The CMR Model Context Protocol (MCP) server enables integration of AI retrievers with NASA's Earthdata Common Metadata Repository (CMR) to search and retrieve datasets. With this server, you can:
startdate and stopdate parametersProvides access to NASA's Common Metadata Repository (CMR) for Earthdata Search, allowing users to query and retrieve dataset metadata from NASA's catalog based on keywords, time periods, and data providers like PO.DAAC.
This module is a model context protocol (MCP) for NASA's earthdata common metedata repository (CMR). The goal of this MCP server is to integrate AI retrievals with NASA Catalog of datasets by way of Earthaccess.
uv - a rust based python package manager a LLM client, such as Claude desktop or chatGPT desktop (for consuming the MCP)
Clone the repository to your local environment, or where your LLM client is running.
use the outputs of which uv (UV_LIB) and PWD (CMR_MCP_INSTALL) to update the following configuration.
In this example we'll use Claude desktop.
Update the claude_desktop_config.json file (sometimes this must be created). On a mac, this is often found in ~/Library/Application\ Support/Claude/claude_desktop_config.json
Add the following configuration, filling in the values of UV_LIB and CMR_MCP_INSTALL - don't use environment variables here.
Simply prompt your agent to search cmr for... data. Below is a simple example of this in action.
Other prompts that can work:
local-only server
The server can only run on the client's local machine because it depends on local resources.
An MCP server that integrates AI retrievals with NASA's Common Metadata Repository (CMR), allowing users to search NASA's catalog of Earth science datasets through natural language queries.
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/podaac/cmr-mcp'
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