What capabilities does mcp-server offer?
It provides HDF5 file reading/listing, Slurm job submission/status checks, node hardware queries (CPU, memory, disk), and string/file compression with gzip or zlib.
MCP Server
@zchaffee1
Basic information
About MCP Server
No overview available yet
MCP Server config
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"mcp-server": {
"type": "http",
"url": "http://localhost:8000"
}
}
}MCP Server tools
Tool list not available yet
This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.
Fetch the live tool list directly from this server's endpoint using the button above.
Overview
What is mcp-server?
mcp-server is a Python server that implements the Model Coupling Protocol (MCP) for HDF5 file operations, Slurm job management, node hardware introspection, and data compression. It is designed for HPC or scientific computing environments where MCP workflows need to interact with HDF5 datasets, submit Slurm jobs, query system hardware, or compress/decompress data.
How to use mcp-server?
Clone the repository, create a virtual environment with uv venv .venv, activate it, and install dependencies with uv pip install -e . (optionally -e ".[test]"). Start the server by running python -m src.server, which listens at http://localhost:8000. Send MCP requests to the POST /mcp endpoint or use a health check at GET /health.
Key features of mcp-server
- Read HDF5 datasets and list file contents
- Submit Slurm jobs and check job status
- Get CPU, memory, disk, and comprehensive system information
- Compress/decompress string data or files using gzip or zlib
- JSON-RPC interface via HTTP for tool discovery and invocation
Use cases of mcp-server
- Integrate HDF5 data access into MCP-based AI agents
- Manage Slurm job lifecycles from within an MCP workflow
- Retrieve node hardware specs for resource-aware task scheduling
- Compress and decompress data on the fly as part of a pipeline
Frequently asked questions
How do I install and run mcp-server?
Use `uv` to create a virtual environment, install the package with `uv pip install -e .`, then run `python -m src.server`. The server starts on `http://localhost:8000`.
What endpoints does mcp-server expose?
It exposes `POST /mcp` for MCP requests and `GET /health` for health checks.
What dependencies or runtime are required?
Python with `uv` for dependency management. The server uses packages listed in `pyproject.toml` (installable via `uv pip install -e .`). No specific Python version is mentioned.
Does mcp-server support authentication or transports other than HTTP?
No authentication is mentioned. The only transport is HTTP at `http://localhost:8000`.
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