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Darius1223

celery-flower-mcp

by Darius1223
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Python
Remote

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    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

    B3/5.0

    Scored across 21 tools

    Disambiguation4/5

    Most tools are distinct (e.g., list_workers vs. shutdown_worker), but some overlap exists: create_task vs. apply_task vs. async_apply_task could be confused, and get_task_result vs. get_task_info are similar. However, descriptions clarify the differences.

    Naming Consistency4/5

    The majority follow a clear verb_noun pattern (list_*, get_*, set_*, create_, apply_*, etc.). There are minor deviations like 'healthcheck' (instead of check_health) and 'autoscale_worker_pool' (verb+noun with no underscore), but overall consistent.

    Tool Count4/5

    21 tools is on the higher side but justified given the breadth of Celery/Flower management (workers, tasks, queues, health). The count is within the heavy range but not excessive for a complex domain.

    Completeness4/5

    The surface covers worker management (list, shutdown, restart, scale), task lifecycle (apply, send, revoke, abort, get results), and queue control (add/cancel consumer, get lengths). Missing: task retry or purge, but most essential operations are present.

    Maintenance

    ActivityInactive
    ResponsivenessNo issues

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