MCP Boilerplate

MCP boilerplate: Model Context Protocol Server

This server implements the Model Context Protocol (MCP) for global use as a boilerplate. It provides a standardized way to connect AI models to different data sources and tools using the Model Context Protocol.

Features

Implements the MCP Server-Sent Events (SSE) transport
Provides a robust structure for building custom MCP servers
Includes example tools with proper type definitions
Secure authentication with API key
Logging capabilities with different severity levels
Session management for multiple client connections
Graceful shutdown handling for SIGINT and SIGTERM signals

Tools

The server currently includes the following example tool:

calculator: Performs basic arithmetic operations (add, subtract, multiply, divide)

For information on how to add your own custom tools, check out the Extending the Boilerplate section.

Configuration

The server configuration is centralized in src/config.ts. This makes it easy to adjust settings without modifying multiple files.

// Essential configuration options
export const config = {
  server: {
    name: "mcp-boilerplate",
    version: "1.0.0",
    port: parseInt(process.env.PORT || "4005"),
    host: process.env.HOST || "localhost",
    apiKey: process.env.API_KEY || "dev_key",
  },
  sse: {
    // How often to send keepalive messages (in milliseconds)
    keepaliveInterval: 30000,
    // Whether to send ping events in addition to comments
    usePingEvents: true,
    // Initial connection message
    sendConnectedEvent: true,
  },
  tools: {
    // Number of retries for failed tool executions
    maxRetries: 3,
    // Delay between retries (in milliseconds)
    retryDelay: 1000,
    // Whether to send notifications about tool execution status
    sendNotifications: true,
  },
  logging: {
    // Default log level
    defaultLevel: "debug",
    // How often to send log messages (in milliseconds)
    logMessageInterval: 10000,
  },
};

Troubleshooting SSE Timeouts

If you're experiencing "Body timeout error" with your MCP connection:

Decrease keepaliveInterval to send more frequent keepalive messages (e.g., 15000ms)
Ensure usePingEvents is enabled for additional connection stability
Check for any proxy timeouts if you're using a proxy server

Setup

Install dependencies:

npm install

Create a .env file with the following variables:

PORT=4005
API_KEY=your_api_key

Build the project:

npm run build

Start the server:

npm run start:sse

Development

# Start in development mode with hot reloading
npm run start

# Start with PM2 for production
npm run start:pm2

# Development mode with nodemon
npm run dev

API Endpoints

/health: Health check endpoint that returns server status and version
/sse: SSE endpoint for establishing MCP connections (requires API key)
/messages: Message handling endpoint for client-server communication

MCP Configuration

To connect to this MCP server from different clients, use the appropriate configuration below:

Cursor, Windsurf, and other SSE-supporting clients

{
  "mcpServers": {
    "mcp-server": {
      "url": "http://localhost:4005/sse?API_KEY={{your_api_key_here}}"
    }
  }
}

Claude Desktop

{
  "mcpServers": {
    "mcp-server": {
      "command": "npx",
      "args": [
        "mcp-remote",
        "http://localhost:4005/sse?API_KEY={{your_api_key_here}}"
      ]
    }
  }
}

Extending the boilerplate

Adding Custom Tools

Follow these steps to add a new tool to the MCP server:

Create your tool handler:
- Add your new tool handler in src/tools.ts file or create a new file in the src/tools directory
- The tool should follow the ToolHandler interface
Configure your tool:
- Add your tool configuration to the toolConfigs array in src/tools.ts
- Define the name, description, input schema, and handler for your tool
Export and register your tool:
- If you created a separate file, export your handler and import it in src/tools.ts
- Make sure your tool is properly registered in the toolConfigs array

Example:

// In src/tools.ts (adding directly to the toolConfigs array)
{
  name: "myTool",
  description: "My tool description",
  inputSchema: {
    type: "object" as const,
    properties: {},
    required: [],
  },
  handler: async () => {
    return createSuccessResult({ result: "Tool result" });
  },
}

Error Handling

The server implements comprehensive error handling:

All operations are wrapped in try/catch blocks
Proper validation for parameters and inputs
Appropriate error messages for better debugging
Helper functions for creating standardized error and success responses

Security Considerations

API key authentication for all connections
Type validation for all parameters
No hard-coded sensitive information
Proper error handling to prevent information leakage
Session-based transport management

MCP Protocol Features

This boilerplate supports the core MCP features:

Tools: List and call tools with proper parameter validation
Logging: Various severity levels (debug, info, notice, warning, error, critical, alert, emergency)
Server configuration: Name, version, and capabilities

Session Management

The server manages client sessions through:

Unique session IDs for each client connection
Tracking of active transports by session ID
Automatic cleanup of disconnected sessions
Connection status tracking

Additional Resources

License

This project is licensed under the MIT License - see the LICENSE file for details.

This server cannot be installed

security - not tested

license - permissive license

quality - not tested

hybrid server

The server is able to function both locally and remotely, depending on the configuration or use case.

A server that implements the Model Context Protocol, providing a standardized way to connect AI models to different data sources and tools.

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