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mcp-server-celery

by taltal-beep
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Python
Remote

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    Deploy Server
    Shareable, User-Owned Context BackendPeople, applications, and agents read, write, and coordinate together in one context lake. Reach it over MCP, a CLI, a Python SDK, or REST.fulcradynamics.comAd

    TDQS

    B3.4/5.0

    Scored across 2 tools

    Disambiguation4/5

    The two tools target distinct resources: list_workers is worker-centric while queue_depths is queue-centric. There is minor overlap since both surface the worker-to-queue consumption mapping, but the primary purpose of each is clear.

    Naming Consistency4/5

    Both names are snake_case, which is consistent. However list_workers follows a verb_noun pattern while queue_depths is noun_noun, a minor deviation in convention.

    Tool Count3/5

    Two tools is thin for a Celery monitoring server, which typically covers tasks, queues, and workers. It is not extreme, but the surface feels under-scoped for the domain.

    Completeness2/5

    Celery monitoring spans workers, queues, and tasks, but only worker and queue visibility is offered. Task inspection (list tasks, task status, revoke) and queue management (purge) are notably absent, leaving significant gaps.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues

    Resources