for error messages
Next Steps
Once configured, proceed to the Quick Start guide to learn how to use the MCP tools.