Client Server Project Using Nodejs
A minimal Model Context Protocol (MCP) implementation built with Node.js and TypeScript. This project demonstrates client–server communication over stdio, structured message handling, and local data access, developed with VS Code and GitHub Copilot to explore modern AI tool integration workflows.
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Simple MCP with Node.js & TypeScript
This project is a minimal, educational implementation of a Model Context Protocol (MCP)–style system using Node.js and TypeScript. It demonstrates how a client and server can communicate over standard input/output (stdio) using structured messages, simulating how modern AI tools interact with external context providers.
The project was built using VS Code with GitHub Copilot, exploring how AI-assisted development integrates with protocol-based system design.
🚀 What This Project Demonstrates
- A lightweight MCP-style client–server architecture
- Communication over stdio instead of HTTP
- Structured request/response handling
- Type-safe development with TypeScript
- Local JSON-based data access
- Practical experimentation with AI tooling workflows
This repository focuses on clarity over complexity, making it ideal for learning, experimentation, and extension.
🧠 Architecture Overview
Client (client.ts)
|
| stdio messages
v
Server (server.ts)
|
| Reads local data
v
users.json
- Client sends structured requests
- Server processes requests and responds via stdio
- users.json acts as a mock data source
- mcp.json defines how the MCP server is launched and integrated
📁 Project Structure
├── client.ts # MCP client implementation
├── server.ts # MCP server implementation
├── users.json # Sample data source
├── mcp.json # MCP server configuration
├── package.json
├── package-lock.json
└── README.md
⚙️ How It Works
- The MCP server is launched using Node.js (configured in
mcp.json) - The client communicates with the server via stdio
- Requests are parsed and handled in a structured manner
- The server reads from
users.jsonand returns results - Responses are sent back to the client in a predictable format
This mirrors how AI tools query external systems for context without relying on traditional REST APIs.
▶️ Running the Project
Install dependencies
npm install
npm run build
node build/server.js
(Client execution depends on your MCP setup or test harness.)
🧪 Why This Matters
Modern AI systems increasingly rely on protocol-driven context sharing rather than monolithic APIs. This project provides a hands-on foundation for understanding:
- AI tool integrations
- Context-aware systems
- Protocol-oriented backend design
- Developer tooling workflows
📌 Notes
- This is a learning and exploration project
- Designed to be easily extended (databases, auth, tools, schemas)
- Emphasizes readability and correctness over feature depth
