https://github.com/chand45/mcp-server-azure-impact-reporting
https://github.com/chand45/mcp-server-azure-impact-reporting
Last synced: 3 months ago
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- Host: GitHub
- URL: https://github.com/chand45/mcp-server-azure-impact-reporting
- Owner: chand45
- Created: 2025-04-11T13:14:34.000Z (6 months ago)
- Default Branch: main
- Last Pushed: 2025-06-16T15:39:19.000Z (4 months ago)
- Last Synced: 2025-06-16T16:41:40.479Z (4 months ago)
- Language: Python
- Size: 273 KB
- Stars: 2
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# MCP-Server-Azure-Impact-Reporting
## Overview
The Azure Impact Reporting MCP (Model Context Protocol) server enables large language models (LLMs) to report impacts to Azure resources. This tool allows LLMs to automatically parse user requests, understand the required parameters, and submit reports to Azure when customers are facing issues with Azure infrastructure.
## Functionality
The `impact-reporter.py` script provides a Model Context Protocol server that:
1. Exposes a tool to report resource impacts to Azure
2. Automatically authenticates with Azure using DefaultAzureCredential
3. Creates workload impact reports via the Azure Management API
4. Handles parameter extraction from natural language requests
5. Can ask for additional details if the request is missing required information
### Impact Categories
The tool supports the following impact categories:
- `Resource.Connectivity` - For connectivity issues with Azure resources
- `Resource.Performance` - For performance degradation issues
- `Resource.Availability` - For availability or downtime issues
- `Resource.Unknown` - When the specific issue type is not known
## Requirements
- Python 3.8+
- `mcp[cli]` - Model Context Protocol package with CLI support
- `azure-identity` - For Azure authentication
- `httpx` - For making HTTP requests to Azure API
## Setup Instructions
### 1. Clone the repository
```bash
git clone https://github.com/yourusername/MCP-Server-Azure-Impact-Reporting.git
cd MCP-Server-Azure-Impact-Reporting
```
### 2. Install dependencies
```bash
pip install -r requirements.txt
```
Or install them manually:
```bash
pip install mcp[cli] azure-identity httpx
```
### 3. Azure Authentication Setup
The tool uses `DefaultAzureCredential` for authentication. Ensure you're logged in to Azure with one of the following methods:
- Azure CLI (`az login`)
- Visual Studio Code Azure Account extension
- Azure PowerShell (`Connect-AzAccount`)
- Environment variables for service principal authentication
### 4. Configure your MCP client
Add the following configuration to your MCP client configuration file (e.g., `claude_desktop_config.json`):
```json
"impactreporter": {
"command": "uv",
"args": [
"--directory",
"ABSOLUTE_PATH_TO_ROOT_FOLDER",
"run",
"impact-reporter.py"
]
}
```
Replace `ABSOLUTE_PATH_TO_ROOT_FOLDER` with the absolute path to where you cloned this repository.
For example:
```json
"impactreporter": {
"command": "uv",
"args": [
"--directory",
"C:\\Users\\username\\source\\repos\\MCP-Server-Azure-Impact-Reporting",
"run",
"impact-reporter.py"
]
}
```
### Understanding the `uv` Command
The `uv` command in the configuration uses `pyproject.toml` to manage dependencies:
- **Virtual Environment**: `uv` creates and manages its own internal virtual environment separate from any `.venv` you may have created
- **Dependency Management**: Dependencies are automatically installed based on `pyproject.toml` specifications
- **Isolation**: The `uv` cache system ensures no interference with your local Python environment
### Alternative: Direct Python Execution
If you prefer not to use `uv`, you can run the MCP server directly:
1. Create and activate a virtual environment:
```bash
python -m venv .venv
# On Windows
.venv\Scripts\activate
# On macOS/Linux
source .venv/bin/activate
```
2. Install dependencies:
```bash
pip install -r requirements.txt
```
3. Run the server directly:
```bash
python impact-reporter.py
```
### 5. Running the MCP Server
If you're using Claude with Desktop or another MCP-enabled client, the server will start automatically when needed.
## Usage Examples
Once configured, your LLM can report impacts with natural language requests like:
1. "Report connectivity issues with my VM named 'web-server' in resource group 'production-rg'"
2. "Let Azure know my SQL database 'customer-db' in 'data-rg' is experiencing performance issues"
3. "Report that my App Service 'api-service' is down"
The MCP server will automatically parse these requests and ask for any missing parameters before submitting the report to Azure.
Example Converstations:
![alt text]()
When additional information is required
1. Request for additional details
![alt text]()
2. Infer the details and report impact
![alt text]()
## API Details
The impact reporting tool uses the Azure Management API (2023-12-01-preview) to create workload impact reports.
## Troubleshooting
- **Authentication issues**: Ensure you're logged into Azure and have proper permissions
- **Missing parameters**: The tool will ask for additional details if needed
- **API errors**: Check Azure portal to ensure your subscription and resources exist
## License
[MIT License](LICENSE)