About Weather Server MCP Server
Weather Server MCP Server is a TypeScript MCP server for weather data. It provides weather resources, tools to fetch and update information, and a prompt for generating summaries.
Key features
- 01Access weather data through weather:// URIs
- 02Read structured weather resources in JSON
- 03Fetch current weather for a location
- 04Update weather data in server state
- 05Generate summaries with embedded weather resources
Use cases
- 01Reading weather entries for a location
- 02Fetching current conditions from the external API
- 03Updating stored weather information
- 04Creating a weather summary for an LLM
MCP support
Exposes weather resources, fetch and update tools, and a summarization prompt to MCP clients.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMEWeather Server MCP Server
Test weather server tool
This is a TypeScript-based MCP server that implements a weather information system. It demonstrates core MCP concepts by providing:
- Resources representing weather data with URIs and metadata
- Tools for fetching and updating weather information
- Prompts for generating weather summaries
Features
Resources
- List and access weather data via
weather://URIs - Each weather entry has a location, temperature, and metadata
- JSON mime type for structured data access
Tools
-
fetch_weather- Fetch current weather information- Takes location as a required parameter
- Retrieves weather data from an external API
-
update_weather- Update weather information- Takes location and new weather data as required parameters
- Updates the weather data in server state
Prompts
summarize_weather- Generate a summary of the current weather data- Includes all weather entries as embedded resources
- Returns structured prompt for LLM summarization
Development
Install dependencies:
npm install
Rename .envexample to .env:
mv .envexample .env
Update OPENWEATHER_API_KEY in the .env file:
OPENWEATHER_API_KEY=Your_Own_OpenWeather_API_KEY
Build the server:
npm run build
For development with auto-rebuild:
npm run watch
Installation
To use with Claude Desktop, add the server config:
On MacOS: ~/Library/Application Support/Claude/claude_desktop_config.json
On Windows: %APPDATA%/Claude/claude_desktop_config.json
{
"mcpServers": {
"weatherserver": {
"command": "/path/to/weatherserver/build/index.js"
}
}
}
Debugging
Since MCP servers communicate over stdio, debugging can be challenging. We recommend using the MCP Inspector, which is available as a package script:
npm run inspector
The Inspector will provide a URL to access debugging tools in your browser.
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.