MCP-Server-Starter

by TheSethRose

A Model Context Protocol server starter template

#server #template #mod #typescript #mcp-server #starter #cursor #claude #mcp

About

What is MCP?

The Model Context Protocol (MCP) is a specialized framework designed to streamline the process of enabling AI agents to interact with a wide array of tools. This starter template helps you quickly build a Model Context Protocol (MCP) server using TypeScript. It provides a robust foundation that you can easily extend to create advanced MCP tools and seamlessly integrate them with various AI platforms.

Core Components

MCP Servers: These servers act as bridges, exposing APIs, databases, and code libraries to external AI hosts. By implementing an MCP server in TypeScript, developers can share data sources or computational logic in a standardized way using JSON-RPC 2.0.
MCP Clients: These are the consumer-facing side of MCP, communicating with servers to query data or perform actions. MCP clients use TypeScript SDKs, ensuring type-safe interactions and uniform approach to tool usage.
MCP Hosts: Systems such as Claude, Cursor, Windsurf, Cline, and other TypeScript-based platforms coordinate requests between servers and clients, ensuring seamless data flow. A single MCP server can thus be accessed by multiple AI hosts without custom integrations.

TypeScript Implementation

The MCP TypeScript SDK provides core classes for building servers:

```typescript import { Server } from "@modelcontextprotocol/sdk/server/index.js"; import { StdioServerTransport } from "@modelcontextprotocol/sdk/server/stdio.js";

const server = new Server({ name: "mcp-server-starter", version: "1.0.0", capabilities: { tools: {}, // Enable tools capability resources: {}, // Enable resource access prompts: {}, // Enable prompt handling streaming: true // Enable streaming responses } });

// Connect transport const transport = new StdioServerTransport(); await server.connect(transport); ```

By using MCP, developers no longer need complex custom code to integrate new tools or services. Instead, they build an MCP server and make it available to supported hosts.

Prerequisites

Node.js (v18 or later): A modern version of Node.js that takes advantage of the latest JavaScript features and performance improvements.
npm (v7 or later): Ensures compatibility for installing and managing packages.
VS Code with Dev Containers extension: Allows you to quickly spin up a reproducible development environment, making collaboration easier and more efficient.

Project Structure

A typical file layout for the MCP server template may look like this:

mcp-server/ ├── .devcontainer/ # Dev container configuration │ └── devcontainer.json ├── src/ │ ├── index.ts # MCP Server main entry point │ └── examples/ # Example tool implementations │ ├── calculator.ts # Calculator tool example │ └── rest-api.ts # REST API tool example ├── package.json # Project configuration └── tsconfig.json # TypeScript configuration

The .devcontainer directory streamlines container-based development, while the src/ folder houses the main server logic and examples of custom tools. This structure keeps your project organized and easy to navigate.

Quick Start

Installing via Smithery

To install MCP Server Starter for any supported client:

```bash

npx -y @smithery/cli install @TheSethRose/mcp-server-starter --client claude

For Cursor

npx -y @smithery/cli install @TheSethRose/mcp-server-starter --client cursor

For Windsurf

npx -y @smithery/cli install @TheSethRose/mcp-server-starter --client windsurf

For Cline

npx -y @smithery/cli install @TheSethRose/mcp-server-starter --client cline

For TypeScript

npx -y @smithery/cli install @TheSethRose/mcp-server-starter --client typescript ```

Clone this template: Retrieve the repository files from your preferred source.
Open in VS Code with Dev Containers: If you have the Dev Containers extension installed, you will be prompted to open this project inside a container.
Install dependencies: bash npm install This command fetches and installs all required packages for the MCP server.
Build the project: bash npm run build This compiles your TypeScript code into JavaScript, preparing it for runtime.

Development Scripts

Build the project: bash npm run build Compiles your TypeScript source and sets file permissions for the main entry point.
Watch mode: bash npm run watch Automatically recompiles TypeScript files whenever changes are made, ideal for active development.
Run with inspector: bash npm run inspector Launches the server alongside a debugging tool, enabling you to trace issues, set breakpoints, and inspect variables in real time.

Tool Response Format

MCP tools must return responses in a specific format to ensure proper communication with AI hosts. Here's the structure:

```typescript interface ToolResponse { content: ContentItem[]; isError?: boolean; metadata?: Record; }

interface ContentItem { type: string; text?: string; mimeType?: string; data?: unknown; } ```

Supported content types include: - text: Plain text content - code: Code snippets with optional language specification - image: Base64-encoded images with MIME type - file: File content with MIME type - error: Error messages (when isError is true)

Example response: typescript return { content: [ { type: "text", text: "Operation completed successfully" }, { type: "code", text: "console.log('Hello, World!')", mimeType: "application/javascript" } ] };

Security Best Practices

When developing MCP tools, follow these security guidelines:

Input Validation:
Always validate input parameters using Zod schemas
Implement strict type checking
Sanitize user inputs before processing
Use the strict() option in schemas to prevent extra properties
Error Handling:
Never expose internal error details to clients
Implement proper error boundaries
Log errors securely
Return user-friendly error messages
Resource Management:
Implement proper cleanup procedures
Handle process termination signals
Close connections and free resources
Implement timeouts for long-running operations
API Security:
Use secure transport protocols
Implement rate limiting
Store sensitive data securely
Use environment variables for configuration

Example secure tool implementation: ```typescript const SecureSchema = z.object({ input: z.string() .min(1) .max(1000) .transform(str => str.trim()) .pipe(z.string().regex(/^[a-zA-Z0-9\s]+$/)) });

server.tool( "secure_tool", SecureSchema.shape, async (params) => { try { // Implement rate limiting await rateLimiter.checkLimit();

  // Process validated input
  const result = await processSecurely(params.input);

  return {
    content: [{
      type: "text",
      text: result
    }]
  };
} catch (error) {
  // Log error internally
  logger.error(error);

  // Return safe error message
  return {
    content: [{
      type: "text",
      text: "An error occurred processing your request"
    }],
    isError: true
  };
}

} ); ```

Advanced Features

Streaming Responses

MCP supports streaming responses for long-running operations:

typescript server.tool( "stream_data", StreamSchema.shape, async function* (params) { for (const chunk of dataStream) { yield { content: [{ type: "text", text: chunk }] }; } } );

Custom Content Types

You can define custom content types for specialized data:

typescript interface CustomContent extends ContentItem { type: "custom"; data: { format: string; value: unknown; }; }

Async Tool Execution

Implement proper async handling:

```typescript server.tool( "async_operation", AsyncSchema.shape, async (params) => { const operation = await startAsyncOperation();

while (!operation.isComplete()) {
  await operation.wait();
}

return {
  content: [{
    type: "text",
    text: await operation.getResult()
  }]
};

} ); ```

Testing & Debugging

Unit Testing

Use Jest for testing your tools:

```typescript describe('Calculator Tool', () => { let server: McpServer;

beforeEach(() => { server = new McpServer({ name: "test-server", version: "1.0.0" }); registerCalculatorTool(server); });

test('adds numbers correctly', async () => { const result = await server.executeTool('calculate', { a: 5, b: 3, operation: 'add' });

expect(result.content[0].text).toBe('8');

}); }); ```

Debugging Tools

MCP Inspector: bash npm run inspector Provides real-time inspection of:
Tool registration
Request/response flow
Error handling
Performance metrics
Logging: typescript function logMessage(level: 'info' | 'warn' | 'error', message: string) { console.error(`[${level.toUpperCase()}] ${message}`); }
Error Tracking: typescript process.on('uncaughtException', (error: Error) => { logMessage('error', `Uncaught error: ${error.message}`); // Implement error reporting });

Transport Configuration

MCP supports multiple transport protocols:

stdio Transport

```typescript import { StdioServerTransport } from "@modelcontextprotocol/sdk/server/stdio.js";

const transport = new StdioServerTransport(); await server.connect(transport); ```

WebSocket Transport

```typescript import { WebSocketServerTransport } from "@modelcontextprotocol/sdk/server/websocket.js";

const transport = new WebSocketServerTransport({ port: 3000 }); await server.connect(transport); ```

Custom Transport

```typescript import { Transport } from "@modelcontextprotocol/sdk/server/transport.js";

class CustomTransport implements Transport { // Implement transport methods } ```

Server Capabilities

Configure server capabilities:

typescript const server = new McpServer({ name: "mcp-server", version: "1.0.0", capabilities: { tools: {}, // Enable tools capability streaming: true, // Enable streaming support customContent: ["myFormat"], // Define custom content types metadata: true // Enable metadata support } });

Integration with MCP Hosts

Multi-Client Support

This MCP server template supports multiple AI platforms out of the box:

Claude Desktop:
Provides a chat-based environment
Supports all MCP capabilities
Ideal for conversational AI interactions
Cursor:
AI-powered development environment
Full tool integration support
Perfect for coding assistance
Windsurf:
Modern AI development platform
Complete MCP protocol support
Streamlined workflow integration
Cline:
Command-line AI interface
Tool-focused interactions
Efficient terminal-based usage
TypeScript:
Native TypeScript support
Type-safe tool development
Seamless SDK integration

Each client can be configured using the appropriate Smithery CLI command:

bash npx -y @smithery/cli run @TheSethRose/mcp-server-starter --client [client-name]

Replace [client-name] with one of: claude, cursor, windsurf, cline, or typescript.

Smithery Integration

A convenient way to run this MCP server is through Smithery, a centralized platform for discovering and publishing MCP servers. Smithery simplifies deployment and ensures your server can be integrated into various AI workflows.

Quick Run

You can immediately execute this server via the Smithery CLI:

bash npx -y @smithery/cli@latest run mcp-server-template --config "{}"

Smithery automatically fetches, installs, and runs the server from its latest release, requiring minimal setup from you.

Publishing Your Own Version

If you have developed new tools or made local modifications and wish to share them, consider publishing your customized server:

Create an account on Smithery.
Follow their deployment instructions to bundle and publish your MCP server.
Other users can then run your server through Smithery by referencing your unique package name.

Smithery offers: - A centralized registry to discover and share MCP servers. - Simplified deployment, removing repetitive setup. - A community-driven approach where developers contribute diverse tools. - Easy integration with popular AI hosts.

For additional guidance: - Smithery Documentation - Smithery GitHub

Cursor Integration

Cursor is another AI development environment that supports MCP. To incorporate your server into Cursor:

Build your server: bash npm run build Ensure an executable index.js is generated in the build directory.
In Cursor, go to Settings > Features > MCP: Add a new MCP server.
Register your server:
Select stdio as the transport type.
Provide a descriptive Name.
Set the command, for example: node /path/to/your/mcp-server/build/index.js.
Save your configuration.

Cursor then detects and lists your tools. During AI-assisted coding sessions or prompt-based interactions, it will call your MCP tools whenever relevant. You can also instruct the AI to use a specific tool by name.

Claude Desktop Integration

Claude Desktop provides a chat-based environment where you can leverage MCP tools. To include your server:

Build your server: bash npm run build Confirm that no errors occur and that the main script is generated in build.
Modify claude_desktop_config.json: json { "mcpServers": { "mcp-server": { "command": "node", "args": [ "/path/to/your/mcp-server/build/index.js" ] } } } Provide the path to your compiled main file along with any additional arguments.
Restart Claude Desktop to load the new configuration.

When you interact with Claude Desktop, it can now invoke the MCP tools you have registered. If a user's request aligns with any of your tool's functionality, Claude will prompt to use that tool.

Development Best Practices

Use TypeScript for better type checking, clearer code organization, and easier maintenance over time.
Adopt consistent patterns for implementing tools:
Keep each tool in its own file
Use descriptive schemas with proper documentation
Implement comprehensive error handling
Return properly formatted content
Include thorough documentation:
Add JSDoc comments to explain functionality
Document parameters and return types
Include examples where helpful
Leverage the inspector for debugging: bash npm run inspector This helps you:
Test tool functionality
Debug request/response flow
Verify schema validation
Check error handling
Test comprehensively before deployment:
Verify input validation
Test error scenarios
Check response formatting
Ensure proper integration with hosts
Follow MCP best practices:
Use proper content types
Implement proper error handling
Validate all inputs and outputs
Handle network requests safely
Format responses consistently

Learn More

For further information on the MCP ecosystem, refer to:

Model Context Protocol Documentation: Detailed coverage of MCP architecture, design principles, and more advanced usage examples.
Smithery - MCP Server Registry: Guidelines for publishing your tools to Smithery and best practices for their registry.
MCP TypeScript SDK Documentation: Comprehensive documentation of the TypeScript SDK.
MCP Security Guidelines: Detailed security best practices and recommendations.

Conclusion

By following this template and best practices, you can quickly build a robust MCP server that opens your tools to a broad range of AI hosts. This expanded approach ensures easier maintenance, better type safety, and a smooth user experience when harnessing the capabilities of modern AI systems.