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Demo MCP Basic

@bertrandgressier

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作者

bertrandgressier

Demo MCP Basic について

Demo of MCP server with HTTP SSE and a client

#mcp#client-server#ai-integration

Demo MCP Basic の設定

標準の設定はありません

このサーバーの README には解析可能な MCP 設定ブロックが含まれていません。インストール手順はリポジトリをご確認ください。

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Demo MCP Basic のツール

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ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

What is Demo MCP Basic?

Demo MCP Basic demonstrates a fundamental client‑server interaction using the Model Context Protocol (MCP). The server provides simple calculation tools (addition, subtraction, etc.) and the client, using the AI SDK, connects a Google AI model (Gemini/Vertex AI) to those tools, enabling the AI to call external functionalities during text generation.

How to use Demo MCP Basic?

Clone the repository, install dependencies (npm install), and create a .env file with your Google AI API key or Vertex AI project ID. Build the project with npm run build, then start the server (npm run start:server) and the client (npm run start:client). Development modes are available via npm run dev:server and npm run dev:client.

Key features of Demo MCP Basic

  • Offers basic arithmetic tools (addition, subtraction) via MCP.
  • Connects Google Gemini or Vertex AI models to external tools.
  • Client‑server architecture with SSE transport on localhost:3001.
  • Includes both production and development run scripts.
  • Fully typed TypeScript project with automatic compilation.

Use cases of Demo MCP Basic

  • Extending AI models with custom calculation tools.
  • Prototyping MCP‑based tool integrations for AI applications.
  • Learning how to implement an MCP client and server.
  • Demonstrating secure, local tool invocation from an AI model.

よくある質問

1

What runtime dependencies does Demo MCP Basic require?

Node.js version 23.0 or higher and npm (bundled with Node.js). A Google AI API key (for Gemini) or a Vertex AI project ID is required.

2

How does the client communicate with the server?

The client connects to the server via SSE (Server‑Sent Events) at `http://localhost:3001/sse`.

3

What tools does the server provide?

The server exposes simple calculation tools, specifically addition and subtraction (and potentially other basic arithmetic operations).

4

Where does the application data live?

All configuration (API keys, project IDs) is stored locally in a `.env` file. No external databases are used; the server runs locally and communicates with Google’s AI services over HTTPS.

5

Are there any known limitations?

The server only offers basic arithmetic tools. The client is a demonstration script hard‑coded to evaluate `"6 + 12"` and relies on the AI model correctly invoking the tool. No authentication or secure transport beyond SSE is implemented.

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