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Simple MCP Server & Client Sample (with Gemini Function Calling)

@yokoba

リポジトリ

基本情報

カテゴリ

AI とエージェント

ライセンス

MIT

トランスポート

stdio

作者

yokoba

Simple MCP Server & Client Sample について

Simple MCP Server & Client Sample (with Gemini Function Calling)

#mcp#server#client#gemini#function-calling

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概要

What is Simple MCP Server & Client Sample (with Gemini Function Calling)?

This repository provides minimal examples of an MCP (Model Context Protocol) server and client. It demonstrates how to let a Gemini LLM automatically select which tool to call using function calling, based on context such as time of day.

How to use Simple MCP Server & Client Sample (with Gemini Function Calling)?

Install dependencies with uv init, uv add google-genai, uv add fastmcp. Set the GEMINI_API_KEY environment variable. Run python mcp_simple_client1.py for a basic client or python mcp_simple_client2.py for the Gemini‑integrated client that automatically chooses between the greet and farewell tools.

Key features of Simple MCP Server & Client Sample (with Gemini Function Calling)

  • Minimal MCP server and client implementations
  • Gemini function calling automatically selects tools
  • Two sample tools: greet and farewell
  • Built with the fastmcp and google-genai libraries
  • Works with Python 3.10+ and recommended uv for speed

Use cases of Simple MCP Server & Client Sample (with Gemini Function Calling)

  • Learning the minimum structure of an MCP server and client
  • Demonstrating how an LLM (Gemini) can call different tools based on context
  • Starting point for quickly building custom MCP‑powered AI agents

よくある質問

1

What is MCP?

Model Context Protocol (MCP) is a protocol that lets machine learning models or AI agents call external tools (APIs).

2

What is the purpose of this repository?

It provides a minimal MCP server and client sample, and shows how to let a Gemini LLM automatically choose which tool to call based on time of day.

3

What are the runtime requirements?

Python 3.10 or later, fastmcp >= 2.5.2, google-genai >= 1.18.0, and a Gemini API key set as the environment variable `GEMINI_API_KEY`. Using `uv` is recommended but not required.

4

Are there any limitations or cautions?

The code prioritises simplicity and omits error handling and exception processing. For production use, add proper validation, logging, and error handling.

5

What license applies?

The code is offered freely under the MIT License. It is a memo/sample; use it at your own responsibility.

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