MCP Servers

netcdf-mcp

Enables reading and understanding NetCDF files, providing tools to inspect structure, variables, metadata, and data quality for scientific datasets.

Category

README

NetCDF MCP Server

An MCP server that reads and understands NetCDF files, designed to give coding agents context about scientific data files.

Installation

uv pip install -e .

Usage

With Cursor/Claude

Add to your MCP configuration file (~/.cursor/mcp.json):

{
  "mcpServers": {
    "netcdf-mcp": {
      "command": "/path/to/uv",
      "args": ["run", "--directory", "/path/to/netcdf-mcp", "netcdf-mcp"]
    }
  }
}

Replace /path/to/uv with your uv binary location (e.g., /opt/homebrew/bin/uv) and /path/to/netcdf-mcp with where you cloned this repository.

Standalone

netcdf-mcp

Tools

Tool	Description
`get_file_structure`	Get dimensions, coordinates, variables, and attributes
`list_variables`	List all data variables with shapes and units
`get_global_attributes`	Get file-level metadata
`get_variable_info`	Detailed info about a specific variable
`get_variable_stats`	Statistical summary (min, max, mean, percentiles)
`get_variable_sample`	Extract sample values for inspection
`get_dimension_values`	Get coordinate values (time, lat, lon)
`check_data_quality`	Check for NaN, outliers, and suspicious patterns
`compare_variables`	Compare two variables for compatibility and correlation
`get_time_range`	Get temporal extent in human-readable format
`get_spatial_bounds`	Get geographic extent (lat/lon bounds)
`check_cf_compliance`	Verify CF conventions compliance
`explain_variable`	Human-readable explanation of a variable

Recommended Servers

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

E2B

Using MCP to run code via e2b.

Neon Database

MCP server for interacting with Neon Management API and databases

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.