Proyecto Cliente MCP con Gemini y Servidor de Herramientas Meteorológicas
@Karlheinzniebuhr
关于 Proyecto Cliente MCP con Gemini y Servidor de Herramientas Meteorológicas
暂无概览
基本信息
配置
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"MCP-Server-Client-Demo-with-Gemini": {
"command": "python",
"args": [
"mcp_gemini_client.py",
"weather_tool_server.py"
]
}
}
}工具
未检测到工具
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 Proyecto Cliente MCP con Gemini y Servidor de Herramientas Meteorológicas?
This project demonstrates how to use the Model Context Protocol (MCP) to connect a Google Gemini AI client with a specialized server that provides weather tools (get_alerts, get_forecast). It acts as a bridge between the AI and external data, handling user input and tool execution.
How to use Proyecto Cliente MCP con Gemini y Servidor de Herramientas Meteorológicas?
Install dependencies with pip install -r requirements.txt, create a .env file with a Gemini API key (GEMINI_API_KEY=your_key), then run python mcp_gemini_client.py weather_tool_server.py. Type weather queries in the terminal when prompted.
Key features of Proyecto Cliente MCP con Gemini y Servidor de Herramientas Meteorológicas
- Gemini AI decides when to call weather tools.
- Standardized MCP communication between client and server.
- Two weather tools: get_alerts and get_forecast.
- Detailed logging of all interactions in
mcp_log.txt. - Lightweight setup with minimal dependencies.
Use cases of Proyecto Cliente MCP con Gemini y Servidor de Herramientas Meteorológicas
- Ask for the current weather forecast in natural language.
- Request weather alerts for a specific location.
- Learn how MCP connects AI agents with external tools.
- Debug AI-tool interaction flow using comprehensive logs.
FAQ from Proyecto Cliente MCP con Gemini y Servidor de Herramientas Meteorológicas
What is the Model Context Protocol (MCP)?
MCP is the standardized communication protocol that lets the client discover and call tools on the server, handling messaging between both sides.
What credentials are required?
A Gemini API key from Google AI Studio must be saved in a .env file as GEMINI_API_KEY.
What tools does the weather server provide?
Two tools: get_alerts and get_forecast, each with their own schema and description.
How do I see the full communication flow?
A detailed log is written to mcp_log.txt, showing every message between the client, Gemini API, and server, including prompts and tool results.
What are the system requirements?
Python 3 with packages google-generativeai, python-dotenv, and the MCP protocol libraries (installed via requirements.txt).
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