Implements Model Context Protocol for efficient HDF5 file operations, Slurm job management, node hardware info retrieval, and data compression with gzip and zlib support.
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By: Zack Chaffee A20478873
A server implementing Model Coupling Protocol (MCP) capabilities for HDF5 file operations and Slurm job management.
Once you clone this reponsitory cd into it
After this hwe will create a virtual enviornment and install all dependincies:
uv venv .venv
source .venv/bin/activate # On Windows: .venv\Scripts\activate
uv pip install -e .
uv pip install -e ".[test]"
To startup the server run:
python -m src.server
This will autoclocate the server at http://localhost:8000.
POST /mcp
: Main endpoint for MCP requestsGET /health
: Health check endpointimport httpx async with httpx.AsyncClient() as client: # Read a dataset response = await client.post("http://localhost:8000/mcp", json={ "capability": "hdf5", "action": "read_dataset", "parameters": { "file_path": "/path/to/data.h5", "dataset_path": "/path/to/dataset" } }) # List contents response = await client.post("http://localhost:8000/mcp", json={ "capability": "hdf5", "action": "list_contents", "parameters": { "file_path": "/path/to/data.h5", "group_path": "/" } })
curl -X POST http://localhost:8000/mcp \ -H "Content-Type: application/json" \ -d '{ "jsonrpc": "2.0", "method": "mcp/listTools", "params": {}, "id": "1" }'
For testing rung:
pytest
For tests with coverage:
pytest --cov=src
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