Model Coupling Platform Server

MCP Server Implementation Name: Esteban Nicolas Student ID: A20593170 I. Implemented MCP Capabilities 1 Data Resources 1.1 HDF5 File Listing - Lists mock HDF5 files in a directory structure - Parameters: `path_pattern` (optional file path pattern) 2 Tools 2.1 Slurm Job Submission - Simulates job submission to a Slurm scheduler - Parameters: `script_path` (required), `cores` (optional, default=1) 2.2 CPU Core Reporting - Reports number of CPU cores available on the system - No parameters required 2.3 CSV Visualization - Plots two columns from a CSV file (defaults to first two columns) - Parameters: `csv_path` (required), `column x`, `column y` (both optional) II. Setup Instructions 1. Create virtual environment uv venv -p python3.10 .venv\Scripts\activate # On Unix: source .venv/bin/activate 2. Install dependencies uv sync uv lock 3. Environment configuration The project uses pyproject.toml for dependency management. Key dependencies include: FastAPI Uvicorn Pydantic Pandas Matplotlib Pytest Pytest-ascyncio 4. Running the MCP Server Start the server cd src uvicorn server:app --reload The server will be available at: API endpoint: http://localhost:8000/mcp Health check: http://localhost:8000/health III Testing 1. Run all tests: pytest tests/ Run specific test file: pytest tests/test_capabilities_plot_vis.py pytest tests/test_capabilities_hdf5.py pytest tests/test_capabilities_cpu_core.py pytest tests/test_capabilities_slurm.py pytest tests/test_mcp_handler.py 2. Example Requests 2.1 List available resources curl -X POST http://localhost:8000/mcp \ -H "Content-Type: application/json" \ -d '{"jsonrpc":"2.0","method":"mcp/listResources","id":1}' 2.2 List HDF5 files curl -X POST http://localhost:8000/mcp \ -H "Content-Type: application/json" \ -d '{"jsonrpc":"2.0","method":"mcp/callTool","params":{"tool":"hdf5_file_listing","path_pattern":"/data/sim_run_123"},"id":2}' 2.3 Submit Slurm job curl -X POST http://localhost:8000/mcp \ -H "Content-Type: application/json" \ -d '{"jsonrpc":"2.0","method":"mcp/callTool","params":{"tool":"slurm_job_submission","script_path":"/jobs/analysis.sh","cores":4},"id":3}' 2.4 Plot CSV columns curl -X POST http://localhost:8000/mcp \ -H "Content-Type: application/json" \ -d '{"jsonrpc":"2.0","method":"mcp/callTool","params":{"tool":"plot_vis_columns","csv_path":"data.csv","column x":"time","column y":"temperature"},"id":4}' IV Implementation Notes 1. Mock Implementations: -HDF5 file listing uses a simulated directory structure -Slurm job submission generates mock job IDs -CPU core reporting uses os.cpu_count() 2. CSV Visualization: -Creates plots in a plots_results directory -Defaults to first two columns if none specified -Returns path to generated PNG file 3. Error Handling: -Proper JSON-RPC 2.0 error responses -Input validation for all parameters -Graceful handling of missing files/invalid paths GITHUB: https://github.com/EstebanIIT/cs550_MCP.git