🛡️ Nascoder Azure AI Foundry MCP Server v2.0

Professional Azure AI Integration - Thoroughly Tested & Production Ready

Developed by Freelancer Nasim with comprehensive testing and security best practices.

🎯 What This Package Delivers

A bulletproof Model Context Protocol (MCP) server that provides seamless integration with Azure AI services. Every tool is manually tested and production-ready.

✅ 9 Fully Tested Tools:

1. ask_azure_ai - Intelligent chat with auto-routing to best available model
2. get_model_info - Real-time model deployment information
3. health_check - Service health monitoring and diagnostics
4. list_capabilities - Available capabilities and features
5. analyze_image - Computer vision analysis (latest API v2024-02-01)
6. translate_text - Multi-language text translation
7. check_content_safety - Content moderation and safety analysis
8. analyze_language - Language detection and sentiment analysis
9. analyze_document - Document processing and text extraction

🚀 Quick Start

Installation

npm install -g nascoder-azure-ai-mcp-server

Prerequisites

You need your own Azure AI resources:

• Azure AI Project (AI Foundry)
• Azure Cognitive Services
• Valid API keys and endpoints

Environment Setup

export AZURE_AI_PROJECT_ENDPOINT="your-azure-ai-project-endpoint"
export AZURE_AI_INFERENCE_API_KEY="your-azure-ai-api-key"
export AZURE_AI_SERVICES_ENDPOINT="your-azure-services-endpoint"
export AZURE_REGION="your-azure-region"
export AZURE_RESOURCE_GROUP="your-resource-group"

Amazon Q CLI Integration

Add to ~/.aws/amazonq/mcp.json:

{
  "mcpServers": {
    "nascoder_azure_ai": {
      "command": "node",
      "args": [
        "/opt/homebrew/lib/node_modules/nascoder-azure-ai-mcp-server/dist/server.js"
      ],
      "env": {
        "AZURE_AI_PROJECT_ENDPOINT": "your-endpoint-here",
        "AZURE_AI_INFERENCE_API_KEY": "your-key-here",
        "AZURE_AI_SERVICES_ENDPOINT": "your-services-endpoint-here",
        "AZURE_REGION": "your-region-here",
        "AZURE_RESOURCE_GROUP": "your-resource-group-here"
      }
    }
  }
}

🔧 Azure Setup Guide

1. Create Azure AI Project

1. Go to Azure AI Foundry
2. Create a new AI Project
3. Note your project endpoint

2. Get API Keys

1. Navigate to your AI Project settings
2. Copy the API key and endpoint
3. Set up your environment variables

3. Deploy Models

Deploy these models in your Azure AI Project:

• GPT-4 or GPT-3.5-turbo for chat
• GPT-4-vision for image analysis
• Text translation service

🧪 Quality Assurance

API Version Updates (v2.0)

• ✅ Computer Vision: Updated to 2024-02-01 (latest stable)
• ✅ Document Intelligence: Updated to 2024-07-31-preview
• ✅ Content Safety: Updated to 2024-09-01
• ✅ Language Services: Updated to 2023-04-01
• ✅ Translator: Using stable v3.0

Security Features

• ✅ No hardcoded credentials
• ✅ Environment variable based configuration
• ✅ Input sanitization
• ✅ Error handling and graceful failures

📊 Tool Examples

Basic Chat

// Tool: ask_azure_ai
{
  "query": "What is machine learning?",
  "model": "gpt-4" // optional
}

Image Analysis

// Tool: analyze_image
{
  "imageUrl": "https://example.com/image.jpg"
}

Text Translation

// Tool: translate_text
{
  "text": "Hello world",
  "targetLanguage": "es",
  "sourceLanguage": "en" // optional
}

🛠️ Troubleshooting

Common Issues

Server won't start:

• Check your Azure credentials
• Verify your Azure AI Project is active
• Ensure models are deployed

API errors:

• Verify your API keys are valid
• Check your Azure subscription status
• Ensure proper permissions

📞 Support

• Issues: GitHub Issues
• Documentation: GitHub Wiki
• Email: [email protected]

📄 License

MIT License - See LICENSE file for details.

🛡️ Built with pride by Freelancer Nasim - Where quality meets reliability!

Bring your own Azure resources and enjoy professional AI integration!