automation-queue-mcp

An MCP (Model Context Protocol) server that lets an LLM like Claude inspect and control an automation job queue — list jobs, check status, trigger new runs, retry failures, and pull queue-wide stats through natural language.

Why I built this

Over several years leading platform engineering for enterprise RPA (UiPath queues triggered via AWS Lambda, robot/machine lifecycle, license and infrastructure administration), I kept coming back to the same question: what would it look like if an LLM could actually operate that queue directly, instead of a human checking a dashboard and manually re-triggering failed jobs?

This project is a generalized, non-proprietary version of that idea — an MCP server exposing the operations any automation queue needs (list, inspect, trigger, retry, stats) so an LLM client can reason about and manage automation jobs conversationally.

It uses an in-memory mock queue so it's safe to run and explore immediately with no setup. Swap job_queue.py for a real backend (REST API, database, Orchestrator client) to point this at a live automation environment.

Related MCP server: Hatchet MCP Server

What it does

Example interaction (via Claude)

You: What's failed in the queue right now?

Claude: (calls list_jobs with status_filter="failed") Two jobs have failed: EligibilityCheck_Workflow on BOT-VM-02 (2 retries already) and ExceptionHandling_Workflow on BOT-VM-04 (1 retry). Want me to retry either of them?

You: Retry the eligibility one.

Claude: (calls retry_failed_job with job_id=2) Done — it's back in the queue, now on retry #3.

Getting started

git clone https://github.com/<your-username>/automation-queue-mcp.git
cd automation-queue-mcp
python -m venv venv
source venv/bin/activate   # Windows: venv\Scripts\activate
pip install -r requirements.txt
python server.py

Connecting it to Claude Desktop

Add the server to your Claude Desktop config (see examples/claude_desktop_config.json for a template):

{
  "mcpServers": {
    "automation-queue": {
      "command": "python",
      "args": ["/absolute/path/to/automation-queue-mcp/server.py"]
    }
  }
}

Restart Claude Desktop, and the five tools above become available in conversation.

Project structure

automation-queue-mcp/
├── server.py              # MCP server + tool definitions
├── job_queue.py            # In-memory mock job queue (swap for a real backend)
├── requirements.txt
├── examples/
│   └── claude_desktop_config.json
└── LICENSE

Extending this

The mock JobQueue class in job_queue.py is intentionally isolated from the MCP server logic in server.py — to connect this to a real automation system, you only need to reimplement JobQueue's five methods (list_jobs, get_job, queue_stats, trigger_job, retry_job) against your actual queue/API. The MCP tool layer doesn't need to change.

Background

Built by John Samuel Jacob David Ravichandran — Technical Lead background in enterprise intelligent automation, platform engineering, and healthcare RPA. More at LinkedIn.

License

MIT — see LICENSE.