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.
@zchaffee1
基本信息
暂无概览
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"mcp-server": {
"type": "http",
"url": "http://localhost:8000"
}
}
}工具列表暂未提供
当前收录暂时没有可展示的工具列表,不代表服务没有工具。请查阅项目文档了解支持的能力。
点击上方按钮,直接连接服务器端点实时获取工具列表。
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.
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.
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.
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`.
It exposes `POST /mcp` for MCP requests and `GET /health` for health checks.
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.
No authentication is mentioned. The only transport is HTTP at `http://localhost:8000`.
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