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gpu-bridge-mcp-server

by gpu-bridge
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    Deploy Server
    One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

    TDQS

    A4/5.0

    Scored across 5 tools

    Disambiguation5/5

    Each tool has a clearly distinct purpose with no overlap: balance checking, catalog listing, cost estimation, job execution, and status monitoring. The descriptions make it unambiguous which tool to use for each task, preventing misselection.

    Naming Consistency5/5

    All tools follow a consistent 'gpu_' prefix with descriptive suffixes (balance, catalog, estimate, run, status). This verb_noun pattern is uniform throughout, making the tool set predictable and easy to navigate.

    Tool Count5/5

    With 5 tools, this server is well-scoped for its GPU service management purpose. Each tool earns its place by covering essential operations: account management, service discovery, cost estimation, job execution, and status tracking, without being overly sparse or bloated.

    Completeness5/5

    The tool set provides complete coverage for the GPU service lifecycle: discover services (catalog), estimate costs, run jobs, monitor status, and manage account (balance). No obvious gaps exist; agents can perform end-to-end workflows without dead ends.

    Maintenance

    ActivityInactive
    ResponsivenessUnresponsive

    Resources