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(Demo) MCP Server for MeteoSwiss Data

(Demo) MCP Server for MeteoSwiss Data

by eins78

289 downloads

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GitHub

Description

# (Demo) MCP Server for MeteoSwiss Data A Model Context Protocol (MCP) server for MeteoSwiss weather data. ## Overview This server provides weather data from MeteoSwiss using the [Model Context Protocol](https://github.com/modelcontextprotocol/typescript-sdk) (MCP), allowing AI…

About

Details

Author: eins78
Downloads: 289
Categories: Web Scraping, Other, Search

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 (Demo) MCP Server for MeteoSwiss Data

Command (node, npx, python, etc.)

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": {
        "(demo) mcp server for meteoswiss data": {
            "mcp-server-meteoswiss": {
                "command": "npx",
                "args": [
                    "mcp-remote",
                    "http://localhost:3000/mcp"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "(demo) mcp server for meteoswiss data": {
            "mcp-server-meteoswiss": {
                "command": "npx",
                "args": [
                    "mcp-remote",
                    "http://localhost:3000/mcp"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "(demo) mcp server for meteoswiss data": {
            "mcp-server-meteoswiss": {
                "command": "npx",
                "args": [
                    "mcp-remote",
                    "http://localhost:3000/mcp"
                ]
            }
        }
    }
}

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": {
        "(demo) mcp server for meteoswiss data": {
            "mcp-server-meteoswiss": {
                "command": "npx",
                "args": [
                    "mcp-remote",
                    "http://localhost:3000/mcp"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "(demo) mcp server for meteoswiss data": {
            "mcp-server-meteoswiss": {
                "command": "npx",
                "args": [
                    "mcp-remote",
                    "http://localhost:3000/mcp"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "(demo) mcp server for meteoswiss data": {
            "mcp-server-meteoswiss": {
                "command": "npx",
                "args": [
                    "mcp-remote",
                    "http://localhost:3000/mcp"
                ]
            }
        }
    }
}

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": {
        "(demo) mcp server for meteoswiss data": {
            "mcp-server-meteoswiss": {
                "command": "npx",
                "args": [
                    "mcp-remote",
                    "http://localhost:3000/mcp"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "(demo) mcp server for meteoswiss data": {
            "mcp-server-meteoswiss": {
                "command": "npx",
                "args": [
                    "mcp-remote",
                    "http://localhost:3000/mcp"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "(demo) mcp server for meteoswiss data": {
            "mcp-server-meteoswiss": {
                "command": "npx",
                "args": [
                    "mcp-remote",
                    "http://localhost:3000/mcp"
                ]
            }
        }
    }
}

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": {
        "(demo) mcp server for meteoswiss data": {
            "mcp-server-meteoswiss": {
                "command": "npx",
                "args": [
                    "mcp-remote",
                    "http://localhost:3000/mcp"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "(demo) mcp server for meteoswiss data": {
            "mcp-server-meteoswiss": {
                "command": "npx",
                "args": [
                    "mcp-remote",
                    "http://localhost:3000/mcp"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "(demo) mcp server for meteoswiss data": {
            "mcp-server-meteoswiss": {
                "command": "npx",
                "args": [
                    "mcp-remote",
                    "http://localhost:3000/mcp"
                ]
            }
        }
    }
}

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": {
        "(demo) mcp server for meteoswiss data": {
            "mcp-server-meteoswiss": {
                "command": "npx",
                "args": [
                    "mcp-remote",
                    "http://localhost:3000/mcp"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "(demo) mcp server for meteoswiss data": {
            "mcp-server-meteoswiss": {
                "command": "npx",
                "args": [
                    "mcp-remote",
                    "http://localhost:3000/mcp"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "(demo) mcp server for meteoswiss data": {
            "mcp-server-meteoswiss": {
                "command": "npx",
                "args": [
                    "mcp-remote",
                    "http://localhost:3000/mcp"
                ]
            }
        }
    }
}

From the repository

Install Node.js v18+ and pnpm, clone the repository, run pnpm install, then start with pnpm start. The server runs on port 3000 as an HTTP service with SSE. To integrate with Claude Desktop, use npx mcp-remote http://localhost:3000/mcp. Environment variables allow customisation of port, public URL, test fixtures, and session limits.

Claude Desktop / Cursor

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

{
    "mcpServers": {
        "(demo) mcp server for meteoswiss data": {
            "mcp-server-meteoswiss": {
                "command": "npx",
                "args": [
                    "mcp-remote",
                    "http://localhost:3000/mcp"
                ]
            }
        }
    }
}

McpServers

{
    "mcp-server-meteoswiss": {
        "command": "npx",
        "args": [
            "mcp-remote",
            "http://localhost:3000/mcp"
        ]
    }
}

Provides weather reports, search, and content from the MeteoSwiss website with multi-language support.

Swiss weather data for AI assistants — powered byMeteoSwiss Open Government Data (OGD), the same data behind the MeteoSwiss app and website. Free, no API key required.

meteoswiss-mcp.ars.is— try the hosted service instantly, no setup needed.

This repo is also a working answer to a design question:how should you give AI agents access to a public dataset?It implements the same MeteoSwiss data access twice — as an agent skill(markdown instructions plus bash scripts, no server) and as an MCP server(structured tools, fuzzy matching, caching, hosted). The two approaches are compared honestly in the skill vs. MCP case study.

A third piece,meteoswiss-forecast-evals, demonstrates eval-driven interface design: a promptfoosuite measuring how well 13 LLMs read the forecast JSON, which settled a real design decision — local-time timestamps beat UTC, with hour-level lookups scoring ~100% vs. ~0%.

- Multi-day forecastsfor ~6000 Swiss locations (postal codes, stations, place names)
- Real-time measurementsfrom ~300 stations (~160 full weather + ~140 precipitation-only), updated every 10 minutes
- Station discoveryby name, canton, or GPS coordinates
- Pollen monitoringfrom ~15 stations across Switzerland
- Climate seriesfrom the National Basic Climatic Network (NBCN), going back decades
- MeteoSwiss websitesearch and content retrieval

- An agent skill— teach an agent to fetch open data directly withcurl/awk/jq: ~630 lines of markdown and bash, zero infrastructure. →packages/meteoswiss-skills
- An MCP server— the same data as structured, validated tools with fuzzy station matching, geocoding, TTL-tiered caching, a real test suite, Docker, and a hosted instance. →packages/meteoswiss-mcp
- Eval-driven interface design— treat tool output as an interface for a language model, and measure its legibility before shipping. →packages/meteoswiss-forecast-evals

Read the comparison:Skill vs. MCP Server: Two Ways to Give AI Agents the Same Data.

Both approaches answer the same weather questions. Which to install depends on your agent:

Full comparison — parity matrix, engineering trade-offs, context cost, when to choose which:docs/skill-vs-mcp.md.

Use the hosted instance (no installation):

# Claude Code claude mcp add meteoswiss https://meteoswiss-mcp.ars.is/mcp

ForCursor, install from the Cursor Directoryor add manually via Settings → MCP.

docker run -p 3000:3000 ghcr.io/eins78/meteoswiss-mcp:latest

See the meteoswiss-mcp READMEfor Claude Desktop setup, environment variables, and full documentation.

Install via the Claude Code plugin marketplace:

/plugin marketplace add eins78/meteoswiss-llm-tools /plugin install meteoswiss-skills@meteoswiss-marketplace

pnpx skills add https://github.com/eins78/meteoswiss-llm-tools.git#packages/meteoswiss-skills --global --agent claude-code --all

See the meteoswiss-skills READMEfor manual installation and details.

Works with both approaches — just ask in any of Switzerland's four languages:

- "What's the weather forecast for Zurich this week?"
- "Wie wird das Wetter in Bern morgen?"
- "Quelle est la météo à Genève?"
- "Che tempo fa a Lugano?"

- Skill vs. MCP case study— the honest comparison of the two approaches
- Eval results: forecast JSON comprehension— the local-time-vs-UTC sweep
- MCP server user guide
- Documentation index

git clone https://github.com/eins78/meteoswiss-llm-tools.git cd meteoswiss-llm-tools nvm use && pnpm install

See each package's README for package-specific commands. The repo uses changesetsfor versioning.

Manual, point-in-time test reports (e.g. live MCP tool test passes) live indocs/test-reports/.

All weather data comes from MeteoSwiss Open Government Data (OGD)— the official free data offering from Switzerland's Federal Office of Meteorology and Climatology. The same data powers the MeteoSwiss app and website.

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Install

{
    "mcpServers": {
        "(demo) mcp server for meteoswiss data": {
            "mcp-server-meteoswiss": {
                "command": "npx",
                "args": [
                    "mcp-remote",
                    "http://localhost:3000/mcp"
                ]
            }
        }
    }
}

Description

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Setting up with Highlight

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Claude Desktop / Cursor

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