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      A Model Context Protocol (MCP) server that enables AI tools like chatbots to interact with and control Jenkins, allowing users to trigger jobs, check build statuses, and perform other Jenkins operations through natural language.
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    TDQS

    A3.6/5.0

    Scored across 17 tools

    Disambiguation3/5

    Most tools target distinct resources, but there is real overlap among queue-related tools (get_queue_item vs wait_for_build vs get_queue) and deploy helpers (deploy vs deploy_tickets vs trigger_build). The detailed descriptions help disambiguate, but some tools could still be confusing to an agent.

    Naming Consistency4/5

    Tool names use consistent snake_case and mostly follow a verb_noun pattern: list_* and get_* for reads, trigger_build, deploy, resolve_job_name for actions. The mix of list/get and imperative verbs is minor and still predictable.

    Tool Count4/5

    17 tools is slightly above the ideal 3-15 range, but the count is justified by combining core Jenkins introspection with deployment-specific and ticket-verification workflows. Each tool has a reasonably distinct niche.

    Completeness4/5

    The toolset covers job discovery, build triggering, queue monitoring, build results, logs, deployment configuration, and ticket-based deployment verification. Minor gaps such as cancel/abort build or job CRUD exist, but the core CI/CD and deployment workflows are well covered.

    Maintenance

    ActivitySlowing
    ResponsivenessNo issues