MCP Server Development Guide

This protocol streamlines MCP server development with Bwat, enabling you to build powerful extensions that connect AI assistants to external systems and services.

🚀 Share your creations: Once developed, submit servers to the Bwat MCP Marketplace for community access.

Understanding MCP Servers

MCP servers empower AI assistants like Bwat to:

Integrate with external APIs and services
Access real-time data streams
Control applications and local systems
Perform actions beyond text-based interactions

These servers bridge the gap between AI capabilities and practical system integrations.

Development Protocol

The core development process uses a structured .bwatrules configuration file placed in your MCP working directory (/Users/your-name/Documents/Bwat/MCP).

The .bwatrules File

This configuration file:

Activates Bwat's specialized MCP development mode
Enforces development best practices
Guides through planning, implementation, and testing
Implements safety checks and validation

Complete protocol template:

# MCP Server Development Protocol  
 
⚠️ IMPORTANT: TEST ALL COMPONENTS BEFORE FINALIZING ⚠️  
 
## Phase 1: Planning  
 
- Define the problem being solved  
- Identify required APIs/services  
- Determine authentication needs:  
  □ API keys  
  □ OAuth flows  
  □ Other credentials  
 
## Phase 2: Implementation  
 
1. Project Setup  
 
   - JavaScript/Node.js environments:  
     ```bash  
     npx @modelcontextprotocol/create-server my-server  
     cd my-server  
     npm install

Python environments:

pip install mcp  
# Recommended alternative:  
uv add "mcp[cli]"

Core Development
- Implement using MCP SDK
- Add comprehensive logging:
  - TypeScript:
```
console.error("[Setup] Initializing server...")  
```
  - Python:
```
import logging  
logging.error('[API] Request to endpoint')  
```
- Include type definitions
- Implement error handling
- Add rate limiting if required

Configuration

Handle credential management

Update MCP settings:

TypeScript projects:

{  
  "mcpServers": {  
    "my-server": {  
      "command": "node",  
      "args": ["path/to/server.js"]  
    }  
  }  
}

Python projects:
```
mcp install server.py -v API_KEY=key  
```

Phase 3: Testing

REQUIRED BEFORE COMPLETION:
□ All tools tested with valid inputs
□ Output formats verified
□ User confirmation received

Completion Checklist

❗ Final verification:
□ Comprehensive testing completed
□ All outputs properly formatted
□ Documentation finalized


## Getting Started

### 1. Initialize Your Project
Create a `.bwatrules` file in your MCP directory using the protocol above. This configures Bwat's development behavior for your project.

### 2. Define Your Server
Begin with a clear description of your server's purpose:

```plaintext
Building an MCP server for WeatherAPI integration that provides:  
- Current weather conditions  
- Forecast data  
- Historical weather patterns  
- Severe weather alerts

3. Development Workflow

Bwat guides you through:

Planning Phase: Design architecture and API integration
Implementation Phase: Code development and configuration
Testing Phase: Rigorous validation of all components

4. Provide API Documentation

Share relevant API documentation early:

WeatherAPI documentation:  
[Paste API endpoints, authentication details, and response formats]

Development Modes

Planning Mode

Collaborative design phase covering:

Problem scope definition
API selection
Authentication strategy
Data flow design

Implementation Mode

Active development phase handling:

Project scaffolding
Core functionality implementation
Configuration management
Comprehensive testing

Implementation Best Practices

Robust Logging

Implement multi-level logging:

// Initialization logging  
console.error("[Init] Starting weather server...")  
 
// API interaction tracking  
console.error(`[WeatherAPI] Fetching data for ${location}`)  
 
// Error handling  
console.error("[Error] API request failed:", error.message)

Type Safety

Enforce strong typing:

interface WeatherData {
  location: string
  temperature: number
  conditions: string
  forecast: ForecastPeriod[]
}
 
function validateLocation(location: string) {
  if (!location.match(/^[A-Za-z\s,]+$/)) {
    throw new Error("Invalid location format")
  }
}

Performance Optimization

Implement intelligent caching:

const CACHE_TTL = {
  CURRENT_WEATHER: 60 * 15, // 15 minutes
  FORECAST: 60 * 60, // 1 hour
  HISTORICAL: 60 * 60 * 24 // 24 hours
}
 
function getCachedWeather(location: string) {
  const cacheKey = `weather-${location}`
  return cache.get(cacheKey) || fetchFreshData(location)
}

Error Handling

Graceful error recovery:

try {
  const data = await fetchWeather(location)
  return formatWeatherResponse(data)
} catch (error) {
  console.error("[WeatherError]", error)
  return {
    error: "Unable to retrieve weather data",
    details: error.message,
    retrySuggestion: true
  }
}

Testing Methodology

Unit Testing: Validate individual components
Integration Testing: Verify API interactions
End-to-End Testing: Test complete user flows

Example test cases:

// Test current weather retrieval
test("Returns valid weather data for known location", async () => {
  const response = await getWeather("New York")
  expect(response).toHaveProperty("temperature")
  expect(response).toHaveProperty("conditions")
})
 
// Test error handling
test("Handles invalid location errors", async () => {
  await expect(getWeather("Invalid$Location"))
    .rejects.toThrow("Invalid location format")
})

Deployment Process

Finalize all testing
Prepare documentation:
- Setup instructions
- Configuration requirements
- Usage examples
Submit to Bwat MCP Marketplace

Additional Resources

This guide provides the complete framework for developing robust MCP servers that extend Bwat's capabilities while maintaining security and reliability standards.

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