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MCP server · Cloud

Vibops MCP

The AI Infrastructure Operating System for enterprise and Cloud Service Provider GPU environments

Unclaimed cloud
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Scored 5 months ago · breakdown

About Vibops MCP

Vibops MCP is an MCP server in the Cloud category: the AI Infrastructure Operating System for enterprise and Cloud Service Provider GPU environments.

Install

From source
git clone https://github.com/VibOpsai/vibops-mcp

This server has no ConduID identity, so agent calls to it are not receipted. Pin the version you install and review the source before granting it credentials.

Tools (16)

get_cluster_deploymentsLive K8s deployment status for a cluster

Parameters not published.

get_cluster_rateGet configured GPU cost rate for a cluster

Parameters not published.

get_cost_estimateEstimated GPU spend

Parameters not published.

get_gpu_metricsHourly GPU utilisation time-series

Parameters not published.

get_jobGet job details and result

Parameters not published.

get_job_metricsJob success rate, latency P50/P95/P99, error breakdown

Parameters not published.

get_mttrMean Time To Resolve GPU alerts

Parameters not published.

get_workload_breakdownJob count by workload type

Parameters not published.

list_alertsList GPU alerts (open or resolved)

Parameters not published.

list_clustersList clusters and GPU utilisation

Parameters not published.

Show all 16 tools
list_gatewaysList registered gateways and status

Parameters not published.

list_jobsList recent jobs with optional filters

Parameters not published.

list_kubectl_contextsList available kubectl contexts

Parameters not published.

list_pipelinesList automation pipelines

Parameters not published.

list_providersList configured AI/GPU cloud providers

Parameters not published.

list_secretsList secrets (names only, never values)

Parameters not published.

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README

vibops-mcp

The provider-agnostic MCP server for GPU infrastructure — one interface for any cloud, any cluster, any provider.

The problem

Large enterprises and CSPs managing GPU infrastructure deal with fragmentation — AWS, GCP, Azure, on-prem, neoclouds, each with their own API, dashboard, and cost model. Correlating utilisation, cost, and workload type across providers requires jumping between 5 tools.

The solution

vibops-mcp is a single MCP server that abstracts this complexity. One pip install, 26 tools, and your AI assistant can observe, operate, and optimize your entire GPU fleet — regardless of where it runs.

  • Observe — GPU utilisation, workload breakdown, MTTR, cost estimates, live K8s deployments
  • Act — deploy models, scale clusters, run Helm/kubectl, trigger pipelines
  • Configure — set cost rates, manage gateways, store secrets

All operations go through your VibOps instance and are recorded in the audit log.

Installation

pip install git+https://github.com/VibOpsai/vibops-mcp.git

Configuration

You need two environment variables:

Variable Description
VIBOPS_URL Base URL of your VibOps instance, e.g. https://vibops.example.com
VIBOPS_TOKEN API token — create one in VibOps → Settings → API Tokens

Claude Desktop

Add to ~/.config/claude/claude_desktop_config.json (macOS: ~/Library/Application Support/Claude/claude_desktop_config.json):

{
  "mcpServers": {
    "vibops": {
      "command": "vibops-mcp",
      "env": {
        "VIBOPS_URL": "https://vibops.example.com",
        "VIBOPS_TOKEN": "your-token-here"
      }
    }
  }
}

Cursor

Add to .cursor/mcp.json in your project root, or to the global config:

{
  "mcpServers": {
    "vibops": {
      "command": "vibops-mcp",
      "env": {
        "VIBOPS_URL": "https://vibops.example.com",
        "VIBOPS_TOKEN": "your-token-here"
      }
    }
  }
}

Claude Code (CLI)

claude mcp add vibops vibops-mcp \
  -e VIBOPS_URL=https://vibops.example.com \
  -e VIBOPS_TOKEN=your-token-here

Available tools

Observation (read-only)

Tool Description
list_clusters List clusters and GPU utilisation
list_kubectl_contexts List available kubectl contexts
get_cluster_deployments Live K8s deployment status for a cluster
get_cluster_rate Get configured GPU cost rate for a cluster
list_jobs List recent jobs with optional filters
get_job Get job details and result
get_gpu_metrics Hourly GPU utilisation time-series
get_workload_breakdown Job count by workload type
get_mttr Mean Time To Resolve GPU alerts
get_cost_estimate Estimated GPU spend
list_gateways List registered gateways and status
list_alerts List GPU alerts (open or resolved)
list_secrets List secrets (names only, never values)
list_providers List configured AI/GPU cloud providers
list_pipelines List automation pipelines

Actions (write)

Tool Description
scale_cluster Scale a K8s deployment or node pool
deploy_model Deploy an AI model onto a GPU cluster
helm_upgrade Run helm upgrade --install
helm_uninstall Uninstall a Helm release
run_kubectl Run an arbitrary kubectl command
git_clone Clone a git repository
create_secret Store an encrypted secret
trigger_pipeline Manually trigger an automation pipeline

Configuration

Tool Description
set_cluster_rate Set GPU cost rate for a cluster (admin only)
register_gateway Register a new gateway (returns one-time token)
delete_gateway Revoke a gateway

Example prompts

"What's our GPU utilisation trend over the last 7 days?"
"Show me the cost breakdown per cluster this week."
"Deploy llama3:8b on vibops-dev with 2 replicas."
"Which clusters have open critical GPU alerts?"
"Scale the inference namespace to 4 replicas on prod-cluster."
"What's our MTTR for critical alerts?"

Roadmap

Wave 1 — Current (v0.1)

  • ✅ Kubernetes (generic — on-prem, Kind, kubeadm)
  • ✅ Any VibOps-connected cluster via gateway

Wave 2 — Q2 2026

  • 🔜 NVIDIA DGX Cloud (NGC API)
  • 🔜 AWS (EC2 GPU + EKS)
  • 🔜 GCP (A3/A2 + GKE)
  • 🔜 Azure (ND/NC series + AKS)

Wave 3 — Q3 2026

  • 🔜 CoreWeave, Lambda Labs, RunPod
  • 🔜 OVHcloud, Scaleway
  • 🔜 Dell APEX, HPE GreenLake

Want a provider prioritised? Open an issue.

Contributing

See CONTRIBUTING.md. All contributions require a DCO sign-off (git commit -s).

License

MIT — free to use, modify, and distribute. See LICENSE.

Built on FastMCP and the VibOps platform.

README copy captured when this server was indexed; it may lag the repository. The original is authoritative.

Questions

About Vibops MCP

How do I install Vibops MCP?

No package has been published for this server, so install it from source: clone the repository and follow its README.

Is Vibops MCP safe to use with an AI agent?

Its trust score is 39 out of 100 (low). It passes 1 of the 1 static security checks run so far. It has no ConduID identity yet, so agent calls to it are not receipted.

Is Vibops MCP still maintained?

Conduid hasn't recorded a commit date for this repository yet. Check the repository directly for recent activity.