weather-server MCP Server: Real-Time Insights, Scalable Predictions

weather-server MCP Server: Unmatched real-time weather insights, scalable for any climate challenge. Power精准预测 and data-driven decisions like never before. #WeatherTech

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About weather-server MCP Server

What is weather-server MCP Server: Real-Time Insights, Scalable Predictions?

weather-server MCP Server is a TypeScript-based implementation of the Model Context Protocol (MCP), designed to demonstrate core MCP concepts through a note-taking system. It enables real-time interaction with textual data via standardized resources, tools for content creation, and structured prompts for advanced analysis. The server provides a framework for managing notes as URI-addressable resources with metadata, while supporting scalable operations through its modular architecture.

How to use weather-server MCP Server: Real-Time Insights, Scalable Predictions?

Start by installing dependencies with npm install, then build the server using npm run build. For active development, run npm run watch to enable auto-rebuilding. To integrate with Claude Desktop, configure the server path in the claude_desktop_config.json file under your OS-specific directory. External debugging is supported via the MCP Inspector tool, accessible via npm run inspector, which provides browser-based diagnostics.

weather-server MCP Server Features

Key Features of weather-server MCP Server: Real-Time Insights, Scalable Predictions?

Resource Management: Access notes via note:// URIs with metadata, supporting plain text content retrieval
Creation Tools: The create_note tool enables programmatic note creation with required title and content parameters
Analytics Prompts: The summarize_notes capability generates structured prompts for LLM-based summarization of all stored notes
Development Workflow: Built-in hot-reloading and debug support via stdio-based communication

Use cases of weather-server MCP Server: Real-Time Insights, Scalable Predictions?

Primarily used for:

Real-time data orchestration in model-driven applications
Context management for AI workflows requiring persistent state
Scalable note-taking systems with embedded analysis capabilities
Prototyping MCP-compliant server architectures for custom use cases

weather-server MCP Server FAQ

FAQ from weather-server MCP Server: Real-Time Insights, Scalable Predictions?

Q: How do I debug communication issues?
A: Use the MCP Inspector tool for visual debugging
Q: Does it support concurrent note operations?
A: Yes, the server maintains stateful resources with thread-safe operations
Q: Can I extend the prompt system?
A: Absolutely, the prompt structure is designed for customization through plugin development
Q: What platforms are supported?
A: Works on macOS and Windows with compatible configuration paths

Content

weather-server MCP Server

A Model Context Protocol server

This is a TypeScript-based MCP server that implements a simple notes system. It demonstrates core MCP concepts by providing:

Resources representing text notes with URIs and metadata
Tools for creating new notes
Prompts for generating summaries of notes

Features

Resources

List and access notes via note:// URIs
Each note has a title, content and metadata
Plain text mime type for simple content access

Tools

create_note - Create new text notes
- Takes title and content as required parameters
- Stores note in server state

Prompts

summarize_notes - Generate a summary of all stored notes
- Includes all note contents as embedded resources
- Returns structured prompt for LLM summarization

Development

Install dependencies:

npm install

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": {
    "weather-server": {
      "command": "/path/to/weather-server/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.

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