openstack-kr/python-openstackmcp-server
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The OpenStack MCP (Model Context Protocol) server is a component designed to facilitate the deployment and management of OpenStack environments using model-driven architecture.
The OpenStack MCP server is a pivotal element in the orchestration and management of cloud infrastructure using OpenStack. It leverages model-driven architecture to streamline the deployment, scaling, and management of OpenStack services. By utilizing MCP, organizations can achieve a higher level of automation and efficiency in their cloud operations. The server acts as a central hub that integrates various OpenStack components, ensuring seamless communication and coordination among them. This approach not only simplifies the management of complex cloud environments but also enhances their reliability and performance. The OpenStack MCP server is particularly beneficial for large-scale deployments where manual management would be cumbersome and error-prone. It provides a robust framework for managing resources, monitoring system health, and automating routine tasks, thereby freeing up IT resources for more strategic initiatives.
Features
- Model-Driven Architecture: Facilitates the deployment and management of OpenStack services through a model-driven approach, enhancing automation and efficiency.
- Centralized Management: Acts as a central hub for integrating and coordinating various OpenStack components, ensuring seamless communication.
- Scalability: Supports large-scale deployments by automating routine tasks and managing resources efficiently.
- Enhanced Reliability: Improves the reliability and performance of cloud environments through streamlined management processes.
- Resource Monitoring: Provides tools for monitoring system health and managing resources effectively.
Usages
usage with local integration stdio
python mcp.run(transport='stdio') # Tools defined via @mcp.tool() decorator
usage with local integration ide plugin
{ "mcpServers": { "openstack": { "command": "python", "args": ["openstack.py"] } } }
usage with remote integration sse
python mcp.run(transport='sse', host="0.0.0.0", port=8000) # Specify SSE endpoint
usage with remote integration streamable http
yaml paths: /mcp: post: x-ms-agentic-protocol: mcp-streamable-1.0 # Copilot Studio integration
usage with platform integration github
{"command": "docker", "args": ["run", "-e", "GITHUB_PERSONAL_ACCESS_TOKEN", "ghcr.io/github/github-mcp-server"]}
usage with platform integration atlassian
{ "mcpServers": { "atlassian": { "command": "python", "args": ["atlassian.py"] } } }