mnvitop-mcp
Related Servers
Alternatives to mnvitop-mcp
No user-submitted related servers found.
Related Servers
- FlicenseNot gradedqualityAmaintenanceAn MCP server for monitoring and managing multi-cluster Slurm GPU jobs, enabling AI agents to execute commands, check allocations, and explore logs across HPC clusters.1-
- AlicenseNot gradedqualityDmaintenanceEnables AI agents to orchestrate a heterogeneous machine fleet via SSH, with unified command execution, file transfer, and dispatch of coding agents across platforms.1Apache 2.0
- FlicenseNot gradedqualityBmaintenanceEnables AI coding agents to run policy-constrained Python jobs on lab NVIDIA GPU hosts, including GPU inspection, device reservation, job launching and monitoring, and owner-scoped process stopping.2-
- FlicenseAqualityCmaintenanceEnables managing remote hosts from ~/.ssh/config over OpenSSH, including availability checks, command execution with sudo and timeouts, background jobs, SSH config and known_hosts management, and llms.txt-based documentation retrieval.19-
- FlicenseNot gradedqualityDmaintenanceEnables users to query Azure HPC/AI Kubernetes clusters for GPU node information and InfiniBand topology details through kubectl commands. Provides tools to list GPU pool nodes with their status and retrieve network topology labels for high-performance computing workloads.-
- FlicenseNot gradedqualityDmaintenanceEnables agents to manage Lambda Cloud GPU instances over SSH, including executing commands, running background jobs, transferring files, and terminating instances, while also exposing UI-configured capacity alerts and auto-provisioning settings.-
TDQS
Scored across 3 tools
Each tool has a clearly distinct purpose: listing configured hosts, querying live status, and finding placement for GPU jobs. No overlap or ambiguity between them.
Two tools use verb_noun pattern (list_hosts, find_gpus) while fleet_status is a noun phrase, creating a minor inconsistency. However, the names are short, clear, and follow a predictable theme of fleet management.
Three tools are ideal for a focused GPU fleet monitoring and placement server. Each tool serves a necessary and non-redundant function, and the count is well within the recommended range.
The server covers listing, status probing, and placement suggestion, which are core to its stated purpose. Minor gaps exist (e.g., no tool to modify host configuration or trigger actions), but for monitoring and placement discovery, it is complete.