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Multi Agent Weather

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Multi Agent Weather MCP Server, understands natural language and outputs touring advice based on weather data.

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Описание

Multi Agent Weather MCP Server, understands natural language and outputs touring advice based on weather data.

README

This project is a Multi-Agent Weather MCP Coordination Platform Server designed to facilitate coordinated weather data processing, control, or simulation with multiple autonomous agents. It serves as a robust backend for orchestrating meteorological computations, simulations, or data aggregation through distributed agent systems.

Features

  • Multi-Agent Architecture: Supports concurrent operation and coordination of several agents for weather-related tasks.
  • Weather Data Processing: Acquires, processes, and analyzes meteorological data from multiple sources.
  • Extensible Communication: Plugin-friendly or API-driven agent communication framework (customizable for additional agent types).
  • Modular Components: Easily integrate new functionalities (data sources, algorithms, or output formats).
  • Real-time & Batch Modes: Choose between streaming/live data or scheduled batch processing.

Getting Started

Prerequisites

Installation

Clone this repository:

git clone https://github.com/feroake/Multi_Agent_Weather_MCP_server.git
cd Multi_Agent_Weather_MCP_server

Install dependencies:

pip install -r requirements.txt

Configuration

  • Edit config.yaml or a similar configuration file to set agent parameters, data sources, API keys, or other environment settings.
  • Environment variables may be needed for secrets like API keys.

Running the Server

To launch the Multi-Agent Weather MCP Server:

python main.py

Or use any provided start script.

Usage

  • Access the server via HTTP API, CLI, or another frontend specified in this project.
  • Integrate custom agents by extending the agents module or using the plugin interface.

Project Structure

Multi_Agent_Weather_MCP_server/
├── agents/             # Core agent implementations
├── tests/              # Automated tests
├── main.py             # Main server entry point
├── requirements.txt     # Python dependencies
├── config.yaml         # Server and agent configuration (example)
└── README.md           

Contributing

Contributions and suggestions are welcome! Please open an issue or submit a pull request. For major changes, propose your ideas in an issue to discuss first.

  1. Fork the repo
  2. Create your feature branch (git checkout -b feature/my-feature)
  3. Commit your changes (git commit -am 'Add new feature')
  4. Push to the branch (git push origin feature/my-feature)
  5. Open a Pull Request

License

Distributed under the MIT License. See LICENSE for details.

Contact

  • Author: feroake
  • For support or inquiries, please open a GitHub issue.

from github.com/feroake/Multi_Agent_Weather_MCP_server

Установка Multi Agent Weather

У этого сервера нет опубликованного пакета — он собирается из исходников. Открой репозиторий и следуй инструкции в README.

▸ github.com/feroake/Multi_Agent_Weather_MCP_server

FAQ

Multi Agent Weather MCP бесплатный?

Да, Multi Agent Weather MCP бесплатный — установка в пару кликов через Unyly без оплаты.

Нужен ли API-ключ для Multi Agent Weather?

Нет, Multi Agent Weather работает без API-ключей и переменных окружения.

Multi Agent Weather — hosted или self-hosted?

Self-hosted: сервер запускается локально на твоей машине командой из раздела установки.

Как установить Multi Agent Weather в Claude Desktop, Claude Code или Cursor?

Открой Multi Agent Weather на unyly.org, выбери вкладку своего клиента (Claude Desktop, Claude Code, Cursor) и нажми Install — конфиг сгенерируется автоматически, без правки JSON.

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