# Celery MCP

> Use this tool when you need to manage and monitor distributed task queues, and control asynchronous job execution through natural language inputs. It solves problems related to task management, worker statistics monitoring, and job execution control, providing outputs such as task status and worker performance metrics. Ideal for use cases requiring efficient task queue management and automation in distributed systems.

Canonical page: https://skillsregistry.net/skills/joeyrubas-celery-mcp  
JSON: https://api.skillsregistry.net/v1/skills/joeyrubas-celery-mcp

## Description

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

## Trust

- **Trust score (0–1):** 0.99
- **Verification tier:** verified
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** monitoring
- **Updated:** 2026-09-19

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/p539chcbg2)
- **Repository:** <https://github.com/JoeyRubas/celery-mcp>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "joeyrubas-celery-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/joeyrubas-celery-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/joeyrubas-celery-mcp/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt