Other MCP Server · MODEL CONTEXT PROTOCOL

eternachen mcp playground

mcp playground

连接能力

eternachen mcp playground 为 AI Agent 提供什么

  • Connects to an MCP server to list available tools.
  • Queries weather information for a specified city.
  • Displays formatted weather information including temperature, humidity, wind speed, and weather description.
  • Python 3.8+
  • `openai` library
  • `dotenv` library
  • `mcp` library
  • Clone the repository:
  • Create a virtual environment and activate it:
  • Install the required dependencies:
  • Create a `.env` file in the root directory and add your OpenAI API key and other configurations:
  • Start the MCP server:
  • Run the client and connect to the server:
  • Interact with the client:
  • Type the name of the city in English to get the weather information.
  • Type `quit` to exit the client.
  • `server.py`: Contains the MCP server implementation and weather query tool.
  • `client.py`: Contains the MCP client implementation to interact with the server.
  • `.env`: Environment variables for API keys and configurations.
  • `.gitignore`: Specifies files and directories to be ignored by git.
  • `README.md`: Project documentation.

安全

MCP 收录不等于安全审核

MCP 服务器可能获得模型上下文、凭据、本地文件或调用外部系统的权限。连接 Agent 前,请检查代码、环境变量、网络行为、软件包来源与维护状态。

README

仓库文档

Weather Query MCP Server/Client Example

This project is a weather query client that interacts with an MCP (Model-Client-Protocol) server to fetch and display weather information for a specified city.

Features

  • Connects to an MCP server to list available tools.
  • Queries weather information for a specified city.
  • Displays formatted weather information including temperature, humidity, wind speed, and weather description.

Requirements

  • Python 3.8+
  • openai library
  • dotenv library
  • mcp library

Setup

  1. Clone the repository:

    git clone <repository_url>
    cd <repository_directory>
  2. Create a virtual environment and activate it:

    python -m venv .venv
    source .venv/bin/activate  # On Windows use `.venv\Scripts\activate`
  3. Install the required dependencies:

    pip install -r requirements.txt
  4. Create a .env file in the root directory and add your OpenAI API key and other configurations:

    OPENAI_API_KEY=<your_openai_api_key>
    BASE_URL=<your_base_url>
    MODEL=<your_model>

Usage

  1. Start the MCP server:

    python server.py
  2. Run the client and connect to the server:

    python client.py <path_to_server_script>
  3. Interact with the client:

    • Type the name of the city in English to get the weather information.
    • Type quit to exit the client.

Project Structure

  • server.py: Contains the MCP server implementation and weather query tool.
  • client.py: Contains the MCP client implementation to interact with the server.
  • .env: Environment variables for API keys and configurations.
  • .gitignore: Specifies files and directories to be ignored by git.
  • README.md: Project documentation.

License

This project is licensed under the MIT License.

在 GitHub 查看 README

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