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Cloud Run MCP Server

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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

    A3.6/5.0

    Scored across 8 tools

    Disambiguation4/5

    Most tools have distinct purposes, but the three deployment tools (deploy_file_contents, deploy_local_files, deploy_local_folder) could cause confusion as they all handle deployment with subtle differences in input source. The other tools (create_project, get_service, get_service_log, list_projects, list_services) are clearly differentiated by their target resources and actions.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern with snake_case, such as create_project, deploy_file_contents, get_service, and list_services. There are no deviations in naming conventions, making the set predictable and easy to parse.

    Tool Count5/5

    With 8 tools, the server is well-scoped for managing Cloud Run deployments and related GCP projects. The count is reasonable, covering core operations like deployment, service management, and project handling without being overwhelming or insufficient.

    Completeness4/5

    The tool set covers key workflows for Cloud Run, including deployment, service retrieval, logging, and project management. Minor gaps exist, such as missing update or delete operations for services or projects, but agents can likely work around these with the provided tools for basic deployment and monitoring tasks.

    Maintenance

    ActivitySlowing
    ResponsivenessUnresponsive

    Resources