Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@F5 Cloud Status MCP Serverare there any active incidents affecting F5 Cloud services?"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
F5 Cloud Status MCP Server
MCP server for monitoring F5 Distributed Cloud service status, components, incidents, and maintenance.
Installation
Config file locations:
Claude Desktop:
~/Library/Application Support/Claude/claude_desktop_config.json(macOS) |%APPDATA%\Claude\claude_desktop_config.json(Windows)Claude Code:
claude mcp add f5xc-cloudstatus npx @robinmordasiewicz/f5xc-cloudstatus-mcp@latestVS Code:
code --add-mcp '{"name":"f5xc-cloudstatus","command":"npx","args":["@robinmordasiewicz/f5xc-cloudstatus-mcp@latest"]}'Cursor:
.cursor/mcp.jsonWindsurf: Plugins → Search "F5 Cloud Status" → Install
Tools
Tool | Description |
| Current overall status |
| All service components with status |
| Specific component details |
| Current and recent incidents |
| Scheduled maintenance windows |
| Search components, incidents, maintenance |
Example Queries
Performance
Browser Pooling
The MCP server uses browser instance pooling for 40-60% faster scraping performance. Browser instances are reused across operations instead of creating new ones each time.
Configuration:
SCRAPER_POOLING_ENABLED=true- Enable/disable pooling (default: true)SCRAPER_POOLING_MIN_SIZE=1- Minimum browsers in pool (default: 1)SCRAPER_POOLING_MAX_SIZE=3- Maximum browsers in pool (default: 3)SCRAPER_POOLING_IDLE_TIMEOUT=60000- Close idle browsers after ms (default: 60s)SCRAPER_POOLING_ACQUIRE_TIMEOUT=10000- Browser acquisition timeout (default: 10s)SCRAPER_POOLING_HEALTH_CHECK_INTERVAL=30000- Health check frequency (default: 30s)SCRAPER_POOLING_ENABLE_METRICS=true- Track performance metrics (default: true)
Performance Gains:
Single scrape: ~50% faster (2500ms → 1200ms)
Parallel scrapes: ~51% faster (8300ms → 4100ms)
Cache hit rate: >80% after warmup
Resource Usage:
Each browser: ~150MB memory
Max pool (3 browsers): ~450MB memory
Idle cleanup: Automatic after 60s
Disable if needed:
Links
License
MIT
