Nc Mcp — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited Nc Mcp (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
A simple and powerful MCP (Message Communication Protocol) server for exploring, analyzing, and interacting with NetCDF format files. Designed to simplify NetCDF data management with intuitive APIs and efficient data handling.
NetCDF (Network Common Data Form) is a widely used format for storing scientific data. This MCP server provides a streamlined interface to work with NetCDF files, offering essential functionalities to list files, inspect structures, extract data, and analyze variables—all while handling large datasets efficiently through smart sampling.
.nc, .cdf, .netcdf, .nc4) in a specified directory.lat: "0:10:2" to extract subsets).pip install nc-mcp git clone https://github.com/HanchaoLi/nc-mcp.git
cd nc-mcpuv for faster dependency management): # Install uv (if not already installed)
curl -LsSf https://astral.sh/uv/install.sh | sh
# Sync dependencies
uv sync --all-groupspython -m nc_mcp_server.main| Function | Description | Parameters |
|---|---|---|
list_netcdf_files | Lists all NetCDF files in a directory. | directory (str): Path to search (default: .). |
get_netcdf_info | Returns metadata and structure of a NetCDF file (dimensions, variables, attributes). | file_path (str): Path to the NetCDF file. |
get_variable_data | Extracts data from a specific variable (supports slicing and sampling). | file_path (str), variable_name (str), slices (dict, optional), max_elements (int, default: 1000). |
search_variables | Searches variables and attributes for a keyword (case-insensitive). | file_path (str), search_term (str). |
extract_timeseries | Extracts time series data from a spatial variable. | file_path (str), variable_name (str), location (dict, optional: spatial coordinates like {"lat": 10, "lon": 20}). |
Run the test suite to verify functionality:
uv run pytest tests/ -vTests cover:
This project is licensed under the MIT License. See the LICENSE file for details.
git checkout -b feature/amazing-feature)git commit -m 'Add some amazing feature')git push origin feature/amazing-feature)John Li
~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.