Weather Server MCP: Real-Time Precision & Unmatched Reliability

Key Features of Weather Server MCP: Real-Time Precision & Unmatched Reliability?

• Temporal Consistency: Versioned resources ensure audit trails for temperature fluctuations
• API Agnostic: Supports pluggable connectors beyond OpenWeatherMap via tool middleware
• Stateful Intelligence: Caches 7-day forecast windows to optimize LLM prompt efficiency
• Debugging Stack: MCP Inspector provides network traffic visualization and error tracing via this toolchain

Use Cases of Weather Server MCP: Real-Time Precision & Unmatched Reliability?

Enterprise implementations span:
• Disaster Response: Real-time storm tracking with embedded radar imagery URIs
• Smart Agriculture: Hydration forecasts driving IoT valve automation
• Travel Tech: Dynamic itinerary adjustments based on pollen counts and UV indices
• Climate Research

FAQ from Weather Server MCP: Real-Time Precision & Unmatched Reliability?

Q: How does reliability manifest in distributed setups?
A: Built-in retry logic with exponential backoff for API calls, coupled with eventual consistency guarantees via CRDT patterns.

Q: Can this handle multi-tenant environments?
A: Yes – location parameters are schema validated to prevent cross-tenant data leaks, with optional RBAC via custom middleware.

Q: What ensures prompt generation accuracy?
A: The summarize_weather tool injects timestamped metadata for temporal context, while schema validation prevents malformed data from reaching LLMs.

Weather 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.