mcp-server
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This document provides an overview of a Model Context Protocol (MCP) server implementation by Jafar Alzoubi, focusing on HDF5 data handling and Slurm job scheduling.
The MCP server implementation by Jafar Alzoubi is designed to handle HDF5 data operations and simulate Slurm job scheduling. The server is built using Python and utilizes the uvicorn server for asynchronous request processing. It supports JSON-RPC 2.0 for communication, ensuring robust error handling and proper response mechanisms. The server is fully tested with 100% coverage, ensuring reliability in its operations. The HDF5 handler uses the h5py library to perform file operations such as reading datasets and retrieving metadata. The Slurm handler simulates job submissions, generating UUID-based job IDs and tracking job statuses in memory. The server is designed to be easily set up and run, with clear instructions for environment setup, dependency synchronization, and server execution.
Features
- HDF5 Data Handling: Uses h5py for file operations, supporting actions like list, read, and metadata retrieval.
- Slurm Job Simulation: Simulates job submission and tracking with subprocess, generating UUID-based job IDs.
- JSON-RPC 2.0 Compliance: Ensures robust communication with proper error handling and response mechanisms.
- Asynchronous Processing: Utilizes uvicorn for handling asynchronous requests efficiently.
- Comprehensive Testing: Achieves 100% test coverage for both HDF5 and Slurm capabilities.
Tools
HDF5
Operations for processing HDF5 files, including read, list and metadata operations
Slurm
Used to simulate Slurm job submission and status tracking
