Jupyter Earth Data

by datalayer

2 stars

Not rated

GitHub

About

Bridges Jupyter notebooks with Earth science data analysis by enabling direct NASA Earth Data granule downloads with temporal and geographic filtering capabilities.

Details

Author: datalayer
Repository: datalayer/jupyter-earth-mcp-server
GitHub stars: 2
License: BSD 3-Clause "New" or "Revised" License
Categories: Developer Tools, Productivity, Design, AI, Search, Automation
Tags: #data-science

Setting up with Highlight

This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:

Download and install Highlight from highlightai.com/download
Navigate to the plugins tab and select "Add Custom Plugin"
Configure the plugin with the settings below
Plugin Name Jupyter Earth Data

Command (node, npx, python, etc.) docker
Arguments
- Argument 1 run
- Argument 2 -i
- Argument 3 --rm
- Argument 4 -e
- Argument 5 SERVER_URL
- Argument 6 -e
- Argument 7 TOKEN
- Argument 8 -e
- Argument 9 NOTEBOOK_PATH
- Argument 10 datalayer/jupyter-earth-mcp-server:latest
Environment
- TOKEN MY_TOKEN
- SERVER_URL http://host.docker.internal:8888
- NOTEBOOK_PATH notebook.ipynb
Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
Enable "Start Automatically" if you want the plugin to start when Highlight launches

Setting up with Cursor

Open Cursor's settings
Navigate to the MCP section
Click "Add new Global MCP server"
Copy and paste the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "jupyter earth data": {
            "env": {
                "TOKEN": "MY_TOKEN",
                "SERVER_URL": "http://host.docker.internal:8888",
                "NOTEBOOK_PATH": "notebook.ipynb"
            },
            "args": [
                "run",
                "-i",
                "--rm",
                "-e",
                "SERVER_URL",
                "-e",
                "TOKEN",
                "-e",
                "NOTEBOOK_PATH",
                "datalayer/jupyter-earth-mcp-server:latest"
            ],
            "command": "docker"
        }
    }
}

JSON

{
    "mcpServers": {
        "jupyter earth data": {
            "env": {
                "TOKEN": "MY_TOKEN",
                "SERVER_URL": "http://host.docker.internal:8888",
                "NOTEBOOK_PATH": "notebook.ipynb"
            },
            "args": [
                "run",
                "-i",
                "--rm",
                "-e",
                "SERVER_URL",
                "-e",
                "TOKEN",
                "-e",
                "NOTEBOOK_PATH",
                "datalayer/jupyter-earth-mcp-server:latest"
            ],
            "command": "docker"
        }
    }
}

JSON

{
    "mcpServers": {
        "jupyter earth data": {
            "env": {
                "TOKEN": "MY_TOKEN",
                "SERVER_URL": "http://localhost:8888",
                "NOTEBOOK_PATH": "notebook.ipynb"
            },
            "args": [
                "run",
                "-i",
                "--rm",
                "-e",
                "SERVER_URL",
                "-e",
                "TOKEN",
                "-e",
                "NOTEBOOK_PATH",
                "--network=host",
                "datalayer/jupyter-earth-mcp-server:latest"
            ],
            "command": "docker"
        }
    }
}

Setting up with Claude Desktop

Open Claude Desktop's settings
Go to the Integrations tab
Click "Add MCP Server"
Use the configuration below based on your operating system

Note: Make sure Claude Desktop is running before attempting to connect.

JSON

{
    "mcpServers": {
        "jupyter earth data": {
            "env": {
                "TOKEN": "MY_TOKEN",
                "SERVER_URL": "http://host.docker.internal:8888",
                "NOTEBOOK_PATH": "notebook.ipynb"
            },
            "args": [
                "run",
                "-i",
                "--rm",
                "-e",
                "SERVER_URL",
                "-e",
                "TOKEN",
                "-e",
                "NOTEBOOK_PATH",
                "datalayer/jupyter-earth-mcp-server:latest"
            ],
            "command": "docker"
        }
    }
}

JSON

{
    "mcpServers": {
        "jupyter earth data": {
            "env": {
                "TOKEN": "MY_TOKEN",
                "SERVER_URL": "http://host.docker.internal:8888",
                "NOTEBOOK_PATH": "notebook.ipynb"
            },
            "args": [
                "run",
                "-i",
                "--rm",
                "-e",
                "SERVER_URL",
                "-e",
                "TOKEN",
                "-e",
                "NOTEBOOK_PATH",
                "datalayer/jupyter-earth-mcp-server:latest"
            ],
            "command": "docker"
        }
    }
}

JSON

{
    "mcpServers": {
        "jupyter earth data": {
            "env": {
                "TOKEN": "MY_TOKEN",
                "SERVER_URL": "http://localhost:8888",
                "NOTEBOOK_PATH": "notebook.ipynb"
            },
            "args": [
                "run",
                "-i",
                "--rm",
                "-e",
                "SERVER_URL",
                "-e",
                "TOKEN",
                "-e",
                "NOTEBOOK_PATH",
                "--network=host",
                "datalayer/jupyter-earth-mcp-server:latest"
            ],
            "command": "docker"
        }
    }
}

Setting up with Windsurf

Open Windsurf's preferences
Go to the Integrations section
Click "Add MCP Integration"
Use the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "jupyter earth data": {
            "env": {
                "TOKEN": "MY_TOKEN",
                "SERVER_URL": "http://host.docker.internal:8888",
                "NOTEBOOK_PATH": "notebook.ipynb"
            },
            "args": [
                "run",
                "-i",
                "--rm",
                "-e",
                "SERVER_URL",
                "-e",
                "TOKEN",
                "-e",
                "NOTEBOOK_PATH",
                "datalayer/jupyter-earth-mcp-server:latest"
            ],
            "command": "docker"
        }
    }
}

JSON

{
    "mcpServers": {
        "jupyter earth data": {
            "env": {
                "TOKEN": "MY_TOKEN",
                "SERVER_URL": "http://host.docker.internal:8888",
                "NOTEBOOK_PATH": "notebook.ipynb"
            },
            "args": [
                "run",
                "-i",
                "--rm",
                "-e",
                "SERVER_URL",
                "-e",
                "TOKEN",
                "-e",
                "NOTEBOOK_PATH",
                "datalayer/jupyter-earth-mcp-server:latest"
            ],
            "command": "docker"
        }
    }
}

JSON

{
    "mcpServers": {
        "jupyter earth data": {
            "env": {
                "TOKEN": "MY_TOKEN",
                "SERVER_URL": "http://localhost:8888",
                "NOTEBOOK_PATH": "notebook.ipynb"
            },
            "args": [
                "run",
                "-i",
                "--rm",
                "-e",
                "SERVER_URL",
                "-e",
                "TOKEN",
                "-e",
                "NOTEBOOK_PATH",
                "--network=host",
                "datalayer/jupyter-earth-mcp-server:latest"
            ],
            "command": "docker"
        }
    }
}

Setting up with Cline

Open Cline's settings
Navigate to the Integrations section
Click "Add MCP Server"
Copy and paste the configuration below based on your operating system

Note: Make sure to restart Cline after adding the configuration.

JSON

{
    "mcpServers": {
        "jupyter earth data": {
            "env": {
                "TOKEN": "MY_TOKEN",
                "SERVER_URL": "http://host.docker.internal:8888",
                "NOTEBOOK_PATH": "notebook.ipynb"
            },
            "args": [
                "run",
                "-i",
                "--rm",
                "-e",
                "SERVER_URL",
                "-e",
                "TOKEN",
                "-e",
                "NOTEBOOK_PATH",
                "datalayer/jupyter-earth-mcp-server:latest"
            ],
            "command": "docker"
        }
    }
}

JSON

{
    "mcpServers": {
        "jupyter earth data": {
            "env": {
                "TOKEN": "MY_TOKEN",
                "SERVER_URL": "http://host.docker.internal:8888",
                "NOTEBOOK_PATH": "notebook.ipynb"
            },
            "args": [
                "run",
                "-i",
                "--rm",
                "-e",
                "SERVER_URL",
                "-e",
                "TOKEN",
                "-e",
                "NOTEBOOK_PATH",
                "datalayer/jupyter-earth-mcp-server:latest"
            ],
            "command": "docker"
        }
    }
}

JSON

{
    "mcpServers": {
        "jupyter earth data": {
            "env": {
                "TOKEN": "MY_TOKEN",
                "SERVER_URL": "http://localhost:8888",
                "NOTEBOOK_PATH": "notebook.ipynb"
            },
            "args": [
                "run",
                "-i",
                "--rm",
                "-e",
                "SERVER_URL",
                "-e",
                "TOKEN",
                "-e",
                "NOTEBOOK_PATH",
                "--network=host",
                "datalayer/jupyter-earth-mcp-server:latest"
            ],
            "command": "docker"
        }
    }
}

Setting up with Goose

Open Goose's preferences
Go to the Integrations tab
Select "MCP Servers"
Click "Add New Server"
Use the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "jupyter earth data": {
            "env": {
                "TOKEN": "MY_TOKEN",
                "SERVER_URL": "http://host.docker.internal:8888",
                "NOTEBOOK_PATH": "notebook.ipynb"
            },
            "args": [
                "run",
                "-i",
                "--rm",
                "-e",
                "SERVER_URL",
                "-e",
                "TOKEN",
                "-e",
                "NOTEBOOK_PATH",
                "datalayer/jupyter-earth-mcp-server:latest"
            ],
            "command": "docker"
        }
    }
}

JSON

{
    "mcpServers": {
        "jupyter earth data": {
            "env": {
                "TOKEN": "MY_TOKEN",
                "SERVER_URL": "http://host.docker.internal:8888",
                "NOTEBOOK_PATH": "notebook.ipynb"
            },
            "args": [
                "run",
                "-i",
                "--rm",
                "-e",
                "SERVER_URL",
                "-e",
                "TOKEN",
                "-e",
                "NOTEBOOK_PATH",
                "datalayer/jupyter-earth-mcp-server:latest"
            ],
            "command": "docker"
        }
    }
}

JSON

{
    "mcpServers": {
        "jupyter earth data": {
            "env": {
                "TOKEN": "MY_TOKEN",
                "SERVER_URL": "http://localhost:8888",
                "NOTEBOOK_PATH": "notebook.ipynb"
            },
            "args": [
                "run",
                "-i",
                "--rm",
                "-e",
                "SERVER_URL",
                "-e",
                "TOKEN",
                "-e",
                "NOTEBOOK_PATH",
                "--network=host",
                "datalayer/jupyter-earth-mcp-server:latest"
            ],
            "command": "docker"
        }
    }
}

From the repository

{
  "mcpServers": {
    "jupyter-earth": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "-e",
        "SERVER_URL",
        "-e",
        "TOKEN",
        "-e",
        "NOTEBOOK_PATH",
        "datalayer/jupyter-earth-mcp-server:latest"
      ],
      "env": {
        "SERVER_URL": "http://host.docker.internal:8888",
        "TOKEN": "MY_TOKEN",
        "NOTEBOOK_PATH": "notebook.ipynb"
      }
    }
  }
}

CLAUDE_CONFIG=${HOME}/.config/Claude/claude_desktop_config.json
cat <<EOF > $CLAUDE_CONFIG
{
  "mcpServers": {
    "jupyter-earth": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "-e",
        "SERVER_URL",
        "-e",
        "TOKEN",
        "-e",
        "NOTEBOOK_PATH",
        "--network=host",
        "datalayer/jupyter-earth-mcp-server:latest"
      ],
      "env": {
        "SERVER_URL": "http://localhost:8888",
        "TOKEN": "MY_TOKEN",
        "NOTEBOOK_PATH": "notebook.ipynb"
      }
    }
  }
}
EOF
cat $CLAUDE_CONFIG

`download_earth_data_granules`

Download Earth data granules from NASA Earth Data. Parameters: folder_name (string), short_name (string), count (int), temporal (optional tuple), bounding_box (optional tuple)

The server currently offers 1 tool:

1. download_earth_data_granules

- Add a code cell in a Jupyter notebook to download Earth data granules from NASA Earth Data.
- Input:
- folder_name(string): Local folder name to save the data.
- short_name(string): Short name of the Earth dataset to download.
- count(int): Number of data granules to download.
- temporal (tuple): (Optional) Temporal range in the format (date_from, date_to).
- bounding_box (tuple): (Optional) Bounding box in the format (lower_left_lon, lower_left_lat, upper_right_lon, upper_right_lat).
- Returns: Cell output.

Claude Desktop / Cursor

Paste into your MCP client config file to install this server.

{
    "mcpServers": {
        "jupyter earth data": {
            "env": {
                "TOKEN": "MY_TOKEN",
                "SERVER_URL": "http://host.docker.internal:8888",
                "NOTEBOOK_PATH": "notebook.ipynb"
            },
            "args": [
                "run",
                "-i",
                "--rm",
                "-e",
                "SERVER_URL",
                "-e",
                "TOKEN",
                "-e",
                "NOTEBOOK_PATH",
                "datalayer/jupyter-earth-mcp-server:latest"
            ],
            "command": "docker"
        }
    }
}

Linux

{
    "env": {
        "TOKEN": "MY_TOKEN",
        "SERVER_URL": "http://localhost:8888",
        "NOTEBOOK_PATH": "notebook.ipynb"
    },
    "args": [
        "run",
        "-i",
        "--rm",
        "-e",
        "SERVER_URL",
        "-e",
        "TOKEN",
        "-e",
        "NOTEBOOK_PATH",
        "--network=host",
        "datalayer/jupyter-earth-mcp-server:latest"
    ],
    "command": "docker"
}

Macos

{
    "env": {
        "TOKEN": "MY_TOKEN",
        "SERVER_URL": "http://host.docker.internal:8888",
        "NOTEBOOK_PATH": "notebook.ipynb"
    },
    "args": [
        "run",
        "-i",
        "--rm",
        "-e",
        "SERVER_URL",
        "-e",
        "TOKEN",
        "-e",
        "NOTEBOOK_PATH",
        "datalayer/jupyter-earth-mcp-server:latest"
    ],
    "command": "docker"
}

Windows

{
    "env": {
        "TOKEN": "MY_TOKEN",
        "SERVER_URL": "http://host.docker.internal:8888",
        "NOTEBOOK_PATH": "notebook.ipynb"
    },
    "args": [
        "run",
        "-i",
        "--rm",
        "-e",
        "SERVER_URL",
        "-e",
        "TOKEN",
        "-e",
        "NOTEBOOK_PATH",
        "datalayer/jupyter-earth-mcp-server:latest"
    ],
    "command": "docker"
}

> This repository is archived - Use https://github.com/datalayer/earthdata-mcp-server instead.

🌎 ✨ Jupyter Earth MCP Server

🌍 Jupyter Earth MCP Server is a Model Context Protocol (MCP) server implementation that provides a set of tools for 🗺️ Geospatial analysis in 📓 Jupyter notebooks.

The following demo uses the Earthdata MCP server to search for datasets and data granules on NASA Earthdata, this MCP server to download the data in Jupyter and the jupyter-mcp-server to run further analysis.

<div>
<a href="https://www.loom.com/share/c2b5b05f548d4f1492d5c107f0c48dbc">
<p>Analyzing Sea Level Rise with AI-Powered Geospatial Tools and Jupyter - Watch Video</p>
</a>
<a href="https://www.loom.com/share/c2b5b05f548d4f1492d5c107f0c48dbc">

</a>
</div>

Start JupyterLab

Make sure you have the following installed. The collaboration package is needed as the modifications made on the notebook can be seen thanks to Jupyter Real Time Collaboration.

pip install jupyterlab==4.4.1 jupyter-collaboration==4.0.2 ipykernel
pip uninstall -y pycrdt datalayer_pycrdt
pip install datalayer_pycrdt==0.12.17

Then, start JupyterLab with the following command.

jupyter lab --port 8888 --IdentityProvider.token MY_TOKEN --ip 0.0.0.0

You can also run make jupyterlab.

> [!NOTE]
>
> The --ip is set to 0.0.0.0 to allow the MCP server running in a Docker container to access your local JupyterLab.

Use with Claude Desktop

Claude Desktop can be downloaded from this page for macOS and Windows.

For Linux, we had success using this UNOFFICIAL build script based on nix

# ⚠️ UNOFFICIAL
You can also run make claude-linux
NIXPKGS_ALLOW_UNFREE=1 nix run github:k3d3/claude-desktop-linux-flake \
  --impure \
  --extra-experimental-features flakes \
  --extra-experimental-features nix-command

To use this with Claude Desktop, add the following to your claude_desktop_config.json (read more on the MCP documentation website).

> [!IMPORTANT]
>
> Ensure the port of the SERVER_URLand TOKEN match those used in the jupyter lab command.
>
> The NOTEBOOK_PATH should be relative to the directory where JupyterLab was started.

Claude Configuration on macOS and Windows

{
  "mcpServers": {
    "jupyter-earth": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "-e",
        "SERVER_URL",
        "-e",
        "TOKEN",
        "-e",
        "NOTEBOOK_PATH",
        "datalayer/jupyter-earth-mcp-server:latest"
      ],
      "env": {
        "SERVER_URL": "http://host.docker.internal:8888",
        "TOKEN": "MY_TOKEN",
        "NOTEBOOK_PATH": "notebook.ipynb"
      }
    }
  }
}

Claude Configuration on Linux

CLAUDE_CONFIG=${HOME}/.config/Claude/claude_desktop_config.json
cat <<EOF > $CLAUDE_CONFIG
{
  "mcpServers": {
    "jupyter-earth": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "-e",
        "SERVER_URL",
        "-e",
        "TOKEN",
        "-e",
        "NOTEBOOK_PATH",
        "--network=host",
        "datalayer/jupyter-earth-mcp-server:latest"
      ],
      "env": {
        "SERVER_URL": "http://localhost:8888",
        "TOKEN": "MY_TOKEN",
        "NOTEBOOK_PATH": "notebook.ipynb"
      }
    }
  }
}
EOF
cat $CLAUDE_CONFIG

Components

Tools

The server currently offers 1 tool:

1. download_earth_data_granules

Prompts

1. download_analyze_global_sea_level
- To ask for downloading and analyzing global sea level data in Jupyter.
- Returns: Prompt correctly formatted.

Building

You can build the Docker image it from source.

make build-docker

29:["$","div",null,{

No reviews yet — be the first

Use Google, GitHub, or an email account so ratings stay tied to real people.

Email sign in

No reviews posted yet.

About

Details

Jump to

Setting up with Highlight

From the repository

download_earth_data_granules

Claude Desktop / Cursor

Linux

Macos

Windows

🌎 ✨ Jupyter Earth MCP Server

Start JupyterLab

Use with Claude Desktop

You can also run make claude-linux

Claude Configuration on macOS and Windows

Claude Configuration on Linux

Components

Tools

Prompts

Building

Install

More like this

Time

Sentry

Github

Git

GitLab

Context 7

`download_earth_data_granules`

You can also run `make claude-linux`