MCP Azure Project
Provides tools for managing local documents, including the ability to read, write, and list files within a specified directory.
This server does not currently have a deployable release on Glama. Follow the repository's setup instructions to install and configure it for your MCP client, including any required credentials and local dependencies.
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
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
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This server cannot be deployed
Maintenance
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