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MCP-Ambari-API

by call518
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Python
Hybrid

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    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

    A3.5/5.0

    Scored across 30 tools

    Disambiguation3/5

    Several tools overlap significantly: get_service_status, get_service_details, and get_cluster_services all provide service state information; get_alerts_history and get_current_alerts are redundant (one is explicitly deprecated); dump_configurations supersedes other config tools but those aren't present. The service-level vs component-level distinction is clear, but the service status/details overlap creates ambiguity.

    Naming Consistency4/5

    Most tools follow a consistent verb_noun pattern (get_, list_, start_, stop_, restart_, dump_, query_). Minor deviations include hdfs_dfadmin_report (no underscore after hdfs) and get_prompt_template (not a cluster operation), but overall the pattern is predictable.

    Tool Count3/5

    30 tools is on the heavy side for an Ambari cluster management server. While many are justified (service lifecycle, host components, requests, alerts, metrics), the count is inflated by deprecated wrappers, overlapping service info tools, and a prompt template tool that doesn't fit the domain.

    Completeness4/5

    The server covers the core Ambari lifecycle well: cluster info, service start/stop/restart, host component operations, request tracking, alerts, hosts, users, and metrics. Minor gaps include no service configuration update tool (only dump_configurations) and no user management (create/delete/update), but the main operational surface is solid.

    Maintenance

    ActivityMaintained
    ResponsivenessUnresponsive

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