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Gemini API with MCP Tool Integration

@hitechdk

代码仓库

基本信息

分类

AI 与智能体

许可证

MIT license

传输方式

stdio

作者

hitechdk

关于 Gemini API with MCP Tool Integration

AI agent that retrieves weather data from the MCP server to provide automated forecasts. Ideal for integration into weather-related applications.

#weather-ai#weather-forecast#gemini-api

Gemini API with MCP Tool Integration 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "weather-ai-agent": {
      "command": "python3",
      "args": [
        "-m",
        "venv",
        "venv"
      ]
    }
  }
}

Gemini API with MCP Tool Integration 工具

工具列表暂未提供

当前收录暂时没有可展示的工具列表，不代表服务没有工具。请查阅项目文档了解支持的能力。

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

What is Gemini API with MCP Tool Integration?

This project integrates the Google Gemini API with custom tools managed by the MCP (Multi-Cloud Platform) framework. It processes natural language queries via Gemini and executes specific actions based on query intent using MCP tools.

How to use Gemini API with MCP Tool Integration?

Install Python 3.7+, set up a Google Cloud project with Gemini API enabled, configure a .env file with GEMINI_API_KEY, GEMINI_MODEL, MCP_RUNNER, and MCP_SCRIPT, then run python main.py. Customize prompt, get_contents(), and process_response() as needed.

Key features of Gemini API with MCP Tool Integration

  • Integrates Google Gemini API with MCP custom tools
  • Uses environment variables for configuration
  • Processes tool calls made by the model
  • Supports customizable prompt and response handling
  • Automates actions based on natural language queries

Use cases of Gemini API with MCP Tool Integration

  • Automating cloud tasks through natural language commands
  • Building AI assistants that trigger external tools
  • Prototyping applications combining Gemini with MCP-based services
  • Enabling conversational interfaces with backend action execution

常见问题

1

What is the purpose of this integration?

It demonstrates how to combine the Gemini API with MCP framework tools to interpret natural language and perform corresponding actions.

2

What are the prerequisites?

Python 3.7+, a Google Cloud project with the Gemini API enabled, an API key, and an MCP environment with the necessary tools.

3

How do I install the required dependencies?

Use `uv` to install `dotenv`, `google-generativeai`, `mcp`, and other packages as listed in the README.

4

How do I run the application?

After setting up the `.env` file, execute `python main.py` from the project root.

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