MCP Azure Project
Provides tools for managing local documents, including the ability to read, write, and list files within a specified directory.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@MCP Azure Projectlist 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.txt2. 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-preview3. Test the MCP Server
# Start server with inspector
mcp dev server/document_server.py
# Opens browser at http://localhost:51734. Run the Client
python client/azure_client.pyRelated MCP server: Universal MCP Server
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 filesAvailable Tools
read_document: Read file contents
write_document: Create/update files
list_documents: List all documents
Resources
This server cannot be deployed
Maintenance
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