Identify and prioritize KVM host issues by combining status, update flags, and recent warning events. Get ranked findings with signal, cause, and action to guide remediation.
MIT
650,522 tools. Updated 2026-10-14 02:11
"LLVM" matching MCP tools:
- Identify engine-level problems by checking health, version, clock, backups, certificate expiry, and HA reservations, then rank correlated warning events worst-first for root-cause analysis.MIT
- Retrieve engine events filtered by severity and recency, with pagination and incremental fetch for new events.MIT
- Identifies and ranks storage-domain capacity problems worst first, flagging critical free-space shortfalls, low-space warnings, and inactive domains using engine thresholds and correlated events.MIT
- Apply a recorded undo by dispatching its inverse tool to reverse a previous action. Use dry_run=True to preview the inverse call without executing it.MIT
- List KVM hosts with status, SPM role, memory, and VM counts to quickly assess host inventory and identify underperforming or down hosts.MIT
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- List pending undo tokens with their IDs, associated tools, and verification status, so you can identify and apply the correct reversion for prior writes.MIT
- Diagnose VM health issues by ranking problems worst first and correlating recent warning events to identify root causes like storage errors, pauses, or availability risks.MIT
- Retrieve storage domains with status and capacity metrics (free, used, committed bytes and percentages) to identify health and space issues.MIT
- Retrieve details of a single virtual machine by its ID from an OLVM or oVirt 4.5 engine, enabling read-only inventory and diagnosis queries.MIT
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- Retrieve engine jobs (long-running operations) with status and duration, optionally filtering by status or limit, for monitoring and diagnosis.MIT
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- Retrieve current VM statistics including memory, CPU percentage, network, and disk usage with units. Specify VM ID to get real-time performance metrics.MIT
- Run private or large-output tasks on a local LLM by providing text, files, or command output, and receive sanitized placeholders or digested summaries so data stays on your network.MIT
- Run private or bulk text tasks on a local LLM, keeping data on your machine. Pass file paths for local processing; only the model's answer returns.MIT
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