mcp-disaster-server
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@mcp-disaster-servershow me earthquake statistics in Japan since 2010"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
mcp-disaster-server
MCP server for querying the Kaggle "All Natural Disasters 1900-2021 / EOSDIS" CSV dataset via pandas.
Exposes two tools over the stdio MCP protocol:
search_disasters— filter records by disaster type, country, and year rangeget_disaster_statistics— aggregate statistics by dimension (country, continent, year, etc.)
Usage with uvx
DISASTER_CSV_PATH=/path/to/natural_disasters.csv uvx --from . mcp-disaster-serverOr if published to PyPI:
DISASTER_CSV_PATH=/path/to/natural_disasters.csv uvx mcp-disaster-serverRelated MCP server: wems-mcp-server
Install as editable package (for development)
pip install -e .After installation the entry point is available as:
DISASTER_CSV_PATH=/path/to/natural_disasters.csv mcp-disaster-serverEnvironment
Variable | Required | Description |
| First run only | Kaggle API token for auto-downloading the CSV on first launch. Not needed if the CSV already exists at |
| No | Override the CSV path. Defaults to |
Data
The server auto-downloads the Kaggle All Natural Disasters 1900-2021 / EOSDIS dataset
on first launch (requires KAGGLE_API_TOKEN) and caches it at
~/.mcp-disaster-server/natural_disasters.csv. Subsequent runs reuse the cached file.
Column names are normalized at startup (lowercase, underscores, no punctuation).
See docs/architecture.md for design decisions.
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