FAQ: MCP Server for HDF5 & Slurm Integration

Q: What is an MCP Server? A: MCP (Model Context Protocol) server acts as a bridge, allowing AI models to access and interact with external data sources and tools. It standardizes how applications provide context to LLMs.

Q: What are HDF5 and Slurm, and why are they important? A: HDF5 is a high-performance data storage format used in scientific and engineering. Slurm is a workload manager for high-performance computing clusters. They are essential for managing and processing large datasets and complex simulations.

Q: What actions are supported for HDF5 files? A: The server supports listing directory contents, reading datasets with shape/dtype info, and retrieving file-level metadata.

Q: How does the Slurm handler simulate job submissions? A: It uses subprocess to simulate job submission, generates UUID-based job IDs, tracks job status in memory, and simulates queueing/running/completed states.

Q: Is this server JSON-RPC 2.0 compliant? A: Yes, the server is fully compliant with the JSON-RPC 2.0 standard, ensuring seamless communication with other systems.

Q: What is UBOS? A: UBOS is a full-stack AI Agent Development Platform focused on bringing AI Agents to every business department. It helps orchestrate AI Agents, connect them with enterprise data, build custom AI Agents, and create Multi-Agent Systems.

Q: How does this MCP server integrate with UBOS? A: It seamlessly integrates with other UBOS services and tools, allowing for the orchestration of complex AI workflows and connection to various data sources.

Q: What are some common troubleshooting steps? A: Common issues include port conflicts (resolve with lsof -i :8000 and kill -9 <PID>) and missing dependencies (install with uv pip install --force-reinstall -r requirements.txt).

Q: What kind of test coverage does this server have? A: This server has 100% test coverage for both HDF5 and Slurm capabilities, ensuring reliability and stability.

Q: Where can I find example test outputs? A: Sample test outputs are provided in the documentation, demonstrating successful execution of HDF5 dataset reading and Slurm job submission.