wsl-envidat-mcp 0.1.0

MCP-Server für WSL/EnviDat – Umweltforschungs- und Monitoringdaten der Eidg. Forschungsanstalt für Wald, Schnee und Landschaft

🇨🇭 Part of the Swiss Public Data MCP Portfolio

wsl-envidat-mcp 🌲❄️⛰️

MCP server connecting AI models to Swiss environmental research data from WSL via EnviDat — forest, snow, avalanches, natural hazards and biodiversity, no API key required.

🇩🇪 Deutsche Version

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Overview

The WSL (Eidgenössische Forschungsanstalt für Wald, Schnee und Landschaft / Swiss Federal Research Institute for Forest, Snow and Landscape) is one of Europe's leading environmental research institutes. Its open data platform EnviDat provides access to 1,000+ research datasets, time series of up to 130 years, and data from 6,000+ monitoring stations.

This MCP server exposes the EnviDat CKAN API as 12 tools and 2 resources, enabling AI assistants to search, filter and retrieve WSL research data by keyword, domain, or geographic bounding box — all without an API key.

Anchor demo query: "How was air quality and forest health around Schulhaus Leutschenbach in Zurich — and what does the WSL say about the current forest condition in the canton?"

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Features

• 12 tools covering full-text search, domain-specific queries, spatial search, and curated thematic tools (avalanche, forest, natural hazards)
• 2 MCP resources for organizations and research domains
• 5 research domains: Forest · Biodiversity · Natural Hazards · Snow & Ice · Landscape
• 815+ datasets, time series since 1890, data from the SLF avalanche research institute
• No API key required — all data publicly accessible via open licenses
• Dual transport: stdio (Claude Desktop / local) + Streamable HTTP (cloud deployment)
• Model-agnostic: works with Claude, GPT-4, and any MCP-compatible client

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Prerequisites

• Python 3.11+
• pip or uv / uvx
• Internet connection (live API calls to envidat.ch)

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Installation

# Recommended: uvx (no installation needed)
uvx wsl-envidat-mcp

# Or with pip
pip install wsl-envidat-mcp

# Development
git clone https://github.com/malkreide/wsl-envidat-mcp.git
cd wsl-envidat-mcp
pip install -e ".[dev]"

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Quickstart

Claude Desktop

Edit ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows):

{
  "mcpServers": {
    "wsl-envidat": {
      "command": "uvx",
      "args": ["wsl-envidat-mcp"]
    }
  }
}

Restart Claude Desktop, then ask:

• "What WSL datasets exist on fatal avalanche accidents in Switzerland?"
• "Show me forest inventory data from the LFI for the canton of Zurich."
• "Which natural hazard research data does the SLF publish on EnviDat?"
• "Are there WSL datasets on drought conditions in summer 2022?"
• "What biodiversity data is available for alpine ecosystems?"

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Configuration

No API key required. Optional environment variables:

Variable	Default	Description
MCP_TRANSPORT	stdio	Transport mode: stdio or streamable_http
PORT	8000	Port for Streamable HTTP mode

Cloud Deployment (Streamable HTTP)

For use via claude.ai in the browser (e.g. on managed workstations without local software):

MCP_TRANSPORT=streamable_http PORT=8000 python -m wsl_envidat_mcp.server

💡 "stdio for the developer laptop, SSE for the browser."

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Available Tools

Tool	Description
wsl_search_datasets	Full-text search across all datasets (Solr syntax supported)
wsl_get_dataset	Full metadata, DOI, download URLs for a specific dataset
wsl_search_by_domain	Thematic search by WSL research domain
wsl_search_by_location	Spatial search via bounding box coordinates
wsl_list_organizations	List all WSL research units on EnviDat
wsl_get_organization	Details of a specific research unit incl. datasets
wsl_list_tags	Browse available tags/keywords
wsl_get_recent_datasets	Most recently updated datasets
wsl_get_avalanche_data	SLF avalanche & snow data (incl. fatal accidents since 1936)
wsl_get_forest_data	Forest data incl. National Forest Inventory (LFI) & Sanasilva
wsl_get_naturgefahren_data	Natural hazard datasets (landslides, rockfall, floods)
wsl_catalog_stats	Catalog overview and statistics

Example Use Cases

Query	Tool
"Fatal avalanche accidents in Valais since 2000?"	wsl_get_avalanche_data
"Forest health data for canton Zurich?"	wsl_get_forest_data
"Landslide risk datasets near Brienz?"	wsl_get_naturgefahren_data
"Most recent WSL publications on biodiversity?"	wsl_search_by_domain
"Which datasets cover the area around Lake Constance?"	wsl_search_by_location
"How many datasets does SLF publish?"	wsl_get_organization

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Resources

URI	Description
envidat://organization/{name}	Research unit (e.g. slf, wsl)
envidat://domain/{domain}	Domain overview with top datasets

Valid domain values: wald, biodiversitaet, naturgefahren, schnee_eis, landschaft

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Architecture

┌─────────────────┐     ┌───────────────────────────┐     ┌──────────────────────────┐
│   Claude / AI   │────▶│    WSL EnviDat MCP        │────▶│       envidat.ch          │
│   (MCP Host)    │◀────│    (MCP Server)           │◀────│                          │
└─────────────────┘     │                           │     │  CKAN API  (REST/JSON)   │
                        │  12 Tools · 2 Resources   │     │  Solr full-text search   │
                        │  Stdio | Streamable HTTP  │     │  1,000+ research datasets│
                        │                           │     │  815+ open datasets      │
                        │  server.py                │     │  Time series since 1890  │
                        │  api_client.py            │     └──────────────────────────┘
                        └───────────────────────────┘

Infrastructure Components

Component	Metaphor	Function
api_client.py	Librarian	Handles all HTTP requests to EnviDat CKAN API
server.py	Reception desk	Registers all 12 tools and 2 resources with FastMCP
Domain filters	Filing cabinet	Pre-configured keyword sets per research domain
Bounding box search	Map overlay	Spatial filtering via lat/lon coordinates

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Project Structure

wsl-envidat-mcp/
├── src/wsl_envidat_mcp/
│   ├── __init__.py         # Package
│   ├── server.py           # MCP server — 12 tools, 2 resources
│   └── api_client.py       # HTTP client for EnviDat CKAN API
├── tests/
│   └── test_integration.py # 11 live API integration tests
├── .github/workflows/
│   └── ci.yml              # GitHub Actions CI (Python 3.11–3.13)
├── pyproject.toml          # Project config (hatchling build backend)
├── CHANGELOG.md
├── CONTRIBUTING.md
├── LICENSE                 # MIT
├── README.md               # This file (English)
└── README.de.md            # German version

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Combination with Other MCP Servers

This server is part of the Swiss Open Data MCP Portfolio and integrates well with:

Combination	Use Case
+ zurich-opendata-mcp	Urban climate + forest condition around Zurich
+ swiss-statistics-mcp	Population data + environmental quality
+ swiss-transport-mcp	Avalanche risk + public transport connections
+ fedlex-mcp	Forest protection law + actual LFI forest condition
+ global-education-mcp	Compare environmental education data internationally

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Known Limitations

• Solr search: OR is treated as a stopword — use single, specific search terms per query
• Domain search: Results depend on WSL's internal keyword tagging — not all datasets are tagged consistently
• Spatial search: Bounding box filtering is approximate; verify coordinates with individual dataset metadata
• Live API: All tools make live calls to envidat.ch — results depend on availability of the public API
• Languages: Dataset metadata is primarily in English and German; some older entries may be in German only

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Testing

# Unit tests (no API key required, no network access)
PYTHONPATH=src pytest tests/ -m "not live"

# Integration tests (live API calls to envidat.ch)
PYTHONPATH=src pytest tests/ -m "live"

# Linting
ruff check src/

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Changelog

See CHANGELOG.md

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Contributing

See CONTRIBUTING.md

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License

MIT License — see LICENSE

Data on EnviDat is published under various open licenses (Creative Commons, CC0) — see individual dataset metadata.

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Author

Hayal Oezkan · malkreide

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Credits & Related Projects

• Data: EnviDat – WSL Swiss Federal Research Institute for Forest, Snow and Landscape
• Protocol: Model Context Protocol – Anthropic / Linux Foundation
• Portfolio: Swiss Public Data MCP Portfolio