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Related Servers

Alternatives to kwctl

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    Related Servers

    • A
      license
      A
      quality
      B
      maintenance
      Jungle Grid MCP Server lets AI agents submit, estimate, monitor, and retrieve logs for GPU workloads through Jungle Grid. It enables agentic execution for inference, training, fine-tuning, and batch jobs without manually choosing GPU providers or infrastructure.
      8
      13 npm
      4
      MIT
    • F
      license
      Not graded
      quality
      B
      maintenance
      MCP server for renting real GPUs from the terminal. Enables browsing, renting, chatting, managing, and pooling GPU instances with per-second billing, designed for AI agents.
      76 npm
      1
      -
    • A
      license
      A
      quality
      A
      maintenance
      VibOps MCP is the control plane between your AI agents and your GPU infrastructure. 74 tools covering: GPU fleet management (deploy, scale, monitor across NVIDIA, AMD, Intel, AWS, Google, Groq), Agent Infrastructure Control Plane (per-agent GPU cost, budget enforcement, model policies, dependency graph), governance (AI Act, SOC 2, immutable HMAC audit chain), and GPU FinOps (chargeback, waste..)..
      74
      18
      MIT
    • F
      license
      Not graded
      quality
      A
      maintenance
      An 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
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    TDQS

    A4.1/5.0

    Scored across 1 tool

    Disambiguation5/5

    There is only one tool, deploy_gpu_node, so there is no possibility of confusing it with another tool. Its purpose is clearly provisioning GPU compute on Kilawatt Cloud.

    Naming Consistency5/5

    The single tool name deploy_gpu_node uses a clear snake_case verb_noun pattern. With only one tool, there is no inconsistency across the set.

    Tool Count3/5

    A single tool is borderline thin for a cloud provisioning server, even though the tool itself is substantial. The rubric treats 1-2 tools as borderline, so it is not clearly well-scoped or clearly mismatched.

    Completeness2/5

    The surface only covers provisioning/deployment via deploy_gpu_node. There are no tools to list, inspect, update, stop, or terminate existing GPU nodes, leaving significant lifecycle gaps for agents managing real infrastructure.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues