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cloudprice-mcp

by Albaker-Group
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Python
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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

    A4.1/5.0

    Scored across 14 tools

    Disambiguation4/5

    Most tools have clearly distinct purposes: compare_clouds for single VM, compare_compute_inventory for bulk compute, compare_workload for combined compute+storage, etc. However, assess_migration and compare_total_cost_of_ownership overlap in projecting workload costs, and compare_workload overlaps with separate inventory tools, causing minor ambiguity.

    Naming Consistency4/5

    Names follow a mostly consistent pattern: 'compare_' for multi-cloud comparisons, 'get_' for single-cloud lookups, and specialized verbs like 'assess_', 'find_', 'optimize_'. Minor variations exist (e.g., compare_total_cost_of_ownership vs compare_clouds) but overall readable and predictable.

    Tool Count5/5

    14 tools is well-scoped for a cloud pricing server. Each tool covers a distinct pricing scenario (single VM, bulk compute, storage, egress, databases, migration, TCO, commitment), avoiding redundancy without missing critical functionality.

    Completeness4/5

    The tool set covers core compute, storage, egress, database, migration, and TCO scenarios. Notable gaps include non-PostgreSQL databases, serverless compute, and advanced networking costs (e.g., VPC peering, load balancers). Descriptions acknowledge missing features, which agents can work around.

    Maintenance

    ActivityMaintained
    ResponsivenessUnresponsive

    Resources