@aashari/boilerplate-mcp-server
Version:
TypeScript Model Context Protocol (MCP) server boilerplate providing IP lookup tools/resources. Includes CLI support and extensible structure for connecting AI systems (LLMs) to external data sources like ip-api.com. Ideal template for creating new MCP in
354 lines (261 loc) • 10.6 kB
Markdown
# Boilerplate MCP Server
A foundation for developing custom Model Context Protocol (MCP) servers in TypeScript. Provides a complete layered architecture pattern, working example tools, and developer infrastructure to connect AI assistants with external APIs and data sources.
[](https://www.npmjs.com/package/@aashari/boilerplate-mcp-server)
[](https://github.com/aashari/boilerplate-mcp-server/actions)
[](https://www.typescriptlang.org/)
[](https://opensource.org/licenses/ISC)
## Why Use This Boilerplate?
- **Production-Ready Architecture**: Follows the same pattern used in published MCP servers, with clean separation between CLI, tools, controllers, and services
- **Type Safety**: Built with TypeScript for improved developer experience, code quality, and maintainability
- **Working Example**: Includes fully implemented tools demonstrating the complete pattern from CLI to API integration
- **Testing Framework**: Ready-to-use testing infrastructure for unit and CLI integration tests, with coverage reporting
- **Complete Developer Tooling**: Pre-configured ESLint, Prettier, TypeScript, and CI/CD workflows
## What is MCP?
Model Context Protocol (MCP) is an open standard for securely connecting AI systems to external tools and data sources. This boilerplate implements the MCP specification with a clean, layered architecture that can be extended to build custom MCP servers for any API or data source.
## Prerequisites
- **Node.js** (>=18.x): [Download](https://nodejs.org/)
- **Git**: For version control
## Quick Start
```bash
# Clone the repository
git clone https://github.com/aashari/boilerplate-mcp-server.git
cd boilerplate-mcp-server
# Install dependencies
npm install
# Start development server
npm run dev:server
# Try the example tool
npm run dev:cli -- get-ip-details 8.8.8.8
```
## Architecture Overview
<details>
<summary><b>Project Structure (Click to expand)</b></summary>
```
src/
├── cli/ # Command-line interfaces
│ ├── index.ts # CLI entry point
│ └── *.cli.ts # Feature-specific CLI modules
├── controllers/ # Business logic
│ └── *.controller.ts # Feature controllers
├── services/ # External API interactions
│ └── *.service.ts # Service modules
├── tools/ # MCP tool definitions
│ ├── *.tool.ts # Tool implementations
│ └── *.types.ts # Tool argument schemas
├── types/ # Type definitions
│ └── common.types.ts # Shared type definitions
├── utils/ # Shared utilities
│ ├── logger.util.ts # Structured logging
│ ├── error.util.ts # Error handling
│ └── ... # Other utility modules
└── index.ts # Server entry point
```
</details>
## Layered Architecture
The boilerplate follows a clean, layered architecture that promotes maintainability and clear separation of concerns:
### 1. CLI Layer (`src/cli/*.cli.ts`)
- **Purpose**: Command-line interfaces that parse arguments and call controllers
- **Pattern**: Use `commander` for argument parsing, call controllers, handle errors with `handleCliError`
- **Naming**: `<feature>.cli.ts`
### 2. Tools Layer (`src/tools/*.tool.ts`)
- **Purpose**: MCP tool definitions exposed to AI assistants
- **Pattern**: Use `zod` for schema validation, call controllers, format responses for MCP
- **Naming**: `<feature>.tool.ts` with types in `<feature>.types.ts`
### 3. Controllers Layer (`src/controllers/*.controller.ts`)
- **Purpose**: Business logic orchestration, error handling, response formatting
- **Pattern**: Return standardized `ControllerResponse` objects, throw errors with context
- **Naming**: `<feature>.controller.ts` with optional `<feature>.formatter.ts`
### 4. Services Layer (`src/services/*.service.ts`)
- **Purpose**: External API interactions and data handling
- **Pattern**: Pure API calls with minimal logic, return raw data
- **Naming**: `<feature>.service.ts` or `vendor.<vendor>.<feature>.service.ts`
### 5. Utils Layer (`src/utils/*.util.ts`)
- **Purpose**: Shared functionality across the application
- **Key Utils**: Logging, error handling, formatting, configuration
## Developer Guide
### Development Scripts
```bash
# Start server in dev mode with hot-reload & inspector
npm run dev:server
# Run CLI commands in development
npm run dev:cli -- [command] [args]
# Build the project
npm run build
# Production server
npm start
npm run start:server
# Production CLI
npm run start:cli -- [command] [args]
# Testing
npm test # Run all tests
npm test -- src/path/to/test.ts # Run specific tests
npm run test:coverage # Generate coverage report
# Code Quality
npm run lint # Run ESLint
npm run format # Format with Prettier
npm run typecheck # Check TypeScript types
```
### Debugging Tools
- **MCP Inspector**: Visual tool for testing your MCP tools
- Run server with `npm run dev:server`
- Open http://localhost:5173 in your browser
- **Server Logs**: Enable with `DEBUG=true npm run dev:server` or in config
<details>
<summary><b>Configuration (Click to expand)</b></summary>
Create `~/.mcp/configs.json`:
```json
{
"boilerplate": {
"environments": {
"DEBUG": "true",
"ANY_OTHER_CONFIG": "value"
}
}
}
```
</details>
## Building Custom Tools
<details>
<summary><b>Step-by-Step Tool Implementation Guide (Click to expand)</b></summary>
### 1. Define Service Layer
Create a new service in `src/services/` to interact with your external API:
```typescript
// src/services/example.service.ts
import { Logger } from '../utils/logger.util.js';
const logger = Logger.forContext('services/example.service.ts');
export async function getData(param: string): Promise<any> {
logger.debug('Getting data', { param });
// API interaction code here
return { result: 'example data' };
}
```
### 2. Create Controller
Add a controller in `src/controllers/` to handle business logic:
```typescript
// src/controllers/example.controller.ts
import { Logger } from '../utils/logger.util.js';
import * as exampleService from '../services/example.service.js';
import { formatMarkdown } from '../utils/formatter.util.js';
import { handleControllerError } from '../utils/error-handler.util.js';
import { ControllerResponse } from '../types/common.types.js';
const logger = Logger.forContext('controllers/example.controller.ts');
export interface GetDataOptions {
param?: string;
}
export async function getData(
options: GetDataOptions = {},
): Promise<ControllerResponse> {
try {
logger.debug('Getting data with options', options);
const data = await exampleService.getData(options.param || 'default');
const content = formatMarkdown(data);
return { content };
} catch (error) {
throw handleControllerError(error, {
entityType: 'ExampleData',
operation: 'getData',
source: 'controllers/example.controller.ts',
});
}
}
```
### 3. Implement MCP Tool
Create a tool definition in `src/tools/`:
```typescript
// src/tools/example.tool.ts
import { McpServer } from '@modelcontextprotocol/sdk/server/mcp.js';
import { z } from 'zod';
import { Logger } from '../utils/logger.util.js';
import { formatErrorForMcpTool } from '../utils/error.util.js';
import * as exampleController from '../controllers/example.controller.js';
const logger = Logger.forContext('tools/example.tool.ts');
const GetDataArgs = z.object({
param: z.string().optional().describe('Optional parameter'),
});
type GetDataArgsType = z.infer<typeof GetDataArgs>;
async function handleGetData(args: GetDataArgsType) {
try {
logger.debug('Tool get_data called', args);
const result = await exampleController.getData({
param: args.param,
});
return {
content: [{ type: 'text' as const, text: result.content }],
};
} catch (error) {
logger.error('Tool get_data failed', error);
return formatErrorForMcpTool(error);
}
}
export function register(server: McpServer) {
server.tool(
'get_data',
`Gets data from the example API, optionally using \`param\`.
Use this to fetch example data. Returns formatted data as Markdown.`,
GetDataArgs.shape,
handleGetData,
);
}
```
### 4. Add CLI Support
Create a CLI command in `src/cli/`:
```typescript
// src/cli/example.cli.ts
import { program } from 'commander';
import { Logger } from '../utils/logger.util.js';
import * as exampleController from '../controllers/example.controller.js';
import { handleCliError } from '../utils/error-handler.util.js';
const logger = Logger.forContext('cli/example.cli.ts');
program
.command('get-data')
.description('Get example data')
.option('--param <value>', 'Optional parameter')
.action(async (options) => {
try {
logger.debug('CLI get-data called', options);
const result = await exampleController.getData({
param: options.param,
});
console.log(result.content);
} catch (error) {
handleCliError(error);
}
});
```
### 5. Register Components
Update the entry points to register your new components:
```typescript
// In src/cli/index.ts
import '../cli/example.cli.js';
// In src/index.ts (for the tool)
import exampleTool from './tools/example.tool.js';
// Then in registerTools function:
exampleTool.register(server);
```
</details>
## Publishing Your MCP Server
1. Update package.json with your details:
```json
{
"name": "your-mcp-server-name",
"version": "1.0.0",
"description": "Your custom MCP server",
"author": "Your Name",
// Other fields...
}
```
2. Update README.md with your tool documentation
3. Build: `npm run build`
4. Test: `npm run start:server`
5. Publish: `npm publish`
## Testing Best Practices
- **Unit Tests**: Test utils and pure functions in isolation
- **Controller Tests**: Test business logic with mocked service calls
- **Integration Tests**: Test CLI with real dependencies
- **Coverage Goal**: Aim for >80% test coverage
## License
[ISC License](https://opensource.org/licenses/ISC)
## Resources
- [MCP Specification](https://github.com/modelcontextprotocol/mcp-spec)
- [Official MCP Documentation](https://www.modelcontextprotocol.ai/)
- [TypeScript Documentation](https://www.typescriptlang.org/docs/)