Qarote ships RabbitMQ monitoring with a built-in MCP endpoint. Plug Claude Desktop or Cursor in under 5 minutes — the agent pulls your incidents, reads the firehose evidence, and returns the root cause in your workflow, not a dashboard tab.
No exporter, no Grafana, no configRabbitMQ 3.x & 4.x
list_incidents · get_incidentorders.incoming lost its 3 consumers at 15:06; depth is climbing ~8k/min with zero drain — likely a crashed worker downstream.The fix took five minutes.
The diagnosis took forty.
Qarote is the gap between those two numbers.
Most RabbitMQ tooling stops at metrics. Qarote ships a deterministic incident engine and managed root-cause analysis behind one MCP surface your agent already speaks — so you debug by asking, in the chat you're already in.
Point Qarote at your Management HTTP API over TLS. No exporter, no agent on the box.
Generate an API key scoped to your workspace. Free incident tools, or unlock Explain.
Drop the server into your .mcp.json. Claude Code, Cursor, Copilot — all the same.
"What's wrong with my RabbitMQ?" The agent calls the tools and explains the root cause.
list_incidentsopen incidents, rankedget_incidentone incident, full detaillist_config_findingsanti-patterns foundlist_serversbrokers under watchlist_queuesqueues + stateget_overviewcluster healthpingconnectivity checkexplain_incidentLLM root-cause, in chatDeterministic detection is free and stays free. explain_incident takes the incident plus the surrounding broker state and writes the root-cause line your agent reads back to you. Run it on our managed model, or a local Ollama model when self-hosted.
No Prometheus exporter to deploy. No Grafana to wire. No scrape config to babysit. Three steps from broker to a working agent surface.
Give Qarote your broker's Management HTTP API URL and read-only credentials, over TLS. It works against RabbitMQ 3.x and 4.x, single-node or clustered, including CloudAMQP and Amazon MQ.
The rules engine begins scanning immediately — incidents, depth anomalies, dropped consumers, and config anti-patterns. No baseline period, no dashboards to build.
Add the Qarote MCP server to your editor's config and your agent can call every tool. Ask it a question; it does the clicking for you.
{ "mcpServers": { "qarote": { "command": "npx", "args": ["-y", "@qarote/mcp"], "env": { "QAROTE_API_KEY": "qa_live_••••••••" } } }}# self-hosted? point at your own URL# QAROTE_BASE_URL=https://qarote.internalA deterministic rules engine watches live state for incidents, and a config scan flags the structural problems that turn into 3 a.m. pages. Every finding is something your agent can read back to you.
Live, rules-based — fires the moment broker state crosses a threshold. Free and open source.
consumers → 0orders.incoming lost all 3 consumers at 15:06; depth climbing ~8k/min with zero drain.
depth anomalypayments.capture depth up 14× over baseline with publish rate flat — drain has stalled.
ack rate → 0webhooks.delivery is redelivering without acking — a likely poison-message loop.
Catches RabbitMQ anti-patterns in your topology before they cause an incident.
missing DLX5 queues have no dead-letter exchange — rejected messages vanish silently.
idle no-consumer queue3 durable queues have had zero consumers for 7+ days — likely orphaned by a deploy.
default-exchange overuse82% of publishes route through the default exchange — no routing flexibility, hard to evolve.
Plus topology visualization to see the whole graph, and alerting via email, Slack, and webhooks when something fires.
The built-in plugin is fine for a quick look. A metrics stack is powerful if you assemble it. Qarote is fast to value, multi-broker, and the only one that explains incidents and answers to your agent. It complements a metrics stack — it doesn't replace it.
Cloud-hosted when you want it managed. Self-hosted when you don’t. The self-hosted path is built so nothing has to phone home — including the AI.
Self-hosted Qarote validates its license with offline JWT verification. No callback to our servers, no telemetry beacon, no dependency on our uptime for yours.
Point explain_incident at a local Ollama model and root-cause analysis runs on your hardware. Your broker state never leaves your network.
The incident-detection engine and the free MCP tools are MIT-licensed and open source. Read the rules, run the core, trust what it does.
20 questions across queues, exchanges, consumers, and production patterns. Get a score, a tier verdict, and see exactly where your gaps are.
Incident detection and the MCP tools are free and open source. The paid tiers add managed root-cause analysis, more brokers, and team controls.
The open-source core. Monitoring, detection, and the read MCP tools.
For individuals and small teams. Adds AI root-cause and full alerting.
For platform teams. SSO, managed AI, audit, and security controls.
Everything you need to know about Qarote
Qarote is a RabbitMQ monitoring dashboard that replaces the default Management Plugin with real-time queue, exchange, and node monitoring. It connects securely via the Management HTTP API over TLS and works with both cloud services (CloudAMQP, Amazon MQ) and self-hosted instances. The core monitoring tier is free forever with no credit card required — paid plans add multi-server support, alerting, and team collaboration.
Qarote is built for developers, DevOps engineers, and SREs who use RabbitMQ and want better visibility without the complexity of Prometheus and Grafana. Whether you run a single instance or dozens of clusters across environments, Qarote helps you spot queue backlogs before they cause outages and troubleshoot routing issues faster. Getting started takes under two minutes.
Yes. All connections to your RabbitMQ servers use TLS encryption. Qarote reads only the metrics exposed by the Management HTTP API — it never stores message payloads or credentials. For teams with strict compliance needs, Qarote can be fully self-hosted on your own infrastructure, ensuring monitoring data never leaves your network. Self-hosted deployments use offline license validation with no internet connection required after activation.
They serve different purposes and complement each other well. Setting up Prometheus and Grafana for RabbitMQ means installing exporters, configuring scrape targets, building dashboards from scratch, and writing PromQL queries — then maintaining everything as versions evolve. Qarote gives you purpose-built RabbitMQ monitoring with zero configuration: connect your server and start monitoring immediately, with pre-built dashboards, queue management controls, and alerting out of the box. For teams already running Prometheus, Qarote adds deeper RabbitMQ-specific insights alongside your existing stack.
Yes. You can deploy Qarote on your own infrastructure using Docker, Docker Compose, Dokku, or a standalone binary — the entire setup takes under five minutes. The Community edition is free and open source under the MIT license. Self-hosted paid plans unlock multi-server support, alerting, and team features. License validation works entirely offline with no internet connection needed after activation, making it suitable for air-gapped environments.
Qarote supports RabbitMQ 3.x and 4.x, including all current LTS and latest releases. It connects through the standard Management HTTP API — no additional plugins, exporters, or agents are required on your servers. Qarote is tested against both single-node and clustered deployments, as well as managed services like CloudAMQP and Amazon MQ.
Yes. Qarote fully supports clusters with automatic node discovery — no extra configuration needed. It shows both individual node metrics and cluster-wide aggregates in a unified view. You can track each node's health, monitor queue distribution across nodes, and receive alerts when nodes become unavailable or exceed resource thresholds.
Can't find the answer you're looking for? Please chat to our friendly team.