Which integrations are available for this server?

Provides tools for managing local documents, including the ability to read, write, and list files within a specified directory.

How do I use MCP Azure Project?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@MCP Azure Project list all documents and read the content of sample.txt" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

MCP Azure Project

This project integrates Model Context Protocol (MCP) with Azure AI Foundry's Claude deployment.

Quick Start

1. Install Dependencies

# Create virtual environment
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

# Install packages
pip install -r requirements.txt

2. Configure Azure Credentials

Edit .env file with your Azure AI Foundry credentials:

AZURE_OPENAI_ENDPOINT=https://your-resource.openai.azure.com/
AZURE_OPENAI_API_KEY=your-api-key-here
AZURE_DEPLOYMENT_NAME=claude-35-sonnet
AZURE_API_VERSION=2024-10-01-preview

3. Test the MCP Server

# Start server with inspector
mcp dev server/document_server.py
# Opens browser at http://localhost:5173

4. Run the Client

python client/azure_client.py

Project Structure

.
├── .env                    # Azure credentials (don't commit!)
├── .gitignore
├── requirements.txt
├── server/
│   ├── __init__.py
│   └── document_server.py  # MCP server with tools
├── client/
│   ├── __init__.py
│   └── azure_client.py     # Azure-compatible client
└── test_documents/
    └── sample.txt          # Test files