Demo MCP Basic

Name: Demo MCP Basic
Author: bertrandgressier

@bertrandgressier

代码仓库

关于 Demo MCP Basic

Demo of MCP server with HTTP SSE and a client

#mcp #client-server #ai-integration

基本信息

分类

其他

运行时

node

传输方式

stdio

发布者

bertrandgressier

配置

暂无标准配置

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代码仓库

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概览

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.

FAQ from Demo MCP Basic

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.

How does the client communicate with the server?

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

What tools does the server provide?

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

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.

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.