An OpenStack resource query service based on MCP (Model Context Protocol), providing API interfaces to query compute, storage, network, image, and other resources from the OpenStack cloud platform.

• Real-time Resource Queries: Get the latest resource status of OpenStack clusters via API
• Multi-dimensional Information: Support querying various resources including compute, storage, network, and images
• Flexible Filtering: Filter resources by name, ID, and other conditions
• Detail Level Control: Support basic, detailed, and full information display levels
• Standard MCP Interface: Fully compatible with MCP protocol, seamlessly integrating with large language models

• High-performance asynchronous HTTP service based on Starlette and Uvicorn
• Interact with OpenStack API using OpenStack SDK
• Provide structured OpenStack resource information to large language models through MCP protocol
• Support SSE streaming output for real-time feedback

┌─────────────┐    ┌─────────────┐    ┌─────────────┐
│             │    │             │    │             │
│  AI Client  │───▶│  MCP Server │───▶│  OpenStack  │
│  (LLM)      │◀───│  (Server)   │◀───│  API        │
│             │    │             │    │             │
└─────────────┘    └─────────────┘    └─────────────┘

• Python 3.10+
• OpenStack environment

pip install openstack-mcp-server

openstack-mcp-server --port 8000 --log-level INFO --auth-url 'https://<OpenStack-API-Endpoint>:5000/v3' --username '<OpenStack-Admin-User>' --password '<OpenStack-Admin-Password>'

After starting, the MCP interface will be available at https://localhost:8000/openstack.

• --port: Service listening port, default is 8000
• --log-level: Log level, options are DEBUG, INFO, WARNING, ERROR, CRITICAL, default is INFO
• --json-response: Use JSON response instead of SSE stream, default is False

Through the MCP protocol, you can use the following tools to query OpenStack resources:

{
  "name": "get_instances",
  "arguments": {
    "filter": "web-server",
    "limit": 10,
    "detail_level": "detailed"
  }
}

Parameter description:

• filter: Filter condition, such as instance name or ID (optional)
• limit: Maximum number of results to return (optional, default 100)
• detail_level: Level of detail in the returned information, options are basic, detailed, full (optional, default detailed)

# Clone repository
git clone https://github.com/wangshqly0407/openstack-mcp-server.git
cd openstack-mcp-server
# Create virtual environment
uv venv
# Activate virtual environment
source .venv/bin/activate
# Initialize runtime environment
uv sync
# Start streaming HTTP MCP server
uv run ./src/mcp_openstack_http/server.py --port 8000 --log-level INFO --auth-url 'https://<OpenStack-API-Endpoint>:5000/v3' --username '<OpenStack-Admin-User>' --password '<OpenStack-Admin-Password>'

# Method 1: Test using npx
npx -y @modelcontextprotocol/inspector uv run ./src/mcp_openstack_http/server.py --port 8000 --log-level INFO --auth-url 'https://<OpenStack-API-Endpoint>:5000/v3' --username '<OpenStack-Admin-User>' --password '<OpenStack-Admin-Password>'
# Method 2: Test using docker
docker run -it --rm -p 6274:6274 -p 6277:6277 -v $(pwd):/app -w /app node:18 npx -y @modelcontextprotocol/inspector uv run ./src/mcp_openstack_http/server.py --port 8000 --log-level INFO --auth-url 'https://<OpenStack-API-Endpoint>:5000/v3' --username '<OpenStack-Admin-User>' --password '<OpenStack-Admin-Password>'

Access: https://localhost:6274/

1. Add corresponding resource acquisition functions in src/mcp_openstack_http/server.py
2. Register the new tool in the list_tools method
3. Implement the tool's processing logic in the call_tool method

Apache 2.0