"Celery" matching MCP servers:

This MCP server provides AI assistants with full control over Celery task queues by exposing all Celery Flower REST API endpoints as tools. It enables monitoring workers, managing tasks, inspecting queues, and controlling worker pools in real-time through natural language.

FastMCP server with read-only tools to monitor Redis — queue depths, Celery queue status, connected clients, server/memory info, and per-database key counts

Enables AI assistants to diagnose a Python backend stack — Postgres, Celery, Redis and logs — in a single tool call, returning findings, a merged timeline of events, and possible cause-effect chains. All checks are strictly read-only, so an assistant can inspect blocked queries, missing workers, queue backlogs, Redis memory pressure and log error spikes without ever modifying anything.