Cover image
Try Now
2025-04-04

从MCP服务器检索天气数据以提供自动预测的AI代理。集成到天气相关的应用中的理想选择。

3 years

Works with Finder

1

Github Watches

0

Github Forks

0

Github Stars

Gemini API with MCP Tool Integration

This project demonstrates how to integrate the Google Gemini API with custom tools managed by the MCP (Multi-Cloud Platform) framework. It uses the Gemini API to process natural language queries, and leverages MCP tools to execute specific actions based on the query's intent.

Prerequisites

Before running this project, ensure you have the following:

  • Python 3.7 or higher

  • A Google Cloud project with the Gemini API enabled and an API key.

  • An MCP environment set up with the necessary tools.

  • .env file with the following environment variables:

    GEMINI_API_KEY=<your_gemini_api_key>
    GEMINI_MODEL=<your_gemini_model_name>
    MCP_RUNNER=<path_to_mcp_runner>
    MCP_SCRIPT=<path_to_mcp_script>
    

Installation

  1. Clone the repository:

    git clone <repository_url>
    cd <repository_directory>
    
  2. Create a virtual environment (recommended):

    python3 -m venv venv
    source venv/bin/activate  # On macOS/Linux
    
    
  3. Install the required dependencies using uv:

    uv pip install dotenv google-generativeai mcp
    uv add "mcp[cli]" httpx
    uv pip install python-dotenv google-generativeai mcp
    
  4. Create a .env file in the project root and add your environment variables.

GEMINI_API_KEY=your_api_key_here
GEMINI_MODEL=gemini-pro
MCP_RUNNER=path_to_mcp_runner
MCP_SCRIPT=path_to_mcp_script

Usage

To run the application, execute the following command:

python main.py

How It Works

  1. The application loads environment variables and validates their presence
  2. Establishes a connection with the MCP client
  3. Retrieves available tools from the MCP session
  4. Sends the prompt to Gemini's API along with tool definitions
  5. Processes any tool calls made by the model
  6. Returns the final response that includes results from tool calls

Customization

To customize the prompt or behavior:

  1. Modify the prompt variable with your desired text
  2. Adjust the get_contents() function to change how prompts are formatted
  3. Extend process_response() to handle different response types

License

MIT License

相关推荐

  • Joshua Armstrong
  • Confidential guide on numerology and astrology, based of GG33 Public information

  • https://suefel.com
  • Latest advice and best practices for custom GPT development.

  • Alexandru Strujac
  • Efficient thumbnail creator for YouTube videos

  • Emmet Halm
  • Converts Figma frames into front-end code for various mobile frameworks.

  • lumpenspace
  • Take an adjectivised noun, and create images making it progressively more adjective!

  • Elijah Ng Shi Yi
  • Advanced software engineer GPT that excels through nailing the basics.

  • Lists Tailwind CSS classes in monospaced font

  • https://maiplestudio.com
  • Find Exhibitors, Speakers and more

  • tomoyoshi hirata
  • Sony α7IIIマニュアルアシスタント

  • Yusuf Emre Yeşilyurt
  • I find academic articles and books for research and literature reviews.

  • Carlos Ferrin
  • Encuentra películas y series en plataformas de streaming.

  • apappascs
  • 发现市场上最全面,最新的MCP服务器集合。该存储库充当集中式枢纽,提供了广泛的开源和专有MCP服务器目录,并提供功能,文档链接和贡献者。

  • ShrimpingIt
  • MCP系列GPIO Expander的基于Micropython I2C的操作,源自ADAFRUIT_MCP230XX

  • jae-jae
  • MCP服务器使用剧作《无头浏览器》获取网页内容。

  • HiveNexus
  • 一个适用于中小型团队的AI聊天机器人,支持DeepSeek,Open AI,Claude和Gemini等车型。 专为中小团队设计的ai聊天应用,支持deepSeek,打开ai,claude,双子座等模型。

  • ravitemer
  • 一个功能强大的Neovim插件,用于管理MCP(模型上下文协议)服务器

  • patruff
  • Ollama和MCP服务器之间的桥梁,使本地LLMS可以使用模型上下文协议工具

  • pontusab
  • 光标与风浪冲浪社区,查找规则和MCP

  • JackKuo666
  • 🔍使AI助手可以通过简单的MCP接口搜索和访问PYPI软件包信息。

  • av
  • 毫不费力地使用一个命令运行LLM后端,API,前端和服务。

    Reviews

    3 (1)
    Avatar
    user_dlccgN7j
    2025-04-18

    The Weather-AI-Agent by hitechdk is a phenomenal tool for anyone interested in accurate and up-to-date weather information. Its innovative approach leverages AI to deliver precise forecasts and insights. The user interface is intuitive, and the support from the developer is commendable. As someone who relies heavily on weather updates, this agent has greatly enhanced my planning and decision-making processes. Highly recommend checking it out on GitHub!