Skip to main content

Azure MCP Agent for secure, compliant resource deployment

Project description

Azure SFI Agent - MCP Server

An intelligent Model Context Protocol (MCP) server for deploying Azure resources with automatic SFI compliance orchestration.

Features

  • 🚀 Interactive Deployment: Agent prompts for missing parameters
  • 🔒 Automatic NSP Attachment: Network Security Perimeter for storage, key vault, cosmos-db, sql-db
  • 📊 Automatic Log Analytics: Diagnostic settings for monitoring-enabled resources
  • SFI Compliance: Enforced security baselines and governance
  • 🎯 Zero Bypass: All deployments go through compliance orchestration

Installation

Via uvx (Recommended for GitHub Copilot)

uvx install azure-sfi-agent

Via pip

pip install azure-sfi-agent

Quick Start

1. Configure in GitHub Copilot (VS Code)

Add to your VS Code settings.json:

{
  "github.copilot.mcpServers": {
    "azure-sfi-agent": {
      "command": "uvx",
      "args": ["azure-sfi-agent"]
    }
  }
}

Or if installed via pip:

{
  "github.copilot.mcpServers": {
    "azure-sfi-agent": {
      "command": "python",
      "args": ["-m", "azure_sfi_agent.server"]
    }
  }
}

2. Login to Azure

az login

3. Use in Copilot Chat

User: "Create a storage account for ADLS"

Agent: 📋 Creating storage-account - Please provide:
       ✓ resource_group: (Azure resource group name)
       ✓ storageAccountName: (required)
       ✓ location: (required)
       ✓ accessTier: (required)

User: "RG: my-rg, name: datalake001, location: eastus, tier: Hot"

Agent: ✅ Deployment succeeded
       ✅ NSP attached: my-rg-nsp
       
       Endpoints:
       - DFS: https://datalake001.dfs.core.windows.net/

Supported Resources

Resource Type NSP Log Analytics
storage-account (ADLS)
key-vault
cosmos-db
sql-db
openai
ai-search
ai-foundry
log-analytics

Available Tools

  • create_azure_resource() - Interactive resource creation with compliance
  • list_permissions() - View active role assignments
  • list_resources() - View accessible Azure resources
  • create_resource_group() - Create resource group with tagging
  • get_bicep_requirements() - Check required parameters for a resource type

Requirements

  • Python 3.10+
  • Azure CLI installed and authenticated
  • PowerShell Core (pwsh) for script execution
  • Appropriate Azure RBAC permissions (Contributor role)

License

MIT

Support

For issues and questions, please visit the GitHub repository.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

azure_sfi_agent-1.0.25.tar.gz (23.4 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

azure_sfi_agent-1.0.25-py3-none-any.whl (29.4 kB view details)

Uploaded Python 3

File details

Details for the file azure_sfi_agent-1.0.25.tar.gz.

File metadata

  • Download URL: azure_sfi_agent-1.0.25.tar.gz
  • Upload date:
  • Size: 23.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.10.11

File hashes

Hashes for azure_sfi_agent-1.0.25.tar.gz
Algorithm Hash digest
SHA256 1548320674ce1ac082686f9369c0d8bfb59bac8d348d139cb98bddd9f72982ef
MD5 8823eaf8c772c5033d8bf86837c7fa99
BLAKE2b-256 f60df2ac1a44334a92a3a0360d8952c076f3a6f8fea68e4a1bbf29d012174e8c

See more details on using hashes here.

File details

Details for the file azure_sfi_agent-1.0.25-py3-none-any.whl.

File metadata

File hashes

Hashes for azure_sfi_agent-1.0.25-py3-none-any.whl
Algorithm Hash digest
SHA256 5a899d66f62575efdccf722ee5b6756510cff5fb25ef703ff3c9fa1c479f45c8
MD5 09cd217546a81053ee70623effcb4b23
BLAKE2b-256 58b7d606b9bf60775abb4547449aa35e51f47014bac46b4cafcf1dd892fd6869

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page