MCP server with JAX-based numerical tools
Project description
HIDENNSIM - MCP Server with JAX Integration
A Model Context Protocol (MCP) server providing JAX-based numerical computation tools.
Features
- MCP server with JAX-powered numerical tools (
add_jax,subtract_jax,multiply_jax) - Cython binary compilation for optimized performance
- Cross-platform support (Windows, macOS, Linux)
- Available on PyPI - simple
pip installinstallation - Integration guides for Claude Desktop and Cursor IDE
Quick Start
Installation Checklist
Follow these steps in order for successful setup:
- Step 1: Create virtual environment (
python -m venv hidennsim-env) - Step 2: Activate virtual environment
- Step 3: Install hidennsim (
pip install hidennsim) - Step 4: Install JAX (
pip install "jax[cpu]") - Step 5: Verify JAX works (
python -c "import jax") - Step 6: Configure your LLM (Claude Desktop or Cursor IDE) with full path to
hidennsim.exe - Step 7: Restart your LLM application
1. Create Virtual Environment (Recommended)
Creating a virtual environment isolates HIDENNSIM and its dependencies from your system Python.
macOS/Linux:
python3 -m venv hidennsim-env
source hidennsim-env/bin/activate
Windows (PowerShell):
python -m venv hidennsim-env
.\hidennsim-env\Scripts\Activate.ps1
Windows (Command Prompt):
python -m venv hidennsim-env
hidennsim-env\Scripts\activate.bat
Note: Your terminal prompt should now show
(hidennsim-env)indicating the virtual environment is active.
2. Install HIDENNSIM
Important: Ensure your virtual environment is activated before running pip install commands.
pip install hidennsim
3. Install JAX (REQUIRED)
CRITICAL: JAX must be installed in the same virtual environment as HIDENNSIM. The MCP server will fail to start without it.
CPU-Only (Recommended for most users):
pip install "jax[cpu]"
GPU-Accelerated (Linux or WSL2 only):
WINDOWS USERS: JAX GPU (CUDA) support does NOT work on native Windows. GPU acceleration requires either:
- Linux (native installation)
- WSL2 (Windows Subsystem for Linux 2)
For Linux or WSL2 with NVIDIA GPU and CUDA 12:
pip install "jax[cuda12]"
Verify Installation:
python -c "import jax; print('JAX', jax.__version__, 'installed successfully')"
4. Configure LLM
Claude Desktop Configuration
-
Open Settings: Click Claude icon → Settings → Developer tab → Edit Config
-
Add MCP Server Configuration:
macOS/Linux:
{ "mcpServers": { "hidennsim": { "command": "/full/path/to/hidennsim-env/bin/hidennsim", "args": [] } } }
Windows:
{ "mcpServers": { "hidennsim": { "command": "C:\\full\\path\\to\\hidennsim-env\\Scripts\\hidennsim.exe", "args": [] } } }
Important: Replace the path with the actual absolute path to your virtual environment.
-
Save and Restart Claude Desktop
Cursor IDE Configuration
- Press
Ctrl+Shift+P(Windows/Linux) orCmd+Shift+P(macOS) - Type "Settings" and select Preferences: Open Settings (UI)
- Search for "MCP" and add the same configuration as above
- Save and restart Cursor IDE
Configuration File Locations
Claude Desktop:
- macOS:
~/Library/Application Support/Claude/claude_desktop_config.json - Windows:
%APPDATA%\Claude\claude_desktop_config.json - Linux:
~/.config/Claude/claude_desktop_config.json
Cursor IDE:
- macOS:
~/Library/Application Support/Cursor/User/globalStorage/saoudrizwan.claude-dev/settings/cline_mcp_settings.json - Windows:
%APPDATA%\Cursor\User\globalStorage\saoudrizwan.claude-dev\settings\cline_mcp_settings.json - Linux:
~/.config/Cursor/User/globalStorage/saoudrizwan.claude-dev/settings/cline_mcp_settings.json
Available Tools
| Tool | Description | Parameters |
|---|---|---|
add_jax |
Floating-point addition using JAX | a, b (numbers) |
subtract_jax |
Floating-point subtraction (a - b) | a, b (numbers) |
multiply_jax |
Floating-point multiplication (a * b) | a, b (numbers) |
Troubleshooting
MCP Server Fails to Start
Error: "ModuleNotFoundError: No module named 'jax'"
JAX is not installed. Fix:
# Activate virtual environment first, then:
pip install "jax[cpu]"
Error: "spawn ... hidennsim.exe ENOENT"
The executable path is incorrect. Verify:
- Check the path exists:
- Windows:
C:\path\to\hidennsim-env\Scripts\hidennsim.exe - macOS/Linux:
/path/to/hidennsim-env/bin/hidennsim
- Windows:
- Use absolute paths (not relative) in your config
- Restart your LLM application after config changes
Verify Installation
# Check hidennsim
pip show hidennsim
# Check JAX
pip show jax
# Test MCP server
hidennsim --help
System Requirements
- Python: 3.10 or higher
- Operating System: Windows 10+, macOS 12+, or Linux (Ubuntu 20.04+)
- RAM: 4GB minimum (8GB recommended for GPU acceleration)
Documentation
License
MIT License - See LICENSE file for details.
Support
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