"Celery" matching MCP servers:

Enables interaction with Celery distributed task queues through MCP tools. Supports task management, monitoring worker statistics, and controlling asynchronous job execution through natural language.

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

A Django-native MCP application and tool registration framework inspired by Celery, providing async tool definitions, autodiscovery, and stdio/Streamable HTTP serving built on the official MCP Python SDK.

Enables asynchronous task execution and scheduling using RabbitMQ, Celery, and Redis/SQLite. Supports immediate background task execution, scheduled tasks with ISO 8601 timestamps, task status monitoring, cancellation, and completion notifications.