Skillget

python-openstackmcp-server

mcp
Guvenlik Denetimi
Gecti
Health Gecti
  • License — License: Apache-2.0
  • Description — Repository has a description
  • Active repo — Last push 0 days ago
  • Community trust — 18 GitHub stars
Code Gecti
  • Code scan — Scanned 12 files during light audit, no dangerous patterns found
Permissions Gecti
  • Permissions — No dangerous permissions requested
Purpose
This server acts as a bridge between AI assistants and OpenStack cloud infrastructure, allowing AI models to manage compute, storage, network, and identity resources via the Model Context Protocol (MCP).

Security Assessment
Overall Risk: Medium. The tool makes external network requests by design to communicate with your OpenStack cloud via its REST SDK. It does not request dangerous local permissions, execute arbitrary shell commands, or contain hardcoded secrets. However, it inherently accesses highly sensitive infrastructure data. To function, it must be explicitly passed a `clouds.yaml` file containing your OpenStack authentication credentials. You must trust the AI assistant interacting with this server, as it gains the ability to read and modify your cloud infrastructure based on the privileges assigned to those credentials.

Quality Assessment
The project appears well-maintained and exhibits solid fundamentals. It has a clear, descriptive README with easy setup instructions for popular platforms. The light code audit found no dangerous patterns across 12 files, and it is distributed under the permissive Apache-2.0 license. While community trust is still in its early stages with 18 GitHub stars, the repository is highly active, with the most recent push occurring just today.

Verdict
Use with caution — the code itself is safe and clean, but you must strictly guard the OpenStack credentials you provide to it and limit the AI's permissions to prevent unintended infrastructure changes.
SUMMARY

openstack mcp server

README.md

python-openstackmcp-server

Openstack mcp server is a Model Context Protocol (MCP) server that provides an interface for AI assistants to interact with OpenStack services.

flowchart LR
    AI[AI Assistant] <-->|MCP Protocol| Server[OpenStack MCP Server]
    Server <-->|OpenStack SDK| SDK[OpenStack SDK]
    SDK <-->|REST API| Cloud[OpenStack Cloud]

Table of Contents

Features

  • MCP Protocol Support: Implements the Model Context Protocol for AI assistants.
  • Compute Tools: Manage OpenStack compute resources (servers, flavors).
  • Image Tools: Manage OpenStack images.
  • Identity Tools: Handle OpenStack identity and authentication.
  • Network Tools: Manage OpenStack networking resources.
  • Block Storage Tools: Manage OpenStack block storage resources.

Quick Start with Claude Desktop

Get started quickly with the OpenStack MCP server using Claude Desktop

Requirements

  • Python 3.10 or higher
  • OpenStack credentials configured in clouds.yaml file
  • Claude Desktop installed

  1. Create or update your clouds.yaml file with your OpenStack credentials.

    Example clouds.yaml:

    clouds:
  openstack:
    auth:
      auth_url: https://your-openstack-auth-url.com
      username: your-username
      password: your-password
      project_name: your-project-name
      user_domain_name: Default
      project_domain_name: Default
    region_name: your-region
    interface: public
    identity_api_version: 3

  2. Create or update your Claude Desktop configuration file:

    • macOS: Edit $HOME/Library/Application Support/Claude/claude_desktop_config.json
    • Windows: Edit %APPDATA%\Claude\claude_desktop_config.json
    • Linux: Edit $HOME/.config/Claude/claude_desktop_config.json

Using python

{
  "mcpServers": {
    "openstack-mcp-server": {
      "command": "/path/to/your/python",
      "args": [
        "python-openstackmcp-server"
      ],
      "env" : {
        "OS_CLIENT_CONFIG_FILE": "/path/to/your/clouds.yaml"
      }
    }
  }
}

Using uvx

{
  "mcpServers": {
    "openstack-mcp-server": {
      "command": "uvx",
      "args": [
        "python-openstackmcp-server"
      ],
      "env" : {
        "OS_CLIENT_CONFIG_FILE": "/path/to/your/clouds.yaml"
      }
    }
  }
}

Development

Setup

This project supports both uv and tox for development and testing.

Using uv (Fast Local Development)

# Install dependencies (including dev and test groups)
uv sync

# Run tests
uv run --group test pytest

# Run linting
uv run ruff check src tests

# Format code
uv run ruff format src tests

Using tox (OpenStack Standard)

# Install tox
pip install tox
# or
uv tool install tox

# Run tests
tox -e py3

# Run linting
tox -e pep8

# Auto-format code
tox -e format

# Generate coverage report
tox -e cover

# Run arbitrary commands in virtualenv
tox -e venv -- <command>

# Test on specific Python version
tox -e py310  # or py311, py312, py313

# List all available environments
tox list

Testing

The project includes comprehensive test coverage (85%+). Tests are located in the tests/ directory.

# Run all tests
tox -e py3

# Run with coverage
tox -e cover

# Run with debugger
tox -e debug

# Run specific test file
tox -e py3 -- tests/tools/test_compute_tools.py

Contributing

Contributions are welcome! Please see the CONTRIBUTING file for details on how to contribute to this project.

License

This project is licensed under the Apache License 2.0. See the LICENSE file for details.

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