MCP-server-typescript

MCP-server-typescript

A production-ready Model Context Protocol server built with Node.js and TypeScript, providing tool-based execution with input validation and error handling.

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MCP Server - Model Context Protocol Tool Server

A production-ready Model Context Protocol (MCP) server built with Node.js, TypeScript, and Express. This server provides a tool-based execution system with input validation, error handling, and a scalable architecture.

šŸ“‹ Table of Contents


šŸ¤” What is MCP?

Model Context Protocol (MCP) is a pattern for enabling AI assistants and other clients to execute backend tools/functions through a standardized API. Think of it as a bridge between AI models and your backend services.

How It Works:

  1. Client (AI assistant, frontend app) sends a request to the MCP server
  2. MCP Server validates the input using schemas
  3. Tool executes the requested function
  4. Response is returned in a standardized format
[AI Assistant] → POST /mcp → [MCP Server] → [Tool Execution] → [Response]

✨ Features

  • āœ… TypeScript - Full type safety
  • āœ… Express - Fast and minimal web framework
  • āœ… Zod Validation - Runtime input validation
  • āœ… Error Handling - Comprehensive error management
  • āœ… Logging - Winston logger with file and console output
  • āœ… Security - Helmet for HTTP headers, CORS support
  • āœ… Scalable Architecture - Easy to add new tools
  • āœ… Production Ready - Proper error codes, health checks

šŸ“ Folder Structure

mcp-server/
ā”œā”€ā”€ src/
│   ā”œā”€ā”€ tools/                  # Tool definitions
│   │   ā”œā”€ā”€ sum.tool.ts         # Sum tool implementation
│   │   ā”œā”€ā”€ getUser.tool.ts     # GetUser tool implementation
│   │   └── index.ts            # Tool registry
│   ā”œā”€ā”€ types/                  # TypeScript type definitions
│   │   └── tool.types.ts       # Core MCP types
│   ā”œā”€ā”€ middleware/             # Express middleware
│   │   ā”œā”€ā”€ errorHandler.ts    # Global error handler
│   │   └── logger.ts           # Winston logger configuration
│   ā”œā”€ā”€ utils/                  # Utility functions
│   │   └── validator.ts        # Input validation helper
│   ā”œā”€ā”€ server.ts               # Express app configuration
│   └── index.ts                # Server entry point
ā”œā”€ā”€ logs/                       # Log files (auto-generated)
ā”œā”€ā”€ package.json
ā”œā”€ā”€ tsconfig.json
ā”œā”€ā”€ .env.example
└── README.md

šŸš€ Installation

1. Install Dependencies

npm install

2. Set Up Environment Variables

Create a .env file in the root directory:

PORT=3000
NODE_ENV=development
LOG_LEVEL=info

3. Build the Project

npm run build

4. Start the Server

Development mode (with auto-reload):

npm run dev

Production mode:

npm start

The server will start at http://localhost:3000


šŸŽÆ Usage

Quick Start Example

Request:

curl -X POST http://localhost:3000/mcp \
  -H "Content-Type: application/json" \
  -d '{
    "tool": "sum",
    "input": {
      "a": 10,
      "b": 25
    }
  }'

Response:

{
  "success": true,
  "data": {
    "result": 35,
    "operation": "10 + 25 = 35"
  },
  "timestamp": "2026-04-24T10:30:00.000Z"
}

šŸ”Œ API Endpoints

1. Health Check

GET /health

Response:

{
  "status": "healthy",
  "timestamp": "2026-04-24T10:30:00.000Z",
  "uptime": 123.45
}

2. List Available Tools

GET /tools

Response:

{
  "success": true,
  "data": {
    "count": 2,
    "tools": [
      {
        "name": "sum",
        "description": "Adds two numbers together and returns the result"
      },
      {
        "name": "getUser",
        "description": "Retrieves a user by their ID from the database"
      }
    ]
  },
  "timestamp": "2026-04-24T10:30:00.000Z"
}

3. Execute Tool (Main MCP Endpoint)

POST /mcp
Content-Type: application/json

Request Body:

{
  "tool": "toolName",
  "input": {
    // Tool-specific input
  }
}

Success Response:

{
  "success": true,
  "data": {
    // Tool-specific output
  },
  "timestamp": "2026-04-24T10:30:00.000Z"
}

Error Response:

{
  "success": false,
  "error": {
    "code": "VALIDATION_ERROR",
    "message": "Input validation failed",
    "details": {
      "errors": [
        {
          "path": "a",
          "message": "Expected number, received string",
          "code": "invalid_type"
        }
      ]
    }
  },
  "timestamp": "2026-04-24T10:30:00.000Z"
}

šŸ› ļø Example Tools

1. Sum Tool

Adds two numbers together.

Request:

{
  "tool": "sum",
  "input": {
    "a": 15,
    "b": 30
  }
}

Response:

{
  "success": true,
  "data": {
    "result": 45,
    "operation": "15 + 30 = 45"
  },
  "timestamp": "2026-04-24T10:30:00.000Z"
}

2. GetUser Tool

Retrieves user information by ID.

Request:

{
  "tool": "getUser",
  "input": {
    "id": 1
  }
}

Response:

{
  "success": true,
  "data": {
    "id": 1,
    "name": "Alice Johnson",
    "email": "alice@example.com",
    "role": "admin",
    "createdAt": "2024-01-15T10:30:00Z"
  },
  "timestamp": "2026-04-24T10:30:00.000Z"
}

User Not Found:

{
  "success": true,
  "data": null,
  "timestamp": "2026-04-24T10:30:00.000Z"
}

āž• Adding New Tools

Creating a new tool is simple! Follow these steps:

Step 1: Create Tool File

Create src/tools/myTool.tool.ts:

import { z } from "zod";
import { MCPTool } from "../types/tool.types";

// Define input schema
const myToolInputSchema = z.object({
  name: z.string().min(1),
  age: z.number().positive(),
});

type MyToolInput = z.infer<typeof myToolInputSchema>;

interface MyToolOutput {
  message: string;
}

// Implement the tool
export const myTool: MCPTool<MyToolInput, MyToolOutput> = {
  name: "myTool",
  description: "Description of what my tool does",
  inputSchema: myToolInputSchema,

  execute: async (input: MyToolInput): Promise<MyToolOutput> => {
    // Your tool logic here
    return {
      message: `Hello ${input.name}, you are ${input.age} years old!`,
    };
  },
};

Step 2: Register the Tool

Add to src/tools/index.ts:

import { myTool } from './myTool.tool';

constructor() {
  this.registerTool(sumTool);
  this.registerTool(getUserTool);
  this.registerTool(myTool);  // ← Add your tool here
}

Step 3: Test Your Tool

curl -X POST http://localhost:3000/mcp \
  -H "Content-Type: application/json" \
  -d '{
    "tool": "myTool",
    "input": {
      "name": "John",
      "age": 25
    }
  }'

That's it! Your tool is now available in the MCP server.


šŸŒ Real-World Use Case

AI Assistant with Backend Integration

Scenario: You're building an AI customer support assistant that needs to access real backend systems.

User: "What's the status of order #12345?"
  ↓
AI Assistant: [Calls MCP server with "getOrderStatus" tool]
  ↓
MCP Server: [Validates input, queries database]
  ↓
AI Assistant: [Receives order data]
  ↓
Response: "Your order #12345 is currently being shipped and will arrive tomorrow."

Benefits:

  1. Separation of Concerns - AI logic separate from business logic
  2. Security - Validate and sanitize all AI requests
  3. Consistency - Standardized API for all AI interactions
  4. Auditability - Log all AI actions and tool executions
  5. Flexibility - Add new capabilities without modifying AI model

Example Tools for Production:

  • getOrderStatus - Check order information
  • searchProducts - Find products in inventory
  • createTicket - Create customer support tickets
  • sendEmail - Send automated emails
  • checkAvailability - Check resource availability
  • processRefund - Handle refund requests

āš ļø Error Handling

The MCP server uses standardized error codes:

Error Code HTTP Status Description
TOOL_NOT_FOUND 404 Requested tool doesn't exist
VALIDATION_ERROR 400 Input validation failed
EXECUTION_ERROR 500 Tool execution failed
INTERNAL_ERROR 500 Unexpected server error

Example Error Response:

{
  "success": false,
  "error": {
    "code": "VALIDATION_ERROR",
    "message": "Input validation failed",
    "details": {
      "errors": [
        {
          "path": "id",
          "message": "Number must be greater than 0",
          "code": "too_small"
        }
      ]
    }
  },
  "timestamp": "2026-04-24T10:30:00.000Z"
}

šŸ“Š Logging

Logs are stored in the logs/ directory:

  • combined.log - All logs
  • error.log - Error logs only

Console output is colorized for better readability during development.


šŸ” Security Features

  • Helmet - Secures HTTP headers
  • CORS - Configurable cross-origin requests
  • Input Validation - Zod schema validation for all inputs
  • Error Sanitization - Prevents sensitive data leakage

šŸ“ License

MIT


šŸ¤ Contributing

  1. Create a new tool following the patterns in src/tools/
  2. Add comprehensive input validation
  3. Include tests for your tool
  4. Update this README with examples

šŸ“ž Support

For issues or questions, please open an issue on the repository.


Happy coding! šŸš€

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